Adaptive estimation and discrimination of Holevo-Werner channels
Directory of Open Access Journals (Sweden)
Cope Thomas P. W.
2017-12-01
Full Text Available The class of quantum states known as Werner states have several interesting properties, which often serve to illuminate unusual properties of quantum information. Closely related to these states are the Holevo- Werner channels whose Choi matrices are Werner states. Exploiting the fact that these channels are teleportation covariant, and therefore simulable by teleportation, we compute the ultimate precision in the adaptive estimation of their channel-defining parameter. Similarly, we bound the minimum error probability affecting the adaptive discrimination of any two of these channels. In this case, we prove an analytical formula for the quantum Chernoff bound which also has a direct counterpart for the class of depolarizing channels. Our work exploits previous methods established in [Pirandola and Lupo, PRL 118, 100502 (2017] to set the metrological limits associated with this interesting class of quantum channels at any finite dimension.
RLS Channel Estimation with Adaptive Forgetting Factor for DS-CDMA Frequency-Domain Equalization
Kojima, Yohei; Tomeba, Hiromichi; Takeda, Kazuaki; Adachi, Fumiyuki
Frequency-domain equalization (FDE) based on the minimum mean square error (MMSE) criterion can increase the downlink bit error rate (BER) performance of DS-CDMA beyond that possible with conventional rake combining in a frequency-selective fading channel. FDE requires accurate channel estimation. Recently, we proposed a pilot-assisted channel estimation (CE) based on the MMSE criterion. Using MMSE-CE, the channel estimation accuracy is almost insensitive to the pilot chip sequence, and a good BER performance is achieved. In this paper, we propose a channel estimation scheme using one-tap recursive least square (RLS) algorithm, where the forgetting factor is adapted to the changing channel condition by the least mean square (LMS)algorithm, for DS-CDMA with FDE. We evaluate the BER performance using RLS-CE with adaptive forgetting factor in a frequency-selective fast Rayleigh fading channel by computer simulation.
Sparse Adaptive Channel Estimation Based on lp-Norm-Penalized Affine Projection Algorithm
Directory of Open Access Journals (Sweden)
Yingsong Li
2014-01-01
Full Text Available We propose an lp-norm-penalized affine projection algorithm (LP-APA for broadband multipath adaptive channel estimations. The proposed LP-APA is realized by incorporating an lp-norm into the cost function of the conventional affine projection algorithm (APA to exploit the sparsity property of the broadband wireless multipath channel, by which the convergence speed and steady-state performance of the APA are significantly improved. The implementation of the LP-APA is equivalent to adding a zero attractor to its iterations. The simulation results, which are obtained from a sparse channel estimation, demonstrate that the proposed LP-APA can efficiently improve channel estimation performance in terms of both the convergence speed and steady-state performance when the channel is exactly sparse.
A novel adaptive joint power control algorithm with channel estimation in a CDMA cellular system
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
Joint power control has advantages of multi-user detection and power control; and it can combat the multi-access interference and the near-far problem. A novel adaptive joint power control algorithm with channel estimation in a CDMA cellular system was designed. Simulation results show that the algorithm can control the power not only quickly but also precisely with a time change. The method is useful for increasing system capacity.
Directory of Open Access Journals (Sweden)
Liu KJ Ray
2002-01-01
Full Text Available Orthogonal frequency division multiplexing (OFDM is an effective technique for the future 3G communications because of its great immunity to impulse noise and intersymbol interference. The channel estimation is a crucial aspect in the design of OFDM systems. In this work, we propose a channel estimation algorithm based on a time-frequency polynomial model of the fading multipath channels. The algorithm exploits the correlation of the channel responses in both time and frequency domains and hence reduce more noise than the methods using only time or frequency polynomial model. The estimator is also more robust compared to the existing methods based on Fourier transform. The simulation shows that it has more than improvement in terms of mean-squared estimation error under some practical channel conditions. The algorithm needs little prior knowledge about the delay and fading properties of the channel. The algorithm can be implemented recursively and can adjust itself to follow the variation of the channel statistics.
Directory of Open Access Journals (Sweden)
P. Beinschob
2010-11-01
Full Text Available In this paper we present a novel approach in Multiple-Input Multiple Output (MIMO Orthogonal Frequency Division Multiplexing (OFDM channel estimation technique based on a Decision Directed Recursive Least Squares (RLS algorithm in which no pilot symbols need to be integrated in the data after a short initial preamble. The novelty and key concept of the proposed technique is the block-wise causal and anti-causal RLS processing that yields two independent processings of RLS along with the associated decisions. Due to the usage of low density parity check (LDPC channel code, the receiver operates with soft information, which enables us to introduce a new modification of the Turbo principle as well as a simple information combining approach based on approximated aposteriori log-likelihood ratios (LLRs. Although the computational complexity is increased by both of our approaches, the latter is relatively less complex than the former. Simulation results show that these implementations outperform the simple RLS-DDCE algorithm and yield lower bit error rates (BER and more accurate channel estimates.
DEFF Research Database (Denmark)
2015-01-01
A method includes determining a sequence of first coefficient estimates of a communication channel based on a sequence of pilots arranged according to a known pilot pattern and based on a receive signal, wherein the receive signal is based on the sequence of pilots transmitted over the communicat......A method includes determining a sequence of first coefficient estimates of a communication channel based on a sequence of pilots arranged according to a known pilot pattern and based on a receive signal, wherein the receive signal is based on the sequence of pilots transmitted over...... the communication channel. The method further includes determining a sequence of second coefficient estimates of the communication channel based on a decomposition of the first coefficient estimates in a dictionary matrix and a sparse vector of the second coefficient estimates, the dictionary matrix including...... filter characteristics of at least one known transceiver filter arranged in the communication channel....
Directory of Open Access Journals (Sweden)
Zoltán Endre Rákossy
2012-01-01
Full Text Available Due to the fast changing wireless communication standards coupled with strict performance constraints, the demand for flexible yet high-performance architectures is increasing. To tackle the flexibility requirement, software-defined radio (SDR is emerging as an obvious solution, where the underlying hardware implementation is tuned via software layers to the varied standards depending on power-performance and quality requirements leading to adaptable, cognitive radio. In this paper, we conduct a case study for representatives of two complexity classes of WCDMA channel estimation algorithms and explore the effect of flexibility on energy efficiency using different implementation options. Furthermore, we propose new design guidelines for both highly specialized architectures and highly flexible architectures using high-level synthesis, to enable the required performance and flexibility to support multiple applications. Our experiments with various design points show that the resulting architectures meet the performance constraints of WCDMA and a wide range of options are offered for tuning such architectures depending on power/performance/area constraints of SDR.
Adaptive Spectral Doppler Estimation
DEFF Research Database (Denmark)
Gran, Fredrik; Jakobsson, Andreas; Jensen, Jørgen Arendt
2009-01-01
. The methods can also provide better quality of the estimated power spectral density (PSD) of the blood signal. Adaptive spectral estimation techniques are known to pro- vide good spectral resolution and contrast even when the ob- servation window is very short. The 2 adaptive techniques are tested......In this paper, 2 adaptive spectral estimation techniques are analyzed for spectral Doppler ultrasound. The purpose is to minimize the observation window needed to estimate the spectrogram to provide a better temporal resolution and gain more flexibility when designing the data acquisition sequence...... and compared with the averaged periodogram (Welch’s method). The blood power spectral capon (BPC) method is based on a standard minimum variance technique adapted to account for both averaging over slow-time and depth. The blood amplitude and phase estimation technique (BAPES) is based on finding a set...
Adaptive RAC codes employing statistical channel evaluation ...
African Journals Online (AJOL)
An adaptive encoding technique using row and column array (RAC) codes employing a different number of parity columns that depends on the channel state is proposed in this paper. The trellises of the proposed adaptive codes and a statistical channel evaluation technique employing these trellises are designed and ...
Six-channel adaptive fibre-optic interferometer
Energy Technology Data Exchange (ETDEWEB)
Romashko, R V; Bezruk, M N; Kamshilin, A A; Kulchin, Yurii N
2012-06-30
We have proposed and analysed a scheme for the multiplexing of orthogonal dynamic holograms in photorefractive crystals which ensures almost zero cross talk between the holographic channels upon phase demodulation. A six-channel adaptive fibre-optic interferometer was built, and the detection limit for small phase fluctuations in the channels of the interferometer was determined to be 2.1 Multiplication-Sign 10{sup -8} rad W{sup 1/2} Hz{sup -1/2}. The channel multiplexing capacity of the interferometer was estimated. The formation of 70 channels such that their optical fields completely overlap in the crystal reduces the relative detection limit in the working channel by just 10 %. We found conditions under which the maximum cross talk between the channels was within the intrinsic noise level in the channels (-47 dB).
Channel Estimation in DCT-Based OFDM
Wang, Yulin; Zhang, Gengxin; Xie, Zhidong; Hu, Jing
2014-01-01
This paper derives the channel estimation of a discrete cosine transform- (DCT-) based orthogonal frequency-division multiplexing (OFDM) system over a frequency-selective multipath fading channel. Channel estimation has been proved to improve system throughput and performance by allowing for coherent demodulation. Pilot-aided methods are traditionally used to learn the channel response. Least square (LS) and mean square error estimators (MMSE) are investigated. We also study a compressed sensing (CS) based channel estimation, which takes the sparse property of wireless channel into account. Simulation results have shown that the CS based channel estimation is expected to have better performance than LS. However MMSE can achieve optimal performance because of prior knowledge of the channel statistic. PMID:24757439
Directory of Open Access Journals (Sweden)
Aitzol Astigarraga
2016-01-01
Full Text Available Brain-Computer Interfaces (BCIs have become a research field with interesting applications, and it can be inferred from published papers that different persons activate different parts of the brain to perform the same action. This paper presents a personalized interface design method, for electroencephalogram- (EEG- based BCIs, based on channel selection. We describe a novel two-step method in which firstly a computationally inexpensive greedy algorithm finds an adequate search range; and, then, an Estimation of Distribution Algorithm (EDA is applied in the reduced range to obtain the optimal channel subset. The use of the EDA allows us to select the most interacting channels subset, removing the irrelevant and noisy ones, thus selecting the most discriminative subset of channels for each user improving accuracy. The method is tested on the IIIa dataset from the BCI competition III. Experimental results show that the resulting channel subset is consistent with motor-imaginary-related neurophysiological principles and, on the other hand, optimizes performance reducing the number of channels.
Fuel channel closure and adapter
International Nuclear Information System (INIS)
Cashen, W.S.
1985-01-01
This invention provides a mechanical closure/actuating ram combination particularly suited for use in sealing the ends of the pressure tubes when a CANDU-type reactor is refueled. It provides a cluster that may be inserted into a fuel channel end fitting to provide at least partial closing off of a pressure tube while permitting the disengagement of the fueling machine and its withdrawal from the closure for other purposes. The invention also provides a ram/closure combination wherein the application of loading force to a deformable sealing disk is regulated by a massive load bar component forming part of the fueling machine and being therefore accessible for maintenance or replacement
CFO and channel estimation for MISO-OFDM systems
Ladaycia, Abdelhamid
2017-11-02
This study deals with the joint channel and carrier frequency offset (CFO) estimation in a Multiple Input Single Output (MISO) communications system. This problem arises in OFDM (Orthogonal Frequency Division Multiplexing) based multi-relay transmission protocols such that the geo-routing one proposed by A. Bader et al in 2012. Indeed, the outstanding performance of this multi-hop relaying scheme relies heavily on the channel and CFO estimation quality at the PHY layer. In this work, two approaches are considered: The first is based on estimating the overall channel (including the CFO) as a time-varying one using an adaptive scheme under the assumption of small or moderate CFOs while the second one performs separately, the channel and CFO parameters estimation based on the considered data model. The two solutions are analyzed and compared in terms of performance, cost and convergence rate.
Adaptive noise canceling of electrocardiogram artifacts in single channel electroencephalogram.
Cho, Sung Pil; Song, Mi Hye; Park, Young Cheol; Choi, Ho Seon; Lee, Kyoung Joung
2007-01-01
A new method for estimating and eliminating electrocardiogram (ECG) artifacts from single channel scalp electroencephalogram (EEG) is proposed. The proposed method consists of emphasis of QRS complex from EEG using least squares acceleration (LSA) filter, generation of synchronized pulse with R-peak and ECG artifacts estimation and elimination using adaptive filter. The performance of the proposed method was evaluated using simulated and real EEG recordings, we found that the ECG artifacts were successfully estimated and eliminated in comparison with the conventional multi-channel techniques, which are independent component analysis (ICA) and ensemble average (EA) method. From this we can conclude that the proposed method is useful for the detecting and eliminating the ECG artifacts from single channel EEG and simple to use for ambulatory/portable EEG monitoring system.
A new adaptive blind channel identification algorithm
International Nuclear Information System (INIS)
Peng Dezhong; Xiang Yong; Yi Zhang
2009-01-01
This paper addresses the blind identification of single-input multiple-output (SIMO) finite-impulse-response (FIR) systems. We first propose a new adaptive algorithm for the blind identification of SIMO FIR systems. Then, its convergence property is analyzed systematically. It is shown that under some mild conditions, the proposed algorithm is guaranteed to converge in the mean to the true channel impulse responses in both noisy and noiseless cases. Simulations are carried out to demonstrate the theoretical results.
Multi-Channel Maximum Likelihood Pitch Estimation
DEFF Research Database (Denmark)
Christensen, Mads Græsbøll
2012-01-01
In this paper, a method for multi-channel pitch estimation is proposed. The method is a maximum likelihood estimator and is based on a parametric model where the signals in the various channels share the same fundamental frequency but can have different amplitudes, phases, and noise characteristics....... This essentially means that the model allows for different conditions in the various channels, like different signal-to-noise ratios, microphone characteristics and reverberation. Moreover, the method does not assume that a certain array structure is used but rather relies on a more general model and is hence...
Efficient channel estimation in massive MIMO systems - a distributed approach
Al-Naffouri, Tareq Y.
2016-01-01
We present two efficient algorithms for distributed estimation of channels in massive MIMO systems. The two cases of 1) generic, and 2) sparse channels is considered. The algorithms estimate the impulse response for each channel observed
Bayesian Inference Methods for Sparse Channel Estimation
DEFF Research Database (Denmark)
Pedersen, Niels Lovmand
2013-01-01
This thesis deals with sparse Bayesian learning (SBL) with application to radio channel estimation. As opposed to the classical approach for sparse signal representation, we focus on the problem of inferring complex signals. Our investigations within SBL constitute the basis for the development...... of Bayesian inference algorithms for sparse channel estimation. Sparse inference methods aim at finding the sparse representation of a signal given in some overcomplete dictionary of basis vectors. Within this context, one of our main contributions to the field of SBL is a hierarchical representation...... analysis of the complex prior representation, where we show that the ability to induce sparse estimates of a given prior heavily depends on the inference method used and, interestingly, whether real or complex variables are inferred. We also show that the Bayesian estimators derived from the proposed...
An Adaptive Channel Model for VBLAST in Vehicular Networks
Directory of Open Access Journals (Sweden)
Ghassan M. T. Abdalla
2009-01-01
Full Text Available The wireless transmission environment in vehicular ad hoc systems varies from line of sight with few surroundings to rich Rayleigh fading. An efficient communication system must adapt itself to these diverse conditions. Multiple antenna systems are known to provide superior performance compared to single antenna systems in terms of capacity and reliability. The correlation between the antennas has a great effect on the performance of MIMO systems. In this paper we introduce a novel adaptive channel model for MIMO-VBLAST systems in vehicular ad hoc networks. Using the proposed model, the correlation between the antennas was investigated. Although the line of sight is ideal for single antenna systems, it severely degrades the performance of VBLAST systems since it increases the correlation between the antennas. A channel update algorithm using single tap Kalman filters for VBLAST in flat fading channels has also been derived and evaluated. At 12 dB Es/N0, the new algorithm showed 50% reduction in the mean square error (MSE between the actual channel and the corresponding updated estimate compared to the MSE without update. The computational requirement of the proposed algorithm for a p×q VBLAST is 6p×q real multiplications and 4p×q real additions.
Channel Estimation and Optimal Power Allocation for a Multiple-Antenna OFDM System
Directory of Open Access Journals (Sweden)
Yao Kung
2002-01-01
Full Text Available We propose combining channel estimation and optimal power allocation approaches for a multiple-antenna orthogonal frequency division multiplexing (OFDM system in high-speed transmission applications. We develop a least-square channel estimation approach, derive the performance bound of the estimator, and investigate the optimal training sequences for initial channel acquisition. Based on the channel estimates, the optimal power allocation solution which maximizes the bandwidth efficiency is derived under power and quality of service (Qos (symbol error rate constraints. It is shown that combining channel tracking and adaptive power allocation can dramatically enhance the outage capacity of an OFDM multiple-antenna system when severing fading occurs.
Subspace Based Blind Sparse Channel Estimation
DEFF Research Database (Denmark)
Hayashi, Kazunori; Matsushima, Hiroki; Sakai, Hideaki
2012-01-01
The paper proposes a subspace based blind sparse channel estimation method using 1–2 optimization by replacing the 2–norm minimization in the conventional subspace based method by the 1–norm minimization problem. Numerical results confirm that the proposed method can significantly improve...
D-BLAST OFDM with Channel Estimation
Directory of Open Access Journals (Sweden)
Du Jianxuan
2004-01-01
Full Text Available Multiple-input and multiple-output (MIMO systems formed by multiple transmit and receive antennas can improve performance and increase capacity of wireless communication systems. Diagonal Bell Laboratories Layered Space-Time (D-BLAST structure offers a low-complexity solution for realizing the attractive capacity of MIMO systems. However, for broadband wireless communications, channel is frequency-selective and orthogonal frequency division multiplexing (OFDM has to be used with MIMO techniques to reduce system complexity. In this paper, we investigate D-BLAST for MIMO-OFDM systems. We develop a layerwise channel estimation algorithm which is robust to channel variation by exploiting the characteristic of the D-BLAST structure. Further improvement is made by subspace tracking to considerably reduce the error floor. Simulation results show that the layerwise estimators require 1 dB less signal-to-noise ratio (SNR than the traditional blockwise estimator for a word error rate (WER of when Doppler frequency is 40 Hz. Among the layerwise estimators, the subspace-tracking estimator provides a 0.8 dB gain for WER with 200 Hz Doppler frequency compared with the DFT-based estimator.
The Extended-Window Channel Estimator for Iterative Channel-and-Symbol Estimation
Directory of Open Access Journals (Sweden)
Barry John R
2005-01-01
Full Text Available The application of the expectation-maximization (EM algorithm to channel estimation results in a well-known iterative channel-and-symbol estimator (ICSE. The EM-ICSE iterates between a symbol estimator based on the forward-backward recursion (BCJR equalizer and a channel estimator, and may provide approximate maximum-likelihood blind or semiblind channel estimates. Nevertheless, the EM-ICSE has high complexity, and it is prone to misconvergence. In this paper, we propose the extended-window (EW estimator, a novel channel estimator for ICSE that can be used with any soft-output symbol estimator. Therefore, the symbol estimator may be chosen according to performance or complexity specifications. We show that the EW-ICSE, an ICSE that uses the EW estimator and the BCJR equalizer, is less complex and less susceptible to misconvergence than the EM-ICSE. Simulation results reveal that the EW-ICSE may converge faster than the EM-ICSE.
Multiuser TOA Estimation Algorithm in DS-CDMA Sparse Channel for Radiolocation
Kim, Sunwoo
This letter considers multiuser time delay estimation in a sparse channel environment for radiolocation. The generalized successive interference cancellation (GSIC) algorithm is used to eliminate the multiple access interference (MAI). To adapt GSIC to sparse channels the alternating maximization (AM) algorithm is considered, and the continuous time delay of each path is estimated without requiring a priori known data sequences.
Adaptive Combined Source and Channel Decoding with Modulation ...
African Journals Online (AJOL)
In this paper, an adaptive system employing combined source and channel decoding with modulation is proposed for slow Rayleigh fading channels. Huffman code is used as the source code and Convolutional code is used for error control. The adaptive scheme employs a family of Convolutional codes of different rates ...
A Robust Threshold for Iterative Channel Estimation in OFDM Systems
Directory of Open Access Journals (Sweden)
A. Kalaycioglu
2010-04-01
Full Text Available A novel threshold computation method for pilot symbol assisted iterative channel estimation in OFDM systems is considered. As the bits are transmitted in packets, the proposed technique is based on calculating a particular threshold for each data packet in order to select the reliable decoder output symbols to improve the channel estimation performance. Iteratively, additional pilot symbols are established according to the threshold and the channel is re-estimated with the new pilots inserted to the known channel estimation pilot set. The proposed threshold calculation method for selecting additional pilots performs better than non-iterative channel estimation, no threshold and fixed threshold techniques in poor HF channel simulations.
Comparison of Pilot Symbol Embedded Channel Estimation Algorithms
Directory of Open Access Journals (Sweden)
P. Kadlec
2009-12-01
Full Text Available In the paper, algorithms of the pilot symbol embedded channel estimation are compared. Attention is turned to the Least Square (LS channel estimation and the Sliding Correlator (SC algorithm. Both algorithms are implemented in Matlab to estimate the Channel Impulse Response (CIR of a channel exhibiting multi-path propagation. Algorithms are compared from the viewpoint of computational demands, influence of the Additive White Gaussian Noise (AWGN, an embedded pilot symbol and a computed CIR over the estimation error.
Adaptive vehicle motion estimation and prediction
Zhao, Liang; Thorpe, Chuck E.
1999-01-01
Accurate motion estimation and reliable maneuver prediction enable an automated car to react quickly and correctly to the rapid maneuvers of the other vehicles, and so allow safe and efficient navigation. In this paper, we present a car tracking system which provides motion estimation, maneuver prediction and detection of the tracked car. The three strategies employed - adaptive motion modeling, adaptive data sampling, and adaptive model switching probabilities - result in an adaptive interacting multiple model algorithm (AIMM). The experimental results on simulated and real data demonstrate that our tracking system is reliable, flexible, and robust. The adaptive tracking makes the system intelligent and useful in various autonomous driving tasks.
DFT-based channel estimation and noise variance estimation techniques for single-carrier FDMA
Huang, G; Nix, AR; Armour, SMD
2010-01-01
Practical frequency domain equalization (FDE) systems generally require knowledge of the channel and the noise variance to equalize the received signal in a frequency-selective fading channel. Accurate channel estimate and noise variance estimate are thus desirable to improve receiver performance. In this paper we investigate the performance of the denoise channel estimator and the approximate linear minimum mean square error (A-LMMSE) channel estimator with channel power delay profile (PDP) ...
Energy-efficient power allocation of two-hop cooperative systems with imperfect channel estimation
Amin, Osama
2015-06-08
Recently, much attention has been paid to the green design of wireless communication systems using energy efficiency (EE) metrics that should capture all energy consumption sources to deliver the required data. In this paper, we formulate an accurate EE metric for cooperative two-hop systems that use the amplify-and-forward relaying scheme. Different from the existing research that assumes the availability of perfect channel state information (CSI) at the communication cooperative nodes, we assume a practical scenario, where training pilots are used to estimate the channels. The estimated CSI can be used to adapt the available resources of the proposed system in order to maximize the EE. Two estimation strategies are assumed namely disintegrated channel estimation, which assumes the availability of channel estimator at the relay, and cascaded channel estimation, where the relay is not equipped with channel estimator and only forwards the received pilot(s) in order to let the destination estimate the cooperative link. The channel estimation cost is reflected on the EE metric by including the estimation error in the signal-to-noise term and considering the energy consumption during the estimation phase. Based on the formulated EE metric, we propose an energy-aware power allocation algorithm to maximize the EE of the cooperative system with channel estimation. Furthermore, we study the impact of the estimation parameters on the optimized EE performance via simulation examples.
Improved Sparse Channel Estimation for Cooperative Communication Systems
Directory of Open Access Journals (Sweden)
Guan Gui
2012-01-01
Full Text Available Accurate channel state information (CSI is necessary at receiver for coherent detection in amplify-and-forward (AF cooperative communication systems. To estimate the channel, traditional methods, that is, least squares (LS and least absolute shrinkage and selection operator (LASSO, are based on assumptions of either dense channel or global sparse channel. However, LS-based linear method neglects the inherent sparse structure information while LASSO-based sparse channel method cannot take full advantage of the prior information. Based on the partial sparse assumption of the cooperative channel model, we propose an improved channel estimation method with partial sparse constraint. At first, by using sparse decomposition theory, channel estimation is formulated as a compressive sensing problem. Secondly, the cooperative channel is reconstructed by LASSO with partial sparse constraint. Finally, numerical simulations are carried out to confirm the superiority of proposed methods over global sparse channel estimation methods.
Conveyance estimation in channels with emergent bank vegetation ...
African Journals Online (AJOL)
Emergent vegetation along the banks of a river channel influences its conveyance considerably. The total channel discharge can be estimated as the sum of the discharges of the vegetated and clear channel zones calculated separately. The vegetated zone discharge is often negligible, but can be estimated using ...
Concurrent signal combining and channel estimation in digital communications
Ormesher, Richard C [Albuquerque, NM; Mason, John J [Albuquerque, NM
2011-08-30
In the reception of digital information transmitted on a communication channel, a characteristic exhibited by the communication channel during transmission of the digital information is estimated based on a communication signal that represents the digital information and has been received via the communication channel. Concurrently with the estimating, the communication signal is used to decide what digital information was transmitted.
Li, Husheng; Betz, Sharon M.; Poor, H. Vincent
2007-05-01
This paper examines the performance of decision feedback based iterative channel estimation and multiuser detection in channel coded aperiodic DS-CDMA systems operating over multipath fading channels. First, explicit expressions describing the performance of channel estimation and parallel interference cancellation based multiuser detection are developed. These results are then combined to characterize the evolution of the performance of a system that iterates among channel estimation, multiuser detection and channel decoding. Sufficient conditions for convergence of this system to a unique fixed point are developed.
A Channelization-Based DOA Estimation Method for Wideband Signals
Directory of Open Access Journals (Sweden)
Rui Guo
2016-07-01
Full Text Available In this paper, we propose a novel direction of arrival (DOA estimation method for wideband signals with sensor arrays. The proposed method splits the wideband array output into multiple frequency sub-channels and estimates the signal parameters using a digital channelization receiver. Based on the output sub-channels, a channelization-based incoherent signal subspace method (Channelization-ISM and a channelization-based test of orthogonality of projected subspaces method (Channelization-TOPS are proposed. Channelization-ISM applies narrowband signal subspace methods on each sub-channel independently. Then the arithmetic mean or geometric mean of the estimated DOAs from each sub-channel gives the final result. Channelization-TOPS measures the orthogonality between the signal and the noise subspaces of the output sub-channels to estimate DOAs. The proposed channelization-based method isolates signals in different bandwidths reasonably and improves the output SNR. It outperforms the conventional ISM and TOPS methods on estimation accuracy and dynamic range, especially in real environments. Besides, the parallel processing architecture makes it easy to implement on hardware. A wideband digital array radar (DAR using direct wideband radio frequency (RF digitization is presented. Experiments carried out in a microwave anechoic chamber with the wideband DAR are presented to demonstrate the performance. The results verify the effectiveness of the proposed method.
Efficient collaborative sparse channel estimation in massive MIMO
Masood, Mudassir; Afify, Laila H.; Al-Naffouri, Tareq Y.
2015-01-01
We propose a method for estimation of sparse frequency selective channels within MIMO-OFDM systems. These channels are independently sparse and share a common support. The method estimates the impulse response for each channel observed by the antennas at the receiver. Estimation is performed in a coordinated manner by sharing minimal information among neighboring antennas to achieve results better than many contemporary methods. Simulations demonstrate the superior performance of the proposed method.
Efficient collaborative sparse channel estimation in massive MIMO
Masood, Mudassir
2015-08-12
We propose a method for estimation of sparse frequency selective channels within MIMO-OFDM systems. These channels are independently sparse and share a common support. The method estimates the impulse response for each channel observed by the antennas at the receiver. Estimation is performed in a coordinated manner by sharing minimal information among neighboring antennas to achieve results better than many contemporary methods. Simulations demonstrate the superior performance of the proposed method.
Mathematical models for estimating radio channels utilization when ...
African Journals Online (AJOL)
Definition of the radio channel utilization indicator is given. Mathematical models for radio channels utilization assessment by real-time flows transfer in the wireless self-organized network are presented. Estimated experiments results according to the average radio channel utilization productivity with and without buffering of ...
Propagation channel characterization, parameter estimation, and modeling for wireless communications
Yin, Xuefeng
2016-01-01
Thoroughly covering channel characteristics and parameters, this book provides the knowledge needed to design various wireless systems, such as cellular communication systems, RFID and ad hoc wireless communication systems. It gives a detailed introduction to aspects of channels before presenting the novel estimation and modelling techniques which can be used to achieve accurate models. To systematically guide readers through the topic, the book is organised in three distinct parts. The first part covers the fundamentals of the characterization of propagation channels, including the conventional single-input single-output (SISO) propagation channel characterization as well as its extension to multiple-input multiple-output (MIMO) cases. Part two focuses on channel measurements and channel data post-processing. Wideband channel measurements are introduced, including the equipment, technology and advantages and disadvantages of different data acquisition schemes. The channel parameter estimation methods are ...
Degenerated-Inverse-Matrix-Based Channel Estimation for OFDM Systems
Directory of Open Access Journals (Sweden)
Makoto Yoshida
2009-01-01
Full Text Available This paper addresses time-domain channel estimation for pilot-symbol-aided orthogonal frequency division multiplexing (OFDM systems. By using a cyclic sinc-function matrix uniquely determined by Nc transmitted subcarriers, the performance of our proposed scheme approaches perfect channel state information (CSI, within a maximum of 0.4 dB degradation, regardless of the delay spread of the channel, Doppler frequency, and subcarrier modulation. Furthermore, reducing the matrix size by splitting the dispersive channel impulse response into clusters means that the degenerated inverse matrix estimator (DIME is feasible for broadband, high-quality OFDM transmission systems. In addition to theoretical analysis on normalized mean squared error (NMSE performance of DIME, computer simulations over realistic nonsample spaced channels also showed that the DIME is robust for intersymbol interference (ISI channels and fast time-invariant channels where a minimum mean squared error (MMSE estimator does not work well.
An Adaptive Channel Access Method for Dynamic Super Dense Wireless Sensor Networks.
Lei, Chunyang; Bie, Hongxia; Fang, Gengfa; Zhang, Xuekun
2015-12-03
Super dense and distributed wireless sensor networks have become very popular with the development of small cell technology, Internet of Things (IoT), Machine-to-Machine (M2M) communications, Vehicular-to-Vehicular (V2V) communications and public safety networks. While densely deployed wireless networks provide one of the most important and sustainable solutions to improve the accuracy of sensing and spectral efficiency, a new channel access scheme needs to be designed to solve the channel congestion problem introduced by the high dynamics of competing nodes accessing the channel simultaneously. In this paper, we firstly analyzed the channel contention problem using a novel normalized channel contention analysis model which provides information on how to tune the contention window according to the state of channel contention. We then proposed an adaptive channel contention window tuning algorithm in which the contention window tuning rate is set dynamically based on the estimated channel contention level. Simulation results show that our proposed adaptive channel access algorithm based on fast contention window tuning can achieve more than 95 % of the theoretical optimal throughput and 0 . 97 of fairness index especially in dynamic and dense networks.
An Adaptive Channel Access Method for Dynamic Super Dense Wireless Sensor Networks
Directory of Open Access Journals (Sweden)
Chunyang Lei
2015-12-01
Full Text Available Super dense and distributed wireless sensor networks have become very popular with the development of small cell technology, Internet of Things (IoT, Machine-to-Machine (M2M communications, Vehicular-to-Vehicular (V2V communications and public safety networks. While densely deployed wireless networks provide one of the most important and sustainable solutions to improve the accuracy of sensing and spectral efficiency, a new channel access scheme needs to be designed to solve the channel congestion problem introduced by the high dynamics of competing nodes accessing the channel simultaneously. In this paper, we firstly analyzed the channel contention problem using a novel normalized channel contention analysis model which provides information on how to tune the contention window according to the state of channel contention. We then proposed an adaptive channel contention window tuning algorithm in which the contention window tuning rate is set dynamically based on the estimated channel contention level. Simulation results show that our proposed adaptive channel access algorithm based on fast contention window tuning can achieve more than 95 % of the theoretical optimal throughput and 0 . 97 of fairness index especially in dynamic and dense networks.
Remote optimal state estimation over communication channels with random delays
Mahmoud, Magdi S.; Al-Sunni, Fouad; Liu, Bo
2014-01-01
This paper considers the optimal estimation of linear systems over unreliable communication channels with random delays. In this work, it is assumed that the system to be estimated is far away from the filter. The observations of the system
Channel allocation and rate adaptation for relayed transmission over correlated fading channels
Hwang, Kyusung
2009-09-01
We consider, in this paper, channel allocation and rate adaptation scheme for relayed transmission over correlated fading channels via cross-layer design. Specifically, jointly considering the data link layer buffer occupancy and channel quality at both the source and relay nodes, we develop an optimal channel allocation and rate adaptation policy for a dual-hop relayed transmission. As such the overall transmit power for the relayed system is minimized while a target packet dropping rate (PDR) due to buffer over flows is guaranteed. In order to find such an optimal policy, the channel allocation and rate adaptation transmission framework is formulated as a constraint Markov decision process (CMDP). The PDR performance of the optimal policy is compared with that of two conventional suboptimal schemes, namely the channel quality based and the buffer occupancy based channel allocation schemes. Numerical results show that for a given power budget, the optimal scheme requires significantly less power than the conventional schemes in order to maintain a target PDR. ©2009 IEEE.
Efficient channel estimation in massive MIMO systems - a distributed approach
Al-Naffouri, Tareq Y.
2016-01-21
We present two efficient algorithms for distributed estimation of channels in massive MIMO systems. The two cases of 1) generic, and 2) sparse channels is considered. The algorithms estimate the impulse response for each channel observed by the antennas at the receiver (base station) in a coordinated manner by sharing minimal information among neighboring antennas. Simulations demonstrate the superior performance of the proposed methods as compared to other methods.
mathematical models for estimating radio channels utilization
African Journals Online (AJOL)
2017-08-08
Aug 8, 2017 ... Mathematical models for radio channels utilization assessment by real-time flows transfer in ... data transmission networks application having dynamic topology ..... Journal of Applied Mathematics and Statistics, 56(2): 85–90.
Low-Complexity Bayesian Estimation of Cluster-Sparse Channels
Ballal, Tarig; Al-Naffouri, Tareq Y.; Ahmed, Syed
2015-01-01
This paper addresses the problem of channel impulse response estimation for cluster-sparse channels under the Bayesian estimation framework. We develop a novel low-complexity minimum mean squared error (MMSE) estimator by exploiting the sparsity of the received signal profile and the structure of the measurement matrix. It is shown that due to the banded Toeplitz/circulant structure of the measurement matrix, a channel impulse response, such as underwater acoustic channel impulse responses, can be partitioned into a number of orthogonal or approximately orthogonal clusters. The orthogonal clusters, the sparsity of the channel impulse response and the structure of the measurement matrix, all combined, result in a computationally superior realization of the MMSE channel estimator. The MMSE estimator calculations boil down to simpler in-cluster calculations that can be reused in different clusters. The reduction in computational complexity allows for a more accurate implementation of the MMSE estimator. The proposed approach is tested using synthetic Gaussian channels, as well as simulated underwater acoustic channels. Symbol-error-rate performance and computation time confirm the superiority of the proposed method compared to selected benchmark methods in systems with preamble-based training signals transmitted over clustersparse channels.
Low-Complexity Bayesian Estimation of Cluster-Sparse Channels
Ballal, Tarig
2015-09-18
This paper addresses the problem of channel impulse response estimation for cluster-sparse channels under the Bayesian estimation framework. We develop a novel low-complexity minimum mean squared error (MMSE) estimator by exploiting the sparsity of the received signal profile and the structure of the measurement matrix. It is shown that due to the banded Toeplitz/circulant structure of the measurement matrix, a channel impulse response, such as underwater acoustic channel impulse responses, can be partitioned into a number of orthogonal or approximately orthogonal clusters. The orthogonal clusters, the sparsity of the channel impulse response and the structure of the measurement matrix, all combined, result in a computationally superior realization of the MMSE channel estimator. The MMSE estimator calculations boil down to simpler in-cluster calculations that can be reused in different clusters. The reduction in computational complexity allows for a more accurate implementation of the MMSE estimator. The proposed approach is tested using synthetic Gaussian channels, as well as simulated underwater acoustic channels. Symbol-error-rate performance and computation time confirm the superiority of the proposed method compared to selected benchmark methods in systems with preamble-based training signals transmitted over clustersparse channels.
Impact of co-channel interference on the performance of adaptive generalized transmit beamforming
Radaydeh, Redha Mahmoud Mesleh
2011-08-01
The impact of co-channel interference on the performance of adaptive generalized transmit beamforming for low-complexity multiple-input single-output (MISO) configuration is investigated. The transmit channels are assumed to be sufficiently separated and undergo Rayleigh fading conditions. Due to the limited space, a single receive antenna is employed to capture desired user transmission. The number of active transmit channels is adjusted adaptively based on statistically unordered and/or ordered instantaneous signal-to-noise ratios (SNRs), where the transmitter has no information about the statistics of undesired signals. The adaptation thresholds are identified to guarantee a target performance level, and the adaptation schemes with enhanced spectral efficiency or power efficiency are studied and their performance are compared under various channels conditions. To facilitate comparison studies, results for the statistics of instantaneous combined signal-to-interference-plus-noise ratio (SINR) are derived, which can be applied for different fading conditions of interfering signals. The statistics for combined SNR and combined SINR are then used to quantify various performance measures, considering the impact of non-ideal estimation of the desired user channel state information (CSI) and the randomness in the number of active interferers. Numerical and simulation comparisons for the achieved performance of the adaptation schemes are presented. © 2006 IEEE.
Multicarrier chaotic communications in multipath fading channels without channel estimation
Energy Technology Data Exchange (ETDEWEB)
Wang, Shilian, E-mail: wangsl@nudt.edu.cn; Zhang, Zhili [College of Electrical Science and Engineering, National University of Defense Technology, Changsha, 410073, P R China (China)
2015-01-15
A multi-carrier chaotic shift keying(MC-CSK) communication scheme with low probability of interception(LPI) is proposed in this article. We apply chaotic spreading sequences in the frequency domain, mapping a different chip of a chaotic sequence to an individual orthogonal frequency division multiplexing(OFDM) subcarrier. In each block size of $M$ OFDM symbols, we use one pilot OFDM symbol inserted time-spaced in all-frequency to transmit the reference chaotic signal and use the other M-1 OFDM symbols to transmit the information-bearing signals each spreaded by the reference chaotic signal. At the receiver, we construct a differential detector after DFT and recover the information bits from the correlations between the pilot OFDM symbol and the other M-1 OFDM symbols in each block size of M. Performance analysis and computer simulations show that the MC-CSK outperforms differential chaos shift keying(DCSK) in AWGN channels with high bandwidth efficiency for the block size of M=2 and that the MC-CSK exploits effectively the frequent diversity of the multipath channel.
Multicarrier chaotic communications in multipath fading channels without channel estimation
Directory of Open Access Journals (Sweden)
Shilian Wang
2015-01-01
Full Text Available A multi-carrier chaotic shift keying(MC-CSK communication scheme with low probability of interception(LPI is proposed in this article. We apply chaotic spreading sequences in the frequency domain, mapping a different chip of a chaotic sequence to an individual orthogonal frequency division multiplexing(OFDM subcarrier. In each block size of $M$ OFDM symbols, we use one pilot OFDM symbol inserted time-spaced in all-frequency to transmit the reference chaotic signal and use the other M-1 OFDM symbols to transmit the information-bearing signals each spreaded by the reference chaotic signal. At the receiver, we construct a differential detector after DFT and recover the information bits from the correlations between the pilot OFDM symbol and the other M-1 OFDM symbols in each block size of M. Performance analysis and computer simulations show that the MC-CSK outperforms differential chaos shift keying(DCSK in AWGN channels with high bandwidth efficiency for the block size of M=2 and that the MC-CSK exploits effectively the frequent diversity of the multipath channel.
Adaptive guard channel allocation scheme with buffer for mobile ...
African Journals Online (AJOL)
The devastating effect congestion has on the quality of service delivery and overall network performance demands an utmost attention. This certainly calls for taking some expedient measures to deal with congestion so as to salvage the network from total collapse. In this paper, an adaptive guard channel allocation scheme ...
An information-guided channel-hopping scheme for block-fading channels with estimation errors
Yang, Yuli
2010-12-01
Information-guided channel-hopping technique employing multiple transmit antennas was previously proposed for supporting high data rate transmission over fading channels. This scheme achieves higher data rates than some mature schemes, such as the well-known cyclic transmit antenna selection and space-time block coding, by exploiting the independence character of multiple channels, which effectively results in having an additional information transmitting channel. Moreover, maximum likelihood decoding may be performed by simply decoupling the signals conveyed by the different mapping methods. In this paper, we investigate the achievable spectral efficiency of this scheme in the case of having channel estimation errors, with optimum pilot overhead for minimum meansquare error channel estimation, when transmitting over blockfading channels. Our numerical results further substantiate the robustness of the presented scheme, even with imperfect channel state information. ©2010 IEEE.
Adaptive Response Surface Techniques in Reliability Estimation
DEFF Research Database (Denmark)
Enevoldsen, I.; Faber, M. H.; Sørensen, John Dalsgaard
1993-01-01
Problems in connection with estimation of the reliability of a component modelled by a limit state function including noise or first order discontinuitics are considered. A gradient free adaptive response surface algorithm is developed. The algorithm applies second order polynomial surfaces...
Adaptive measurement selection for progressive damage estimation
Zhou, Wenfan; Kovvali, Narayan; Papandreou-Suppappola, Antonia; Chattopadhyay, Aditi; Peralta, Pedro
2011-04-01
Noise and interference in sensor measurements degrade the quality of data and have a negative impact on the performance of structural damage diagnosis systems. In this paper, a novel adaptive measurement screening approach is presented to automatically select the most informative measurements and use them intelligently for structural damage estimation. The method is implemented efficiently in a sequential Monte Carlo (SMC) setting using particle filtering. The noise suppression and improved damage estimation capability of the proposed method is demonstrated by an application to the problem of estimating progressive fatigue damage in an aluminum compact-tension (CT) sample using noisy PZT sensor measurements.
Detection-Guided Fast Affine Projection Channel Estimator for Speech Applications
Directory of Open Access Journals (Sweden)
Yan Wu Jennifer
2007-04-01
Full Text Available In various adaptive estimation applications, such as acoustic echo cancellation within teleconferencing systems, the input signal is a highly correlated speech. This, in general, leads to extremely slow convergence of the NLMS adaptive FIR estimator. As a result, for such applications, the affine projection algorithm (APA or the low-complexity version, the fast affine projection (FAP algorithm, is commonly employed instead of the NLMS algorithm. In such applications, the signal propagation channel may have a relatively low-dimensional impulse response structure, that is, the number m of active or significant taps within the (discrete-time modelled channel impulse response is much less than the overall tap length n of the channel impulse response. For such cases, we investigate the inclusion of an active-parameter detection-guided concept within the fast affine projection FIR channel estimator. Simulation results indicate that the proposed detection-guided fast affine projection channel estimator has improved convergence speed and has lead to better steady-state performance than the standard fast affine projection channel estimator, especially in the important case of highly correlated speech input signals.
Adaptive evolution of the vertebrate skeletal muscle sodium channel
Directory of Open Access Journals (Sweden)
Jian Lu
2011-01-01
Full Text Available Tetrodotoxin (TTX is a highly potent neurotoxin that blocks the action potential by selectively binding to voltage-gated sodium channels (Na v. The skeletal muscle Na v (Na v1.4 channels in most pufferfish species and certain North American garter snakes are resistant to TTX, whereas in most mammals they are TTX-sensitive. It still remains unclear as to whether the difference in this sensitivity among the various vertebrate species can be associated with adaptive evolution. In this study, we investigated the adaptive evolution of the vertebrate Na v1.4 channels. By means of the CODEML program of the PAML 4.3 package, the lineages of both garter snakes and pufferfishes were denoted to be under positive selection. The positively selected sites identified in the p-loop regions indicated their involvement in Na v1.4 channel sensitivity to TTX. Most of these sites were located in the intracellular regions of the Na v1.4 channel, thereby implying the possible association of these regions with the regulation of voltage-sensor movement.
Channel allocation and rate adaptation for relayed transmission over correlated fading channels
Hwang, Kyusung; Hossain, Md Jahangir; Ko, Youngchai; Alouini, Mohamed-Slim
2009-01-01
at both the source and relay nodes, we develop an optimal channel allocation and rate adaptation policy for a dual-hop relayed transmission. As such the overall transmit power for the relayed system is minimized while a target packet dropping rate (PDR
Distributive estimation of frequency selective channels for massive MIMO systems
Zaib, Alam
2015-12-28
We consider frequency selective channel estimation in the uplink of massive MIMO-OFDM systems, where our major concern is complexity. A low complexity distributed LMMSE algorithm is proposed that attains near optimal channel impulse response (CIR) estimates from noisy observations at receive antenna array. In proposed method, every antenna estimates the CIRs of its neighborhood followed by recursive sharing of estimates with immediate neighbors. At each step, every antenna calculates the weighted average of shared estimates which converges to near optimal LMMSE solution. The simulation results validate the near optimal performance of proposed algorithm in terms of mean square error (MSE). © 2015 EURASIP.
Image transmission system using adaptive joint source and channel decoding
Liu, Weiliang; Daut, David G.
2005-03-01
In this paper, an adaptive joint source and channel decoding method is designed to accelerate the convergence of the iterative log-dimain sum-product decoding procedure of LDPC codes as well as to improve the reconstructed image quality. Error resilience modes are used in the JPEG2000 source codec, which makes it possible to provide useful source decoded information to the channel decoder. After each iteration, a tentative decoding is made and the channel decoded bits are then sent to the JPEG2000 decoder. Due to the error resilience modes, some bits are known to be either correct or in error. The positions of these bits are then fed back to the channel decoder. The log-likelihood ratios (LLR) of these bits are then modified by a weighting factor for the next iteration. By observing the statistics of the decoding procedure, the weighting factor is designed as a function of the channel condition. That is, for lower channel SNR, a larger factor is assigned, and vice versa. Results show that the proposed joint decoding methods can greatly reduce the number of iterations, and thereby reduce the decoding delay considerably. At the same time, this method always outperforms the non-source controlled decoding method up to 5dB in terms of PSNR for various reconstructed images.
Sliding-MOMP Based Channel Estimation Scheme for ISDB-T Systems
Directory of Open Access Journals (Sweden)
Ziji Ma
2016-01-01
Full Text Available Compressive sensing based channel estimation has shown its advantage of accurate reconstruction for sparse signal with less pilots for OFDM systems. However, high computational cost requirement of CS method, due to linear programming, significantly restricts its implementation in practical applications. In this paper, we propose a reduced complexity channel estimation scheme of modified orthogonal matching pursuit with sliding windows for ISDB-T (Integrated Services Digital Broadcasting for Terrestrial system. The proposed scheme can reduce the computational cost by limiting the searching region as well as making effective use of the last estimation result. In addition, adaptive tracking strategy with sliding sampling window can improve the robustness of CS based methods to guarantee its accuracy of channel matrix reconstruction, even for fast time-variant channels. The computer simulation demonstrates its impact on improving bit error rate and computational complexity for ISDB-T system.
Error estimation and adaptivity for incompressible hyperelasticity
Whiteley, J.P.
2014-04-30
SUMMARY: A Galerkin FEM is developed for nonlinear, incompressible (hyper) elasticity that takes account of nonlinearities in both the strain tensor and the relationship between the strain tensor and the stress tensor. By using suitably defined linearised dual problems with appropriate boundary conditions, a posteriori error estimates are then derived for both linear functionals of the solution and linear functionals of the stress on a boundary, where Dirichlet boundary conditions are applied. A second, higher order method for calculating a linear functional of the stress on a Dirichlet boundary is also presented together with an a posteriori error estimator for this approach. An implementation for a 2D model problem with known solution, where the entries of the strain tensor exhibit large, rapid variations, demonstrates the accuracy and sharpness of the error estimators. Finally, using a selection of model problems, the a posteriori error estimate is shown to provide a basis for effective mesh adaptivity. © 2014 John Wiley & Sons, Ltd.
Raiche, Gilles; Blais, Jean-Guy
2009-01-01
In a computerized adaptive test, we would like to obtain an acceptable precision of the proficiency level estimate using an optimal number of items. Unfortunately, decreasing the number of items is accompanied by a certain degree of bias when the true proficiency level differs significantly from the a priori estimate. The authors suggest that it is possible to reduced the bias, and even the standard error of the estimate, by applying to each provisional estimation one or a combination of the following strategies: adaptive correction for bias proposed by Bock and Mislevy (1982), adaptive a priori estimate, and adaptive integration interval.
Weighted-noise threshold based channel estimation for OFDM ...
Indian Academy of Sciences (India)
Existing optimal time-domain thresholds exhibit suboptimal behavior for completely unavailable KCS ... Compared with no truncation case, truncation improved the MSE ... channel estimation errors has been studied. ...... Consumer Electron.
A Fast LMMSE Channel Estimation Method for OFDM Systems
Directory of Open Access Journals (Sweden)
Zhou Wen
2009-01-01
Full Text Available A fast linear minimum mean square error (LMMSE channel estimation method has been proposed for Orthogonal Frequency Division Multiplexing (OFDM systems. In comparison with the conventional LMMSE channel estimation, the proposed channel estimation method does not require the statistic knowledge of the channel in advance and avoids the inverse operation of a large dimension matrix by using the fast Fourier transform (FFT operation. Therefore, the computational complexity can be reduced significantly. The normalized mean square errors (NMSEs of the proposed method and the conventional LMMSE estimation have been derived. Numerical results show that the NMSE of the proposed method is very close to that of the conventional LMMSE method, which is also verified by computer simulation. In addition, computer simulation shows that the performance of the proposed method is almost the same with that of the conventional LMMSE method in terms of bit error rate (BER.
On the secrecy capacity of the MISO wiretap channel under imperfect channel estimation
Rezki, Zouheir; Alomair, Basel; Alouini, Mohamed-Slim
2014-01-01
We consider a wiretap channel consisting of a source with multiple antennas, a legitimate receiver and an eavesdropper with a single antenna each. The channels between the source and the receivers undergo fast fading. We assume that the transmitter, in addition to the statistics of both channels, is only aware of a noisy version of the CSI to the legitimate receiver referred to as main channel. The legitimate receiver is aware of both its instantaneous channel gain and the transmitter's estimate of the main channel. On the other hand, the eavesdropper's receiver, in addition to its instantaneous channel realization, is aware of the actual main CSI and the transmitter's estimate as well. While the capacity of this channel is still open even with perfect CSI at the transmitter, we provide in this paper upper and lower bounds on the secrecy capacity. The upper bound is tighter than the one corresponding to perfect main CSI and the gap between the two upper bounds is characterized in function of the channel estimation error variance, at high-SNR. Furthermore, we show that our upper and lower bounds coincide in the case of no main CSI providing a trivial secrecy capacity.
On the secrecy capacity of the MISO wiretap channel under imperfect channel estimation
Rezki, Zouheir
2014-12-01
We consider a wiretap channel consisting of a source with multiple antennas, a legitimate receiver and an eavesdropper with a single antenna each. The channels between the source and the receivers undergo fast fading. We assume that the transmitter, in addition to the statistics of both channels, is only aware of a noisy version of the CSI to the legitimate receiver referred to as main channel. The legitimate receiver is aware of both its instantaneous channel gain and the transmitter\\'s estimate of the main channel. On the other hand, the eavesdropper\\'s receiver, in addition to its instantaneous channel realization, is aware of the actual main CSI and the transmitter\\'s estimate as well. While the capacity of this channel is still open even with perfect CSI at the transmitter, we provide in this paper upper and lower bounds on the secrecy capacity. The upper bound is tighter than the one corresponding to perfect main CSI and the gap between the two upper bounds is characterized in function of the channel estimation error variance, at high-SNR. Furthermore, we show that our upper and lower bounds coincide in the case of no main CSI providing a trivial secrecy capacity.
Adaptive phase estimation with squeezed thermal light
DEFF Research Database (Denmark)
Berni, A. A.; Madsen, Lars Skovgaard; Lassen, Mikael Østergaard
2013-01-01
Summary form only given. The use of quantum states of light in optical interferometry improves the precision in the estimation of a phase shift, paving the way for applications in quantum metrology, computation and cryptography. Sub-shot noise phase sensing can for example be achieved by injecting...... investigate the performances of such protocol under the realistic assumption of thermalization of the probe state. Indeed, adaptive phase estimation schemes with squeezed states and Bayesian processing of homodyne data have been shown to be asymptotically optimal in the pure case, thus approaching the quantum...... Cramér-Rao bound. In our protocol we take advantage of the enhanced sensitivity of homodyne detection in proximity of the optimal phase which maximizes the homodyne Fisher information. A squeezed thermal probe state (signal) undergoes an unknown phase shift. The first estimation step involves...
On the ergodic secrecy capacity of the wiretap channel under imperfect main channel estimation
Rezki, Zouheir; Khisti, Ashish J.; Alouini, Mohamed-Slim
2011-01-01
imperfect main channel estimation at the transmitter. Inner and outer bounds on the ergodic secrecy capacity are derived for a class of independent identically distributed (i.i.d.) fading channels. The achievable rate is a simple on-off scheme using a
Energy-Efficient Channel Estimation in MIMO Systems
Directory of Open Access Journals (Sweden)
2006-01-01
Full Text Available The emergence of MIMO communications systems as practical high-data-rate wireless communications systems has created several technical challenges to be met. On the one hand, there is potential for enhancing system performance in terms of capacity and diversity. On the other hand, the presence of multiple transceivers at both ends has created additional cost in terms of hardware and energy consumption. For coherent detection as well as to do optimization such as water filling and beamforming, it is essential that the MIMO channel is known. However, due to the presence of multiple transceivers at both the transmitter and receiver, the channel estimation problem is more complicated and costly compared to a SISO system. Several solutions have been proposed to minimize the computational cost, and hence the energy spent in channel estimation of MIMO systems. We present a novel method of minimizing the overall energy consumption. Unlike existing methods, we consider the energy spent during the channel estimation phase which includes transmission of training symbols, storage of those symbols at the receiver, and also channel estimation at the receiver. We develop a model that is independent of the hardware or software used for channel estimation, and use a divide-and-conquer strategy to minimize the overall energy consumption.
Novel Method for 5G Systems NLOS Channels Parameter Estimation
Directory of Open Access Journals (Sweden)
Vladeta Milenkovic
2017-01-01
Full Text Available For the development of new 5G systems to operate in mm bands, there is a need for accurate radio propagation modelling at these bands. In this paper novel approach for NLOS channels parameter estimation will be presented. Estimation will be performed based on LCR performance measure, which will enable us to estimate propagation parameters in real time and to avoid weaknesses of ML and moment method estimation approaches.
Rakia, Tamer
2015-07-23
Hybrid free-space optical (FSO)/radio-frequency (RF) systems have emerged as a promising solution for high-data-rate wireless communications. In this paper, we consider power adaptation strategies based on truncated channel inversion for the hybrid FSO/RF system employing adaptive combining. Specifically, we adaptively set the RF link transmission power when FSO link quality is unacceptable to ensure constant combined signal-to-noise ratio (SNR) at the receiver. Two adaptation strategies are proposed. One strategy depends on the received RF SNR, whereas the other one depends on the combined SNR of both links. Analytical expressions for the outage probability of the hybrid system with and without power adaptation are obtained. Numerical examples show that the hybrid FSO/RF system with power adaptation achieves a considerable outage performance improvement over the conventional system.
Rakia, Tamer; Hong-Chuan Yang; Gebali, Fayez; Alouini, Mohamed-Slim
2015-01-01
Hybrid free-space optical (FSO)/radio-frequency (RF) systems have emerged as a promising solution for high-data-rate wireless communications. In this paper, we consider power adaptation strategies based on truncated channel inversion for the hybrid FSO/RF system employing adaptive combining. Specifically, we adaptively set the RF link transmission power when FSO link quality is unacceptable to ensure constant combined signal-to-noise ratio (SNR) at the receiver. Two adaptation strategies are proposed. One strategy depends on the received RF SNR, whereas the other one depends on the combined SNR of both links. Analytical expressions for the outage probability of the hybrid system with and without power adaptation are obtained. Numerical examples show that the hybrid FSO/RF system with power adaptation achieves a considerable outage performance improvement over the conventional system.
Vahidi, Vahid; Saberinia, Ebrahim; Regentova, Emma E.
2017-10-01
A channel estimation (CE) method based on compressed sensing (CS) is proposed to estimate the sparse and doubly selective (DS) channel for hyperspectral image transmission from unmanned aircraft vehicles to ground stations. The proposed method contains three steps: (1) the priori estimate of the channel by orthogonal matching pursuit (OMP), (2) calculation of the linear minimum mean square error (LMMSE) estimate of the received pilots given the estimated channel, and (3) estimate of the complex amplitudes and Doppler shifts of the channel using the enhanced received pilot data applying a second round of a CS algorithm. The proposed method is named DS-LMMSE-OMP, and its performance is evaluated by simulating transmission of AVIRIS hyperspectral data via the communication channel and assessing their fidelity for the automated analysis after demodulation. The performance of the DS-LMMSE-OMP approach is compared with that of two other state-of-the-art CE methods. The simulation results exhibit up to 8-dB figure of merit in the bit error rate and 50% improvement in the hyperspectral image classification accuracy.
Parameter Estimation Analysis for Hybrid Adaptive Fault Tolerant Control
Eshak, Peter B.
Research efforts have increased in recent years toward the development of intelligent fault tolerant control laws, which are capable of helping the pilot to safely maintain aircraft control at post failure conditions. Researchers at West Virginia University (WVU) have been actively involved in the development of fault tolerant adaptive control laws in all three major categories: direct, indirect, and hybrid. The first implemented design to provide adaptation was a direct adaptive controller, which used artificial neural networks to generate augmentation commands in order to reduce the modeling error. Indirect adaptive laws were implemented in another controller, which utilized online PID to estimate and update the controller parameter. Finally, a new controller design was introduced, which integrated both direct and indirect control laws. This controller is known as hybrid adaptive controller. This last control design outperformed the two earlier designs in terms of less NNs effort and better tracking quality. The performance of online PID has an important role in the quality of the hybrid controller; therefore, the quality of the estimation will be of a great importance. Unfortunately, PID is not perfect and the online estimation process has some inherited issues; the online PID estimates are primarily affected by delays and biases. In order to ensure updating reliable estimates to the controller, the estimator consumes some time to converge. Moreover, the estimator will often converge to a biased value. This thesis conducts a sensitivity analysis for the estimation issues, delay and bias, and their effect on the tracking quality. In addition, the performance of the hybrid controller as compared to direct adaptive controller is explored. In order to serve this purpose, a simulation environment in MATLAB/SIMULINK has been created. The simulation environment is customized to provide the user with the flexibility to add different combinations of biases and delays to
Superimposed Training-Based Channel Estimation for MIMO Relay Networks
Directory of Open Access Journals (Sweden)
Xiaoyan Xu
2012-01-01
Full Text Available We introduce the superimposed training strategy into the multiple-input multiple-output (MIMO amplify-and-forward (AF one-way relay network (OWRN to perform the individual channel estimation at the destination. Through the superposition of a group of additional training vectors at the relay subject to power allocation, the separated estimates of the source-relay and relay-destination channels can be obtained directly at the destination, and the accordance with the two-hop AF strategy can be guaranteed at the same time. The closed-form Bayesian Cramér-Rao lower bound (CRLB is derived for the estimation of two sets of flat-fading MIMO channel under random channel parameters and further exploited to design the optimal training vectors. A specific suboptimal channel estimation algorithm is applied in the MIMO AF OWRN using the optimal training sequences, and the normalized mean square error performance for the estimation is provided to verify the Bayesian CRLB results.
Channel estimation for physical layer network coding systems
Gao, Feifei; Wang, Gongpu
2014-01-01
This SpringerBrief presents channel estimation strategies for the physical later network coding (PLNC) systems. Along with a review of PLNC architectures, this brief examines new challenges brought by the special structure of bi-directional two-hop transmissions that are different from the traditional point-to-point systems and unidirectional relay systems. The authors discuss the channel estimation strategies over typical fading scenarios, including frequency flat fading, frequency selective fading and time selective fading, as well as future research directions. Chapters explore the performa
Directory of Open Access Journals (Sweden)
Biguesh Mehrzad
2004-01-01
Full Text Available In mobile communication systems with multisensor antennas at base stations, downlink channel estimation plays a key role because accurate channel estimates are needed for transmit beamforming. One efficient approach to this problem is channel probing with feedback. In this method, the base station array transmits probing (training signals. The channel is then estimated from feedback reports provided by the users. This paper studies the performance of the channel probing method with feedback using a multisensor base station antenna array and single-sensor users. The least squares (LS, linear minimum mean square error (LMMSE, and a new scaled LS (SLS approaches to the channel estimation are studied. Optimal choice of probing signals is investigated for each of these techniques and their channel estimation performances are analyzed. In the case of multiple LS channel estimates, the best linear unbiased estimation (BLUE scheme for their linear combining is developed and studied.
A Demosaicking Algorithm with Adaptive Inter-Channel Correlation
Directory of Open Access Journals (Sweden)
Joan Duran
2015-12-01
Full Text Available Most common cameras use a CCD sensor device measuring a single color per pixel. Demosaicking is the interpolation process by which one can infer a full color image from such a matrix of values, thus interpolating the two missing components per pixel. Most demosaicking methods take advantage of inter-channel correlation locally selecting the best interpolation direction. The obtained results look convincing except when local geometry cannot be inferred from neighboring pixels or channel correlation is low. In these cases, these algorithms create interpolation artifacts such as zipper effect or color aliasing. This paper discusses the implementation details of the algorithm proposed in [J. Duran, A. Buades, ``Self-Similarity and Spectral Correlation Adaptive Algorithm for Color Demosaicking'', IEEE Transactions on Image Processing, 23(9, pp. 4031--4040, 2014]. The proposed method involves nonlocal image self-similarity in order to reduce interpolation artifacts when local geometry is ambiguous. It further introduces a clear and intuitive manner of balancing how much channel-correlation must be taken advantage of.
On the secrecy capacity of the wiretap channel with imperfect main channel estimation
Rezki, Zouheir
2014-10-01
We study the secrecy capacity of fast fading channels under imperfect main channel (between the transmitter and the legitimate receiver) estimation at the transmitter. Lower and upper bounds on the ergodic secrecy capacity are derived for a class of independent identically distributed (i.i.d.) fading channels. The achievable rate follows from a standard wiretap code in which a simple on-off power control is employed along with a Gaussian input. The upper bound is obtained using an appropriate correlation scheme of the main and eavesdropper channels and is the best known upper bound so far. The upper and lower bounds coincide with recently derived ones in case of perfect main CSI. Furthermore, the upper bound is tight in case of no main CSI, where the secrecy capacity is equal to zero. Asymptotic analysis at high and low signal-to-noise ratio (SNR) is also given. At high SNR, we show that the capacity is bounded by providing upper and lower bounds that depend on the channel estimation error. At low SNR, however, we prove that the secrecy capacity is asymptotically equal to the capacity of the main channel as if there were no secrecy constraint. Numerical results are provided for i.i.d. Rayleigh fading channels.
Radaydeh, Redha Mahmoud Mesleh; Alouini, Mohamed-Slim
2010-01-01
The impact of co-channel interference and nonideal estimation of the desired user channel state information (CSI) on the performance of an adaptive threshold-based generalized transmit diversity for low-complexity multiple-input single-output configuration is investigated. The adaptation to channel conditions is assumed to be based on the desired user CSI, and the number of active transmit antennas is adjusted accordingly to guarantee predetermined target performance. To facilitate comparisons between different adaptation schemes, new analytical results for the statistics of combined signal-to-interference-plus-noise ratio (SINR) are derived, which can be applied for different fading conditions of interfering signals. Selected numerical results are presented to validate the analytical development and to compare the outage performance of the considered adaptation schemes. © 2010 IEEE.
Radaydeh, Redha Mahmoud Mesleh
2010-09-01
The impact of co-channel interference and nonideal estimation of the desired user channel state information (CSI) on the performance of an adaptive threshold-based generalized transmit diversity for low-complexity multiple-input single-output configuration is investigated. The adaptation to channel conditions is assumed to be based on the desired user CSI, and the number of active transmit antennas is adjusted accordingly to guarantee predetermined target performance. To facilitate comparisons between different adaptation schemes, new analytical results for the statistics of combined signal-to-interference-plus-noise ratio (SINR) are derived, which can be applied for different fading conditions of interfering signals. Selected numerical results are presented to validate the analytical development and to compare the outage performance of the considered adaptation schemes. © 2010 IEEE.
Multidimensional Rank Reduction Estimator for Parametric MIMO Channel Models
Directory of Open Access Journals (Sweden)
Marius Pesavento
2004-08-01
Full Text Available A novel algebraic method for the simultaneous estimation of MIMO channel parameters from channel sounder measurements is developed. We consider a parametric multipath propagation model with P discrete paths where each path is characterized by its complex path gain, its directions of arrival and departure, time delay, and Doppler shift. This problem is treated as a special case of the multidimensional harmonic retrieval problem. While the well-known ESPRIT-type algorithms exploit shift-invariance between specific partitions of the signal matrix, the rank reduction estimator (RARE algorithm exploits their internal Vandermonde structure. A multidimensional extension of the RARE algorithm is developed, analyzed, and applied to measurement data recorded with the RUSK vector channel sounder in the 2 GHz band.
On the BER and capacity analysis of MIMO MRC systems with channel estimation error
Yang, Liang
2011-10-01
In this paper, we investigate the effect of channel estimation error on the capacity and bit-error rate (BER) of a multiple-input multiple-output (MIMO) transmit maximal ratio transmission (MRT) and receive maximal ratio combining (MRC) systems over uncorrelated Rayleigh fading channels. We first derive the ergodic (average) capacity expressions for such systems when power adaptation is applied at the transmitter. The exact capacity expression for the uniform power allocation case is also presented. Furthermore, to investigate the diversity order of MIMO MRT-MRC scheme, we derive the BER performance under a uniform power allocation policy. We also present an asymptotic BER performance analysis for the MIMO MRT-MRC system with multiuser diversity. The numerical results are given to illustrate the sensitivity of the main performance to the channel estimation error and the tightness of the approximate cutoff value. © 2011 IEEE.
State estimation and synchronization of pendula systems over digital communication channels
Fradkov, A. L.; Andrievsky, B.; Ananyevskiy, M.
2014-04-01
The recent results on nonlinear systems synchronization and control under communication constraints are applied to the remote state estimation and synchronization for a class of exogenously excited nonlinear Lurie systems. State estimation of the chain of diffusively coupled pendulums over the digital communication channel with limited capacity is experimentally studied. Advantage of the adaptive coding procedure under the conditions of the plant model uncertainty and irregular disturbances is shown. Quality of the estimation is evaluated by means of the experiments with the multi-pendulum set-up. Experimental study of master-slave synchronization over network (local network, wireless network) for the system with two cart-pendulums is presented.
CFO and channel estimation for MISO-OFDM systems
Ladaycia, Abdelhamid; Abed-Meraim, Karim; Bader, Ahmed; Alouini, Mohamed-Slim
2017-01-01
-relay transmission protocols such that the geo-routing one proposed by A. Bader et al in 2012. Indeed, the outstanding performance of this multi-hop relaying scheme relies heavily on the channel and CFO estimation quality at the PHY layer. In this work, two
Estimation of adaptive of bread spring wheat varieties
Directory of Open Access Journals (Sweden)
В. А. Власенко
2006-12-01
Full Text Available For estimation of adaptive of varieties it is offered to use the aggregate of estimations of stability and plasticity in the integrated index - rating of adaptive of varieties. The high rating of adaptive on the parameters of productivity have the varieties Elegia myronivska, Kolektyvna 3, Etud and Suita.
Adaptive Estimation of Heteroscedastic Money Demand Model of Pakistan
Directory of Open Access Journals (Sweden)
Muhammad Aslam
2007-07-01
Full Text Available For the problem of estimation of Money demand model of Pakistan, money supply (M1 shows heteroscedasticity of the unknown form. For estimation of such model we compare two adaptive estimators with ordinary least squares estimator and show the attractive performance of the adaptive estimators, namely, nonparametric kernel estimator and nearest neighbour regression estimator. These comparisons are made on the basis standard errors of the estimated coefficients, standard error of regression, Akaike Information Criteria (AIC value, and the Durban-Watson statistic for autocorrelation. We further show that nearest neighbour regression estimator performs better when comparing with the other nonparametric kernel estimator.
On Channel Estimation for OFDM/TDM Using MMSE-FDE in a Fast Fading Channel
Directory of Open Access Journals (Sweden)
Gacanin Haris
2009-01-01
Full Text Available Abstract MMSE-FDE can improve the transmission performance of OFDM combined with time division multiplexing (OFDM/TDM, but knowledge of the channel state information and the noise variance is required to compute the MMSE weight. In this paper, a performance evaluation of OFDM/TDM using MMSE-FDE with pilot-assisted channel estimation over a fast fading channel is presented. To improve the tracking ability against fast fading a robust pilot-assisted channel estimation is presented that uses time-domain filtering on a slot-by-slot basis and frequency-domain interpolation. We derive the mean square error (MSE of the channel estimator and then discuss a tradeoff between improving the tracking ability against fading and the noise reduction. The achievable bit error rate (BER performance is evaluated by computer simulation and compared with conventional OFDM. It is shown that the OFDM/TDM using MMSE-FDE achieves a lower BER and a better tracking ability against fast fading in comparison with conventional OFDM.
Estimation of channel impulse response and FPGA simulation
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YU Longjie
2015-02-01
Full Text Available Wideband code division multiple access (WCDMA is a 3G wireless communication network.The common pilot channel in downlink of WCDMA provides an effective method to estimate the channel impulse response.In this paper,universal software radio peripheral (USRP is utilized to sample and process WCDMA signal which is emitted by China Unicom base station.Firstly,the received signal is pre-processed with filtering and down-sampling.Secondly,fast algorithm of WCDMA cell search is fulfilled.Thirdly,frequency shift caused by USRP′s crystal oscillator is checked and compensated.Eventually,channel impulse response is estimated.In this paper,MATLAB is used to describe the above algorithm and field programmable gate array (FPGA is used to simulate algorithm.In the process of simulation,pipeline and IP core multiplexing are introduced.In the case of 32 MHz clock frequency,FPGA simulation time is 80.861 ms.Simulation results show that FPGA is able to estimate the channel impulse response quickly and accurately with less hardware resources.
Adaptation of the Electra Radio to Support Multiple Receive Channels
Satorius, Edgar H.; Shah, Biren N.; Bruvold, Kristoffer N.; Bell, David J.
2011-01-01
Proposed future Mars missions plan communication between multiple assets (rovers). This paper presents the results of a study carried out to assess the potential adaptation of the Electra radio to a multi-channel transceiver. The basic concept is a Frequency Division multiplexing (FDM) communications scheme wherein different receiver architectures are examined. Options considered include: (1) multiple IF slices, A/D and FPGAs each programmed with an Electra baseband modem; (2) common IF but multiple A/Ds and FPGAs and (3) common IF, single A/D and single or multiple FPGAs programmed to accommodate the FDM signals. These options represent the usual tradeoff between analog and digital complexity. Given the space application, a common IF is preferable; however, multiple users present dynamic range challenges (e.g., near-far constraints) that would favor multiple IF slices (Option 1). Vice versa, with a common IF and multiple A/Ds (Option 2), individual AGC control of the A/Ds would be an important consideration. Option 3 would require a common AGC control strategy and would entail multiple digital down conversion paths within the FPGA. In this paper, both FDM parameters as well as the different Electra design options will be examined. In particular, signal channel spacing as a function of user data rates and transmit powers will be evaluated. In addition, tradeoffs between the different Electra design options will be presented with the ultimate goal of defining an augmented Electra radio architecture for potential future missions.
On the ergodic secrecy capacity of the wiretap channel under imperfect main channel estimation
Rezki, Zouheir
2011-11-01
The ergodic secrecy capacity of the wiretap channel is known when the main channel (between the transmitter and the legitimate receiver) state information (CSI) is perfect at the transmitter and the coherence period is sufficiently large to enable random coding arguments in each block. In a fast fading scenario, when the codeword length spans many coherence periods, the secrecy capacity is still not known. In this paper, we present a framework that characterizes this secrecy capacity under imperfect main channel estimation at the transmitter. Inner and outer bounds on the ergodic secrecy capacity are derived for a class of independent identically distributed (i.i.d.) fading channels. The achievable rate is a simple on-off scheme using a Gaussian input. The upper bound is obtained using an appropriate correlation scheme of the main and the eavesdropper channels. The upper and the lower bounds coincide with recently derived ones in the perfect main CSI extreme. Furthermore, the lower bound matches the upper bound in no main CSI extreme, where the secrecy capacity is equal to zero. Numerical results are provided for independent identically distributed (i.i.d.) Rayleigh fading channels. © 2011 IEEE.
Zhou, Xinyu
2016-03-15
A Gaussian multiple-input single-output (MISO) fading channel is considered. We assume that the transmitter, in addition to the statistics of all channel gains, is aware instantaneously of a noisy version of the channel to the legitimate receiver. On the other hand, the legitimate receiver is aware instantaneously of its channel to the transmitter, whereas the eavesdropper instantaneously knows all channel gains. We evaluate an achievable rate using a Gaussian input without indexing an auxiliary random variable. A sufficient condition for beamforming to be optimal is provided. When the number of transmit antennas is large, beamforming also turns out to be optimal. In this case, the maximum achievable rate can be expressed in a simple closed form and scales with the logarithm of the number of transmit antennas. Furthermore, in the case when a noisy estimate of the eavesdropper’s channel is also available at the transmitter, we introduce the SNR difference and the SNR ratio criterions and derive the related optimal transmission strategies and the corresponding achievable rates.
Zhou, Xinyu; Rezki, Zouheir; Alomair, Basel; Alouini, Mohamed-Slim
2016-01-01
A Gaussian multiple-input single-output (MISO) fading channel is considered. We assume that the transmitter, in addition to the statistics of all channel gains, is aware instantaneously of a noisy version of the channel to the legitimate receiver. On the other hand, the legitimate receiver is aware instantaneously of its channel to the transmitter, whereas the eavesdropper instantaneously knows all channel gains. We evaluate an achievable rate using a Gaussian input without indexing an auxiliary random variable. A sufficient condition for beamforming to be optimal is provided. When the number of transmit antennas is large, beamforming also turns out to be optimal. In this case, the maximum achievable rate can be expressed in a simple closed form and scales with the logarithm of the number of transmit antennas. Furthermore, in the case when a noisy estimate of the eavesdropper’s channel is also available at the transmitter, we introduce the SNR difference and the SNR ratio criterions and derive the related optimal transmission strategies and the corresponding achievable rates.
Remote optimal state estimation over communication channels with random delays
Mahmoud, Magdi S.
2014-01-22
This paper considers the optimal estimation of linear systems over unreliable communication channels with random delays. In this work, it is assumed that the system to be estimated is far away from the filter. The observations of the system are capsulized without time stamp and then transmitted to the network node at which the filter is located. The probabilities of time delays are assumed to be known. The event-driven estimation scheme is applied in this paper and the estimate of the states is updated only at each time instant when any measurement arrives. To capture the feature of communication, the system considered is augmented, and the arrived measurements are regarded as the uncertain observations of the augmented system. The corresponding optimal estimation algorithm is proposed and additionally, a numerical simulation represents the performance of this work. © 2014 The authors. Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved.
Contributions in Radio Channel Sounding, Modeling, and Estimation
DEFF Research Database (Denmark)
Pedersen, Troels
2009-01-01
This thesis spans over three strongly related topics in wireless communication: channel-sounding, -modeling, and -estimation. Three main problems are addressed: optimization of spatio-temporal apertures for channel sounding; estimation of per-path power spectral densities (psds); and modeling...... relies on a ``propagation graph'' where vertices represent scatterers and edges represent the wave propagation conditions between scatterers. The graph has a recursive structure, which permits modeling of the transfer function of the graph. We derive a closed-form expression of the infinite......-bounce impulse response. This expression is used for simulation of the impulse response of randomly generated propagation graphs. The obtained realizations exhibit the well-observed exponential power decay versus delay and specular-to-diffuse transition....
Improvement of Source Number Estimation Method for Single Channel Signal.
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Zhi Dong
Full Text Available Source number estimation methods for single channel signal have been investigated and the improvements for each method are suggested in this work. Firstly, the single channel data is converted to multi-channel form by delay process. Then, algorithms used in the array signal processing, such as Gerschgorin's disk estimation (GDE and minimum description length (MDL, are introduced to estimate the source number of the received signal. The previous results have shown that the MDL based on information theoretic criteria (ITC obtains a superior performance than GDE at low SNR. However it has no ability to handle the signals containing colored noise. On the contrary, the GDE method can eliminate the influence of colored noise. Nevertheless, its performance at low SNR is not satisfactory. In order to solve these problems and contradictions, the work makes remarkable improvements on these two methods on account of the above consideration. A diagonal loading technique is employed to ameliorate the MDL method and a jackknife technique is referenced to optimize the data covariance matrix in order to improve the performance of the GDE method. The results of simulation have illustrated that the performance of original methods have been promoted largely.
Optimal state estimation over communication channels with random delays
Mahmoud, Magdi S.; Liu, Bo
2013-01-01
This paper is concerned with the optimal estimation of linear systems over unreliable communication channels with random delays. The measurements are delivered without time stamp, and the probabilities of time delays are assumed to be known. Since the estimation is time-driven, the actual time delays are converted into virtual time delays among the formulation. The receiver of estimation node stores the sum of arrived measurements between two adjacent processing time instants and also counts the number of arrived measurements. The original linear system is modeled as an extended system with uncertain observation to capture the feature of communication, then the optimal estimation algorithm of systems with uncertain observations is proposed. Additionally, a numerical simulation is presented to show the performance of this work. © 2013 The Franklin Institute.
Optimal state estimation over communication channels with random delays
Mahmoud, Magdi S.
2013-04-01
This paper is concerned with the optimal estimation of linear systems over unreliable communication channels with random delays. The measurements are delivered without time stamp, and the probabilities of time delays are assumed to be known. Since the estimation is time-driven, the actual time delays are converted into virtual time delays among the formulation. The receiver of estimation node stores the sum of arrived measurements between two adjacent processing time instants and also counts the number of arrived measurements. The original linear system is modeled as an extended system with uncertain observation to capture the feature of communication, then the optimal estimation algorithm of systems with uncertain observations is proposed. Additionally, a numerical simulation is presented to show the performance of this work. © 2013 The Franklin Institute.
Adaptive Nonparametric Variance Estimation for a Ratio Estimator ...
African Journals Online (AJOL)
Kernel estimators for smooth curves require modifications when estimating near end points of the support, both for practical and asymptotic reasons. The construction of such boundary kernels as solutions of variational problem is a difficult exercise. For estimating the error variance of a ratio estimator, we suggest an ...
Shen, Qikun; Zhang, Tianping
2015-05-01
The paper addresses a practical issue for adaptive synchronization in master-slave large-scale systems with constant channel time-delay., and a novel adaptive synchronization control scheme is proposed to guarantee the synchronization errors asymptotically converge to the origin, in which the matching condition as in the related literatures is not necessary. The real value of channel time-delay can be estimated online by a proper adaptation mechanism, which removes the conditions that the channel time-delay should be known exactly as in existing works. Finally, simulation results demonstrate the effectiveness of the approach.
Optimal complex exponentials BEM and channel estimation in doubly selective channel
International Nuclear Information System (INIS)
Song, Lijun; Lei, Xia; Yu, Feng; Jin, Maozhu
2016-01-01
Over doubly selective channel, the optimal complex exponentials BEM (CE-BEM) is required to characterize the transmission in transform domain in order to reducing the huge number of the estimated parameters during directly estimating the impulse response in time domain. This paper proposed an improved CE-BEM to alleviating the high frequency sampling error caused by conventional CE-BEM. On the one hand, exploiting the improved CE-BEM, we achieve the sampling point is in the Doppler spread spectrum and the maximum sampling frequency is equal to the maximum Doppler shift. On the other hand we optimize the function and dimension of basis in CE-BEM respectively ,and obtain the closed solution of the EM based channel estimation differential operator by exploiting the above optimal BEM. Finally, the numerical results and theoretic analysis show that the dimension of basis is mainly depend on the maximum Doppler shift and signal-to-noise ratio (SNR), and if fixing the number of the pilot symbol, the dimension of basis is higher, the modeling error is smaller, while the accuracy of the parameter estimation is reduced, which implies that we need to achieve a tradeoff between the modeling error and the accuracy of the parameter estimation and the basis function influences the accuracy of describing the Doppler spread spectrum after identifying the dimension of the basis.
Novel coherent receivers for AF distributed STBC using disintegrated channel estimation
Khan, Fahd Ahmed; Chen, Yunfei; Alouini, Mohamed-Slim
2011-01-01
For a single relay network, disintegrated channel estimation (DCE), where the source-relay channel is estimated at the relay and the relay-destination channel is estimated at the destination, gives better performance than the cascaded channel estimation. We derive novel receivers for the relay network with disintegrated channel estimation. The derived receivers do not require channel estimation at the destination, as they use the received pilot signals and the source-relay channel estimate for decoding directly. We also consider the effect of quantized source-relay channel estimate on the performance of the designed receivers. Simulation results show that a performance gain of up to 2.2 dB can be achieved by the new receivers, compared with the conventional mismatched coherent receiver with DCE. © 2011 IEEE.
Novel coherent receivers for AF distributed STBC using disintegrated channel estimation
Khan, Fahd Ahmed
2011-05-01
For a single relay network, disintegrated channel estimation (DCE), where the source-relay channel is estimated at the relay and the relay-destination channel is estimated at the destination, gives better performance than the cascaded channel estimation. We derive novel receivers for the relay network with disintegrated channel estimation. The derived receivers do not require channel estimation at the destination, as they use the received pilot signals and the source-relay channel estimate for decoding directly. We also consider the effect of quantized source-relay channel estimate on the performance of the designed receivers. Simulation results show that a performance gain of up to 2.2 dB can be achieved by the new receivers, compared with the conventional mismatched coherent receiver with DCE. © 2011 IEEE.
An Efficient Code-Timing Estimator for DS-CDMA Systems over Resolvable Multipath Channels
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Jian Li
2005-04-01
Full Text Available We consider the problem of training-based code-timing estimation for the asynchronous direct-sequence code-division multiple-access (DS-CDMA system. We propose a modified large-sample maximum-likelihood (MLSML estimator that can be used for the code-timing estimation for the DS-CDMA systems over the resolvable multipath channels in closed form. Simulation results show that MLSML can be used to provide a high correct acquisition probability and a high estimation accuracy. Simulation results also show that MLSML can have very good near-far resistant capability due to employing a data model similar to that for adaptive array processing where strong interferences can be suppressed.
High-dimensional quantum channel estimation using classical light
CSIR Research Space (South Africa)
Mabena, Chemist M
2017-11-01
Full Text Available stream_source_info Mabena_20007_2017.pdf.txt stream_content_type text/plain stream_size 960 Content-Encoding UTF-8 stream_name Mabena_20007_2017.pdf.txt Content-Type text/plain; charset=UTF-8 PHYSICAL REVIEW A 96, 053860... (2017) High-dimensional quantum channel estimation using classical light Chemist M. Mabena CSIR National Laser Centre, P.O. Box 395, Pretoria 0001, South Africa and School of Physics, University of the Witwatersrand, Johannesburg 2000, South...
A Novel OFDM Channel Estimation Algorithm with ICI Mitigation over Fast Fading Channels
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C. Tao
2010-06-01
Full Text Available Orthogonal frequency-division multiplexing (OFDM is well-known as a high-bit-rate transmission technique, but the Doppler frequency offset due to the high speed movement destroys the orthogonality of the subcarriers resulting in the intercarrier interference (ICI, and degrades the performance of the system at the same time. In this paper a novel OFDM channel estimation algorithm with ICI mitigation based on the ICI self-cancellation scheme is proposed. With this method, a more accurate channel estimation is obtained by comb-type double pilots and then ICI coefficients can be obtained to mitigate the ICI on each subcarrier under the assumption that the channel impulse response (CIR varies in a linear fashion. The theoretical analysis and simulation results show that the bit error rate (BER and spectral efficiency performances are improved significantly under high-speed mobility conditions (350 km/h – 500 km/h in comparison to ZHAO’s ICI self-cancellation scheme.
Efficiently adapting graphical models for selectivity estimation
DEFF Research Database (Denmark)
Tzoumas, Kostas; Deshpande, Amol; Jensen, Christian S.
2013-01-01
cardinality estimation without making the independence assumption. By carefully using concepts from the field of graphical models, we are able to factor the joint probability distribution over all the attributes in the database into small, usually two-dimensional distributions, without a significant loss...... in estimation accuracy. We show how to efficiently construct such a graphical model from the database using only two-way join queries, and we show how to perform selectivity estimation in a highly efficient manner. We integrate our algorithms into the PostgreSQL DBMS. Experimental results indicate...
Directory of Open Access Journals (Sweden)
Schoeneich Hendrik
2006-01-01
Full Text Available Channel estimation schemes suitable for interleave-division multiple access (IDMA systems are presented. Training and data are superimposed. Training-based and semiblind linear channel estimators are derived and their performance is discussed and compared. Monte Carlo simulation results are presented showing that the derived channel estimators in conjunction with a superimposed pilot sequence and chip-by-chip processing are able to track fast-fading frequency-selective channels. As opposed to conventional channel estimation techniques, the BER performance even improves with increasing Doppler spread for typical system parameters. An error performance close to the case of perfect channel knowledge can be achieved with high power efficiency.
Optimal Smoothing in Adaptive Location Estimation
Mammen, Enno; Park, Byeong U.
1997-01-01
In this paper higher order performance of kernel basedadaptive location estimators are considered. Optimalchoice of smoothing parameters is discussed and it isshown how much is lossed in efficiency by not knowingthe underlying translation density.
Directory of Open Access Journals (Sweden)
David L. Ndzi
2011-01-01
Full Text Available This paper describes the development of a fast adaptable FPGA-based wideband channel sounder with signal bandwidths of up to 200 MHz and channel sampling rates up to 5.4 kHz. The application of FPGA allows the user to vary the number of real-time channel response averages, channel sampling interval, and duration of measurement. The waveform, bandwidth, and frequency resolution of the sounder can be adapted for any channel under investigation. The design approach and technology used has led to a reduction in size and weight by more than 60%. This makes the sounder ideal for mobile time-variant wireless communication channels studies. Averaging allows processing gains of up to 30 dB to be achieved for measurement in weak signal conditions. The technique applied also improves reliability, reduces power consumption, and has shifted sounder design complexity from hardware to software. Test results show that the sounder can detect very small-scale variations in channels.
Petit, Cyril; Védrenne, Nicolas; Velluet, Marie Therese; Michau, Vincent; Artaud, Geraldine; Samain, Etienne; Toyoshima, Morio
2016-11-01
In order to address the high throughput requested for both downlink and uplink satellite to ground laser links, adaptive optics (AO) has become a key technology. While maturing, application of this technology for satellite to ground telecommunication, however, faces difficulties, such as higher bandwidth and optimal operation for a wide variety of atmospheric conditions (daytime and nighttime) with potentially low elevations that might severely affect wavefront sensing because of scintillation. To address these specificities, an accurate understanding of the origin of the perturbations is required, as well as operational validation of AO on real laser links. We report here on a low Earth orbiting (LEO) microsatellite to ground downlink with AO correction. We discuss propagation channel characterization based on Shack-Hartmann wavefront sensor (WFS) measurements. Fine modeling of the propagation channel is proposed based on multi-Gaussian model of turbulence profile. This model is then used to estimate the AO performance and validate the experimental results. While AO performance is limited by the experimental set-up, it proves to comply with expected performance and further interesting information on propagation channel is extracted. These results shall help dimensioning and operating AO systems for LEO to ground downlinks.
Adaptive estimation of binomial probabilities under misclassification
Albers, Willem/Wim; Veldman, H.J.
1984-01-01
If misclassification occurs the standard binomial estimator is usually seriously biased. It is known that an improvement can be achieved by using more than one observer in classifying the sample elements. Here it will be investigated which number of observers is optimal given the total number of
Schoeneich Hendrik; Hoeher Peter Adam
2006-01-01
Channel estimation schemes suitable for interleave-division multiple access (IDMA) systems are presented. Training and data are superimposed. Training-based and semiblind linear channel estimators are derived and their performance is discussed and compared. Monte Carlo simulation results are presented showing that the derived channel estimators in conjunction with a superimposed pilot sequence and chip-by-chip processing are able to track fast-fading frequency-selective channels. As opposed ...
H∞ Channel Estimation for DS-CDMA Systems: A Partial Difference Equation Approach
Directory of Open Access Journals (Sweden)
Wei Wang
2013-01-01
Full Text Available In the communications literature, a number of different algorithms have been proposed for channel estimation problems with the statistics of the channel noise and observation noise exactly known. In practical systems, however, the channel parameters are often estimated using training sequences which lead to the statistics of the channel noise difficult to obtain. Moreover, the received signals are corrupted not only by the ambient noises but also by multiple-access interferences, so the statistics of observation noises is also difficult to obtain. In this paper, we will investigate the H∞ channel estimation problem for direct-sequence code-division multiple-access (DS-CDMA communication systems with time-varying multipath fading channels. The channel estimator is designed by applying a partial difference equation approach together with the innovation analysis theory. This method can give a sufficient and necessary condition for the existence of an H∞ channel estimator.
Directory of Open Access Journals (Sweden)
Xia Liu
2010-01-01
Full Text Available This paper reports investigations on the effect of antenna mutual coupling on performance of training-based Multiple-Input Multiple-Output (MIMO channel estimation. The influence of mutual coupling is assessed for two training-based channel estimation methods, Scaled Least Square (SLS and Minimum Mean Square Error (MMSE. It is shown that the accuracy of MIMO channel estimation is governed by the sum of eigenvalues of channel correlation matrix which in turn is influenced by the mutual coupling in transmitting and receiving array antennas. A water-filling-based procedure is proposed to optimize the training signal transmission to minimize the MIMO channel estimation errors.
Adaptive Unscented Kalman Filter using Maximum Likelihood Estimation
DEFF Research Database (Denmark)
Mahmoudi, Zeinab; Poulsen, Niels Kjølstad; Madsen, Henrik
2017-01-01
The purpose of this study is to develop an adaptive unscented Kalman filter (UKF) by tuning the measurement noise covariance. We use the maximum likelihood estimation (MLE) and the covariance matching (CM) method to estimate the noise covariance. The multi-step prediction errors generated...
Adaptive Window Zero-Crossing-Based Instantaneous Frequency Estimation
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Sekhar S Chandra
2004-01-01
Full Text Available We address the problem of estimating instantaneous frequency (IF of a real-valued constant amplitude time-varying sinusoid. Estimation of polynomial IF is formulated using the zero-crossings of the signal. We propose an algorithm to estimate nonpolynomial IF by local approximation using a low-order polynomial, over a short segment of the signal. This involves the choice of window length to minimize the mean square error (MSE. The optimal window length found by directly minimizing the MSE is a function of the higher-order derivatives of the IF which are not available a priori. However, an optimum solution is formulated using an adaptive window technique based on the concept of intersection of confidence intervals. The adaptive algorithm enables minimum MSE-IF (MMSE-IF estimation without requiring a priori information about the IF. Simulation results show that the adaptive window zero-crossing-based IF estimation method is superior to fixed window methods and is also better than adaptive spectrogram and adaptive Wigner-Ville distribution (WVD-based IF estimators for different signal-to-noise ratio (SNR.
One-Channel Surface Electromyography Decomposition for Muscle Force Estimation
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Wentao Sun
2018-05-01
Full Text Available Estimating muscle force by surface electromyography (sEMG is a non-invasive and flexible way to diagnose biomechanical diseases and control assistive devices such as prosthetic hands. To estimate muscle force using sEMG, a supervised method is commonly adopted. This requires simultaneous recording of sEMG signals and muscle force measured by additional devices to tune the variables involved. However, recording the muscle force of the lost limb of an amputee is challenging, and the supervised method has limitations in this regard. Although the unsupervised method does not require muscle force recording, it suffers from low accuracy due to a lack of reference data. To achieve accurate and easy estimation of muscle force by the unsupervised method, we propose a decomposition of one-channel sEMG signals into constituent motor unit action potentials (MUAPs in two steps: (1 learning an orthogonal basis of sEMG signals through reconstruction independent component analysis; (2 extracting spike-like MUAPs from the basis vectors. Nine healthy subjects were recruited to evaluate the accuracy of the proposed approach in estimating muscle force of the biceps brachii. The results demonstrated that the proposed approach based on decomposed MUAPs explains more than 80% of the muscle force variability recorded at an arbitrary force level, while the conventional amplitude-based approach explains only 62.3% of this variability. With the proposed approach, we were also able to achieve grip force control of a prosthetic hand, which is one of the most important clinical applications of the unsupervised method. Experiments on two trans-radial amputees indicated that the proposed approach improves the performance of the prosthetic hand in grasping everyday objects.
Content Adaptive True Motion Estimator for H.264 Video Compression
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P. Kulla
2007-12-01
Full Text Available Content adaptive true motion estimator for H.264 video coding is a fast block-based matching estimator with implemented multi-stage approach to estimate motion fields between two image frames. It considers the theory of 3D scene objects projection into 2D image plane for selection of motion vector candidates from the higher stages. The stages of the algorithm and its hierarchy are defined upon motion estimation reliability measurement (image blocks including two different directions of spatial gradient, blocks with one dominant spatial gradient and blocks including minimal spatial gradient. Parameters of the image classification into stages are set adaptively upon image structure. Due to search strategy are the estimated motion fields more corresponding to a true motion in an image sequence as in the case of conventional motion estimation algorithms that use fixed sets of motion vector candidates from tight neighborhood.
Directory of Open Access Journals (Sweden)
Scinob Kuroki
Full Text Available An Asian spice, Szechuan pepper (sanshool, is well known for the tingling sensation it induces on the mouth and on the lips. Electrophysiological studies have revealed that its active ingredient can induce firing of mechanoreceptor fibres that typically respond to mechanical vibration. Moreover, a human behavioral study has reported that the perceived frequency of sanshool-induced tingling matches with the preferred frequency range of the tactile rapidly adapting (RA channel, suggesting the contribution of sanshool-induced RA channel firing to its unique perceptual experience. However, since the RA channel may not be the only channel activated by sanshool, there could be a possibility that the sanshool tingling percept may be caused in whole or in part by other sensory channels. Here, by using a perceptual interference paradigm, we show that the sanshool-induced RA input indeed contributes to the human tactile processing. The absolute detection thresholds for vibrotactile input were measured with and without sanshool application on the fingertip. Sanshool significantly impaired detection of vibrations at 30 Hz (RA channel dominant frequency, but did not impair detection of higher frequency vibrations at 240 Hz (Pacinian-corpuscle (PC channel dominant frequency or lower frequency vibrations at 1 Hz (slowly adapting 1 (SA1 channel dominant frequency. These results show that the sanshool induces a peripheral RA channel activation that is relevant for tactile perception. This anomalous activation of RA channels may contribute to the unique tingling experience of sanshool.
Multiple Estimation Architecture in Discrete-Time Adaptive Mixing Control
Directory of Open Access Journals (Sweden)
Simone Baldi
2013-05-01
Full Text Available Adaptive mixing control (AMC is a recently developed control scheme for uncertain plants, where the control action coming from a bank of precomputed controller is mixed based on the parameter estimates generated by an on-line parameter estimator. Even if the stability of the control scheme, also in the presence of modeling errors and disturbances, has been shown analytically, its transient performance might be sensitive to the initial conditions of the parameter estimator. In particular, for some initial conditions, transient oscillations may not be acceptable in practical applications. In order to account for such a possible phenomenon and to improve the learning capability of the adaptive scheme, in this paper a new mixing architecture is developed, involving the use of parallel parameter estimators, or multi-estimators, each one working on a small subset of the uncertainty set. A supervisory logic, using performance signals based on the past and present estimation error, selects the parameter estimate to determine the mixing of the controllers. The stability and robustness properties of the resulting approach, referred to as multi-estimator adaptive mixing control (Multi-AMC, are analytically established. Besides, extensive simulations demonstrate that the scheme improves the transient performance of the original AMC with a single estimator. The control scheme and the analysis are carried out in a discrete-time framework, for easier implementation of the method in digital control.
Adaptive Modulation for a Downlink Multicast Channel in OFDMA Systems
DEFF Research Database (Denmark)
Wang, Haibo; Schwefel, Hans-Peter; Toftegaard, Thomas Skjødeberg
2007-01-01
In this paper we focus on adaptive modulation strategies for multicast service in orthogonal frequency division multiple access systems. A reward function has been defined as the optimization target, which includes both the average user throughput and bit error rate. We also developed an adaptive...... modulation strategy, namely local best reward strategy, to maximize this reward function. The performance of different modulation strategies are compared in different SNR distribution scenarios, and the optimum strategy in each scenario is suggested....
Demonstrating Heisenberg-limited unambiguous phase estimation without adaptive measurements
International Nuclear Information System (INIS)
Higgins, B L; Wiseman, H M; Pryde, G J; Berry, D W; Bartlett, S D; Mitchell, M W
2009-01-01
We derive, and experimentally demonstrate, an interferometric scheme for unambiguous phase estimation with precision scaling at the Heisenberg limit that does not require adaptive measurements. That is, with no prior knowledge of the phase, we can obtain an estimate of the phase with a standard deviation that is only a small constant factor larger than the minimum physically allowed value. Our scheme resolves the phase ambiguity that exists when multiple passes through a phase shift, or NOON states, are used to obtain improved phase resolution. Like a recently introduced adaptive technique (Higgins et al 2007 Nature 450 393), our experiment uses multiple applications of the phase shift on single photons. By not requiring adaptive measurements, but rather using a predetermined measurement sequence, the present scheme is both conceptually simpler and significantly easier to implement. Additionally, we demonstrate a simplified adaptive scheme that also surpasses the standard quantum limit for single passes.
Chen, Yunfei; Alouini, Mohamed-Slim; Tang, Liang; Khan, Fahdahmed
2012-01-01
The performance of adaptive modulation for cognitive radio with opportunistic access is analyzed by considering the effects of spectrum sensing, primary user (PU) traffic, and time delay for Nakagami- m fading channels. Both the adaptive continuous rate scheme and the adaptive discrete rate scheme are considered. Numerical examples are presented to quantify the effects of spectrum sensing, PU traffic, and time delay for different system parameters. © 1967-2012 IEEE.
Chen, Yunfei
2012-09-01
The performance of adaptive modulation for cognitive radio with opportunistic access is analyzed by considering the effects of spectrum sensing, primary user (PU) traffic, and time delay for Nakagami- m fading channels. Both the adaptive continuous rate scheme and the adaptive discrete rate scheme are considered. Numerical examples are presented to quantify the effects of spectrum sensing, PU traffic, and time delay for different system parameters. © 1967-2012 IEEE.
Adaptive rate transmission for spectrum sharing system with quantized channel state information
Abdallah, Mohamed M.
2011-03-01
The capacity of a secondary link in spectrum sharing systems has been recently investigated in fading environments. In particular, the secondary transmitter is allowed to adapt its power and rate to maximize its capacity subject to the constraint of maximum interference level allowed at the primary receiver. In most of the literature, it was assumed that estimates of the channel state information (CSI) of the secondary link and the interference level are made available at the secondary transmitter via an infinite-resolution feedback links between the secondary/primary receivers and the secondary transmitter. However, the assumption of having infinite resolution feedback links is not always practical as it requires an excessive amount of bandwidth. In this paper we develop a framework for optimizing the performance of the secondary link in terms of the average spectral efficiency assuming quantized CSI available at the secondary transmitter. We develop a computationally efficient algorithm for optimally quantizing the CSI and finding the optimal power and rate employed at the cognitive transmitter for each quantized CSI level so as to maximize the average spectral efficiency. Our results give the number of bits required to represent the CSI sufficient to achieve almost the maximum average spectral efficiency attained using full knowledge of the CSI for Rayleigh fading channels. © 2011 IEEE.
Adaptive rate transmission for spectrum sharing system with quantized channel state information
Abdallah, Mohamed M.; Salem, Ahmed H.; Alouini, Mohamed-Slim; Qaraqe, Khalid A.
2011-01-01
The capacity of a secondary link in spectrum sharing systems has been recently investigated in fading environments. In particular, the secondary transmitter is allowed to adapt its power and rate to maximize its capacity subject to the constraint of maximum interference level allowed at the primary receiver. In most of the literature, it was assumed that estimates of the channel state information (CSI) of the secondary link and the interference level are made available at the secondary transmitter via an infinite-resolution feedback links between the secondary/primary receivers and the secondary transmitter. However, the assumption of having infinite resolution feedback links is not always practical as it requires an excessive amount of bandwidth. In this paper we develop a framework for optimizing the performance of the secondary link in terms of the average spectral efficiency assuming quantized CSI available at the secondary transmitter. We develop a computationally efficient algorithm for optimally quantizing the CSI and finding the optimal power and rate employed at the cognitive transmitter for each quantized CSI level so as to maximize the average spectral efficiency. Our results give the number of bits required to represent the CSI sufficient to achieve almost the maximum average spectral efficiency attained using full knowledge of the CSI for Rayleigh fading channels. © 2011 IEEE.
Adaptive Methods for Permeability Estimation and Smart Well Management
Energy Technology Data Exchange (ETDEWEB)
Lien, Martha Oekland
2005-04-01
The main focus of this thesis is on adaptive regularization methods. We consider two different applications, the inverse problem of absolute permeability estimation and the optimal control problem of estimating smart well management. Reliable estimates of absolute permeability are crucial in order to develop a mathematical description of an oil reservoir. Due to the nature of most oil reservoirs, mainly indirect measurements are available. In this work, dynamic production data from wells are considered. More specifically, we have investigated into the resolution power of pressure data for permeability estimation. The inversion of production data into permeability estimates constitutes a severely ill-posed problem. Hence, regularization techniques are required. In this work, deterministic regularization based on adaptive zonation is considered, i.e. a solution approach with adaptive multiscale estimation in conjunction with level set estimation is developed for coarse scale permeability estimation. A good mathematical reservoir model is a valuable tool for future production planning. Recent developments within well technology have given us smart wells, which yield increased flexibility in the reservoir management. In this work, we investigate into the problem of finding the optimal smart well management by means of hierarchical regularization techniques based on multiscale parameterization and refinement indicators. The thesis is divided into two main parts, where Part I gives a theoretical background for a collection of research papers that has been written by the candidate in collaboration with others. These constitutes the most important part of the thesis, and are presented in Part II. A brief outline of the thesis follows below. Numerical aspects concerning calculations of derivatives will also be discussed. Based on the introduction to regularization given in Chapter 2, methods for multiscale zonation, i.e. adaptive multiscale estimation and refinement
Xu, Li; Shan, Lin; Adachi, Fumiyuki
2014-01-01
In orthogonal frequency division modulation (OFDM) communication systems, channel state information (CSI) is required at receiver due to the fact that frequency-selective fading channel leads to disgusting intersymbol interference (ISI) over data transmission. Broadband channel model is often described by very few dominant channel taps and they can be probed by compressive sensing based sparse channel estimation (SCE) methods, for example, orthogonal matching pursuit algorithm, which can take the advantage of sparse structure effectively in the channel as for prior information. However, these developed methods are vulnerable to both noise interference and column coherence of training signal matrix. In other words, the primary objective of these conventional methods is to catch the dominant channel taps without a report of posterior channel uncertainty. To improve the estimation performance, we proposed a compressive sensing based Bayesian sparse channel estimation (BSCE) method which cannot only exploit the channel sparsity but also mitigate the unexpected channel uncertainty without scarifying any computational complexity. The proposed method can reveal potential ambiguity among multiple channel estimators that are ambiguous due to observation noise or correlation interference among columns in the training matrix. Computer simulations show that proposed method can improve the estimation performance when comparing with conventional SCE methods. PMID:24983012
Adaptive distributed parameter and input estimation in linear parabolic PDEs
Mechhoud, Sarra
2016-01-01
First, new sufficient identifiability conditions of the input and the parameter simultaneous estimation are stated. Then, by means of Lyapunov-based design, an adaptive estimator is derived in the infinite-dimensional framework. It consists of a state observer and gradient-based parameter and input adaptation laws. The parameter convergence depends on the plant signal richness assumption, whereas the state convergence is established using a Lyapunov approach. The results of the paper are illustrated by simulation on tokamak plasma heat transport model using simulated data.
International Nuclear Information System (INIS)
Ng, Angela; Nguyen, Thao-Nguyen; Moseley, Joanne L; Hodgson, David C; Sharpe, Michael B; Brock, Kristy K
2012-01-01
Biologically-based models that utilize 3D radiation dosimetry data to estimate the risk of late cardiac effects could have significant utility for planning radiotherapy in young patients. A major challenge arises from having only 2D treatment planning data for patients with long-term follow-up. In this study, we evaluate the accuracy of an advanced deformable image registration (DIR) and navigator channels (NC) adaptation technique to reconstruct 3D heart volumes from 2D radiotherapy planning images for Hodgkin's Lymphoma (HL) patients. Planning CT images were obtained for 50 HL patients who underwent mediastinal radiotherapy. Twelve image sets (6 male, 6 female) were used to construct a male and a female population heart model, which was registered to 23 HL 'Reference' patients' CT images using a DIR algorithm, MORFEUS. This generated a series of population-to-Reference patient specific 3D deformation maps. The technique was independently tested on 15 additional 'Test' patients by reconstructing their 3D heart volumes using 2D digitally reconstructed radiographs (DRR). The technique involved: 1) identifying a matching Reference patient for each Test patient using thorax measurements, 2) placement of six NCs on matching Reference and Test patients' DRRs to capture differences in significant heart curvatures, 3) adapting the population-to-Reference patient-specific deformation maps to generate population-to-Test patient-specific deformation maps using linear and bilinear interpolation methods, 4) applying population-to-Test patient specific deformation to the population model to reconstruct Test-patient specific 3D heart models. The percentage volume overlap between the NC-adapted reconstruction and actual Test patient's true heart volume was calculated using the Dice coefficient. The average Dice coefficient expressed as a percentage between the NC-adapted and actual Test model was 89.4 ± 2.8%. The modified NC adaptation
Single-Channel Blind Estimation of Reverberation Parameters
DEFF Research Database (Denmark)
Doire, C.S.J.; Brookes, M. D.; Naylor, P. A.
2015-01-01
The reverberation of an acoustic channel can be characterised by two frequency-dependent parameters: the reverberation time and the direct-to-reverberant energy ratio. This paper presents an algorithm for blindly determining these parameters from a single-channel speech signal. The algorithm uses...
On Using Exponential Parameter Estimators with an Adaptive Controller
Patre, Parag; Joshi, Suresh M.
2011-01-01
Typical adaptive controllers are restricted to using a specific update law to generate parameter estimates. This paper investigates the possibility of using any exponential parameter estimator with an adaptive controller such that the system tracks a desired trajectory. The goal is to provide flexibility in choosing any update law suitable for a given application. The development relies on a previously developed concept of controller/update law modularity in the adaptive control literature, and the use of a converse Lyapunov-like theorem. Stability analysis is presented to derive gain conditions under which this is possible, and inferences are made about the tracking error performance. The development is based on a class of Euler-Lagrange systems that are used to model various engineering systems including space robots and manipulators.
Iterative Sparse Channel Estimation and Decoding for Underwater MIMO-OFDM
Directory of Open Access Journals (Sweden)
Berger ChristianR
2010-01-01
Full Text Available We propose a block-by-block iterative receiver for underwater MIMO-OFDM that couples channel estimation with multiple-input multiple-output (MIMO detection and low-density parity-check (LDPC channel decoding. In particular, the channel estimator is based on a compressive sensing technique to exploit the channel sparsity, the MIMO detector consists of a hybrid use of successive interference cancellation and soft minimum mean-square error (MMSE equalization, and channel coding uses nonbinary LDPC codes. Various feedback strategies from the channel decoder to the channel estimator are studied, including full feedback of hard or soft symbol decisions, as well as their threshold-controlled versions. We study the receiver performance using numerical simulation and experimental data collected from the RACE08 and SPACE08 experiments. We find that iterative receiver processing including sparse channel estimation leads to impressive performance gains. These gains are more pronounced when the number of available pilots to estimate the channel is decreased, for example, when a fixed number of pilots is split between an increasing number of parallel data streams in MIMO transmission. For the various feedback strategies for iterative channel estimation, we observe that soft decision feedback slightly outperforms hard decision feedback.
Directory of Open Access Journals (Sweden)
Meher Krishna Patel
2017-01-01
Full Text Available This paper presents an adaptive multiuser transceiver scheme for DS-CDMA systems in which pilot symbols are added to users’ data to estimate complex channel fading coefficients. The performance of receiver antenna diversity with maximal ratio combining (MRC technique is analyzed for imperfect channel estimation in flat fading environments. The complex fading coefficients are estimated using least mean square (LMS algorithm and these coefficients are utilized by the maximal ratio combiner for generating the decision variable. Probability of error in closed form is derived. Further, the effect of pilot signal power on bit error rate (BER and BER performance of multiplexed pilot and data signal transmission scenario are investigated. We have compared the performance of added and multiplexed pilot-data systems and concluded the advantages of both systems. The proposed CDMA technique uses the chaotic sequence as spreading sequence. Assuming proper synchronization, the computer simulation results demonstrate the better bit error rate performance in the presence of channel estimator in the chaotic based CDMA system and the receiver antenna diversity technique further improves the performance of the proposed system. Also, no channel estimator is required if there is no phase distortion to the transmitted signal.
About an adaptively weighted Kaplan-Meier estimate.
Plante, Jean-François
2009-09-01
The minimum averaged mean squared error nonparametric adaptive weights use data from m possibly different populations to infer about one population of interest. The definition of these weights is based on the properties of the empirical distribution function. We use the Kaplan-Meier estimate to let the weights accommodate right-censored data and use them to define the weighted Kaplan-Meier estimate. The proposed estimate is smoother than the usual Kaplan-Meier estimate and converges uniformly in probability to the target distribution. Simulations show that the performances of the weighted Kaplan-Meier estimate on finite samples exceed that of the usual Kaplan-Meier estimate. A case study is also presented.
Delayed rectifier K channels contribute to contrast adaptation in mammalian retinal ganglion cells
Weick, Michael; Demb, Jonathan B.
2011-01-01
SUMMARY Retinal ganglion cells adapt by reducing their sensitivity during periods of high contrast. Contrast adaptation in the firing response depends on both presynaptic and intrinsic mechanisms. Here, we investigated intrinsic mechanisms for contrast adaptation in OFF Alpha ganglion cells in the in vitro guinea pig retina. Using either visual stimulation or current injection, we show that brief depolarization evoked spiking and suppressed firing during subsequent depolarization. The suppression could be explained by Na channel inactivation, as shown in salamander cells. However, brief hyperpolarization in the physiological range (5–10 mV) also suppressed firing during subsequent depolarization. This suppression was sensitive selectively to blockers of delayed-rectifier K channels (KDR). Somatic membrane patches showed TEA-sensitive KDR currents with activation near −25 mV and removal of inactivation at voltages negative to Vrest. Brief periods of hyperpolarization apparently remove KDR inactivation and thereby increase the channel pool available to suppress excitability during subsequent depolarization. PMID:21745646
Channel Estimation for Filter Bank Multicarrier Systems in Low SNR Environments
Energy Technology Data Exchange (ETDEWEB)
Driggs, Jonathan; Sibbett, Taylor; Moradiy, Hussein; Farhang-Boroujeny, Behrouz
2017-05-01
Channel estimation techniques are crucial for reliable communications. This paper is concerned with channel estimation in a filter bank multicarrier spread spectrum (FBMCSS) system. We explore two channel estimator options: (i) a method that makes use of a periodic preamble and mimics the channel estimation techniques that are widely used in OFDM-based systems; and (ii) a method that stays within the traditional realm of filter bank signal processing. For the case where the channel noise is white, both methods are analyzed in detail and their performance is compared against their respective Cramer-Rao Lower Bounds (CRLB). Advantages and disadvantages of the two methods under different channel conditions are given to provide insight to the reader as to when one will outperform the other.
Effective Scheme of Channel Tracking and Estimation for Mobile WiMAX DL-PUSC System
Directory of Open Access Journals (Sweden)
Phuong Thi Thu Pham
2010-01-01
Full Text Available This paper introduces an effective joint scheme of channel estimation and tracking for downlink partial usage of subchannel (DL-PUSC mode of mobile WiMAX system. Based on the pilot pattern of this particular system, some channel estimation methods including conventional interpolations and a more favorable least-squares line fitting (LSLF technique are comparatively studied. Besides, channel estimation performance can be remarkably improved by taking advantage of channel tracking derived from the preamble symbol. System performances in terms of packet error rate (PER and user link throughput are investigated in various channels adopted from the well-known ITU models for mobile environments. Simulation results show a significant performance enhancement when the proposed joint scheme is utilized, at least 5 dB, compared to only commonly used channel estimation approaches.
The generation of shared cryptographic keys through channel impulse response estimation at 60 GHz.
Energy Technology Data Exchange (ETDEWEB)
Young, Derek P.; Forman, Michael A.; Dowdle, Donald Ryan
2010-09-01
Methods to generate private keys based on wireless channel characteristics have been proposed as an alternative to standard key-management schemes. In this work, we discuss past work in the field and offer a generalized scheme for the generation of private keys using uncorrelated channels in multiple domains. Proposed cognitive enhancements measure channel characteristics, to dynamically change transmission and reception parameters as well as estimate private key randomness and expiration times. Finally, results are presented on the implementation of a system for the generation of private keys for cryptographic communications using channel impulse-response estimation at 60 GHz. The testbed is composed of commercial millimeter-wave VubIQ transceivers, laboratory equipment, and software implemented in MATLAB. Novel cognitive enhancements are demonstrated, using channel estimation to dynamically change system parameters and estimate cryptographic key strength. We show for a complex channel that secret key generation can be accomplished on the order of 100 kb/s.
A Novel Comb-Pilot Transform Domain Frequency Diversity Channel Estimation for OFDM System
Directory of Open Access Journals (Sweden)
L. Liu
2009-12-01
Full Text Available Due to implementation complexity, the transform domain channel estimation based on training symbols or comb-type pilots has been paid more attention because of its efficient algorithm FFT/IFFT. However, in a comb-type OFDM system, the length of the channel impulse response is much smaller than the pilot number. In this case, the comb-pilot transform domain channel estimation only works as interpolation like the Least Squares (LS algorithm, but loses the noise suppression function. In this paper, we propose a novel frequency diversity channel estimation method via grouped pilots combining. With this estimator, not only the channel frequency response on non-pilot subcarriers can be interpolated, but also the noise can be better suppressed. Moreover, it does not need prior statistical characteristics of the wireless channel.
Blood velocity estimation using ultrasound and spectral iterative adaptive approaches
DEFF Research Database (Denmark)
Gudmundson, Erik; Jakobsson, Andreas; Jensen, Jørgen Arendt
2011-01-01
-mode images are interleaved with the Doppler emissions. Furthermore, the techniques are shown, using both simplified and more realistic Field II simulations as well as in vivo data, to outperform current state-of-the-art techniques, allowing for accurate estimation of the blood velocity spectrum using only 30......This paper proposes two novel iterative data-adaptive spectral estimation techniques for blood velocity estimation using medical ultrasound scanners. The techniques make no assumption on the sampling pattern of the emissions or the depth samples, allowing for duplex mode transmissions where B...
Low-sampling-rate ultra-wideband channel estimation using equivalent-time sampling
Ballal, Tarig
2014-09-01
In this paper, a low-sampling-rate scheme for ultra-wideband channel estimation is proposed. The scheme exploits multiple observations generated by transmitting multiple pulses. In the proposed scheme, P pulses are transmitted to produce channel impulse response estimates at a desired sampling rate, while the ADC samples at a rate that is P times slower. To avoid loss of fidelity, the number of sampling periods (based on the desired rate) in the inter-pulse interval is restricted to be co-prime with P. This condition is affected when clock drift is present and the transmitted pulse locations change. To handle this case, and to achieve an overall good channel estimation performance, without using prior information, we derive an improved estimator based on the bounded data uncertainty (BDU) model. It is shown that this estimator is related to the Bayesian linear minimum mean squared error (LMMSE) estimator. Channel estimation performance of the proposed sub-sampling scheme combined with the new estimator is assessed in simulation. The results show that high reduction in sampling rate can be achieved. The proposed estimator outperforms the least squares estimator in almost all cases, while in the high SNR regime it also outperforms the LMMSE estimator. In addition to channel estimation, a synchronization method is also proposed that utilizes the same pulse sequence used for channel estimation. © 2014 IEEE.
Pilot power optimization for AF relaying using maximum likelihood channel estimation
Wang, Kezhi
2014-09-01
Bit error rates (BERs) for amplify-and-forward (AF) relaying systems with two different pilot-symbol-aided channel estimation methods, disintegrated channel estimation (DCE) and cascaded channel estimation (CCE), are derived in Rayleigh fading channels. Based on these BERs, the pilot powers at the source and at the relay are optimized when their total transmitting powers are fixed. Numerical results show that the optimized system has a better performance than other conventional nonoptimized allocation systems. They also show that the optimal pilot power in variable gain is nearly the same as that in fixed gain for similar system settings. andcopy; 2014 IEEE.
Adaptive distributed parameter and input estimation in linear parabolic PDEs
Mechhoud, Sarra
2016-01-01
In this paper, we discuss the on-line estimation of distributed source term, diffusion, and reaction coefficients of a linear parabolic partial differential equation using both distributed and interior-point measurements. First, new sufficient identifiability conditions of the input and the parameter simultaneous estimation are stated. Then, by means of Lyapunov-based design, an adaptive estimator is derived in the infinite-dimensional framework. It consists of a state observer and gradient-based parameter and input adaptation laws. The parameter convergence depends on the plant signal richness assumption, whereas the state convergence is established using a Lyapunov approach. The results of the paper are illustrated by simulation on tokamak plasma heat transport model using simulated data.
A burst-mode photon counting receiver with automatic channel estimation and bit rate detection
Rao, Hemonth G.; DeVoe, Catherine E.; Fletcher, Andrew S.; Gaschits, Igor D.; Hakimi, Farhad; Hamilton, Scott A.; Hardy, Nicholas D.; Ingwersen, John G.; Kaminsky, Richard D.; Moores, John D.; Scheinbart, Marvin S.; Yarnall, Timothy M.
2016-04-01
We demonstrate a multi-rate burst-mode photon-counting receiver for undersea communication at data rates up to 10.416 Mb/s over a 30-foot water channel. To the best of our knowledge, this is the first demonstration of burst-mode photon-counting communication. With added attenuation, the maximum link loss is 97.1 dB at λ=517 nm. In clear ocean water, this equates to link distances up to 148 meters. For λ=470 nm, the achievable link distance in clear ocean water is 450 meters. The receiver incorporates soft-decision forward error correction (FEC) based on a product code of an inner LDPC code and an outer BCH code. The FEC supports multiple code rates to achieve error-free performance. We have selected a burst-mode receiver architecture to provide robust performance with respect to unpredictable channel obstructions. The receiver is capable of on-the-fly data rate detection and adapts to changing levels of signal and background light. The receiver updates its phase alignment and channel estimates every 1.6 ms, allowing for rapid changes in water quality as well as motion between transmitter and receiver. We demonstrate on-the-fly rate detection, channel BER within 0.2 dB of theory across all data rates, and error-free performance within 1.82 dB of soft-decision capacity across all tested code rates. All signal processing is done in FPGAs and runs continuously in real time.
Frequency domain based LS channel estimation in OFDM based Power line communications
Bogdanović, Mario
2015-01-01
This paper is focused on low voltage power line communication (PLC) realization with an emphasis on channel estimation techniques. The Orthogonal Frequency Division Multiplexing (OFDM) scheme is preferred technology in PLC systems because of its effective combat with frequency selective fading properties of PLC channel. As the channel estimation is one of the crucial problems in OFDM based PLC system because of a problematic area of PLC signal attenuation and interference, the improved LS est...
Objective Evaluation of the Audibility of Transient Errors in an Adaptive A/D Conversion Channel
DEFF Research Database (Denmark)
Marker-Villumsen, Niels; Jørgensen, Ivan Harald Holger; Bruun, Erik
2014-01-01
An adaptive analog-to-digital conversion channel for audio, using automatic gain control, generates transient errors that may be audible. Evaluating the audibility of such errors requires subjective evaluation using listening tests. From an electrical circuit design point-of-view this is not feas......An adaptive analog-to-digital conversion channel for audio, using automatic gain control, generates transient errors that may be audible. Evaluating the audibility of such errors requires subjective evaluation using listening tests. From an electrical circuit design point...
Adaptive Motion Estimation Processor for Autonomous Video Devices
Directory of Open Access Journals (Sweden)
Dias T
2007-01-01
Full Text Available Motion estimation is the most demanding operation of a video encoder, corresponding to at least 80% of the overall computational cost. As a consequence, with the proliferation of autonomous and portable handheld devices that support digital video coding, data-adaptive motion estimation algorithms have been required to dynamically configure the search pattern not only to avoid unnecessary computations and memory accesses but also to save energy. This paper proposes an application-specific instruction set processor (ASIP to implement data-adaptive motion estimation algorithms that is characterized by a specialized datapath and a minimum and optimized instruction set. Due to its low-power nature, this architecture is highly suitable to develop motion estimators for portable, mobile, and battery-supplied devices. Based on the proposed architecture and the considered adaptive algorithms, several motion estimators were synthesized both for a Virtex-II Pro XC2VP30 FPGA from Xilinx, integrated within an ML310 development platform, and using a StdCell library based on a 0.18 μm CMOS process. Experimental results show that the proposed architecture is able to estimate motion vectors in real time for QCIF and CIF video sequences with a very low-power consumption. Moreover, it is also able to adapt the operation to the available energy level in runtime. By adjusting the search pattern and setting up a more convenient operating frequency, it can change the power consumption in the interval between 1.6 mW and 15 mW.
Estimating meme fitness in adaptive memetic algorithms for combinatorial problems.
Smith, J E
2012-01-01
Among the most promising and active research areas in heuristic optimisation is the field of adaptive memetic algorithms (AMAs). These gain much of their reported robustness by adapting the probability with which each of a set of local improvement operators is applied, according to an estimate of their current value to the search process. This paper addresses the issue of how the current value should be estimated. Assuming the estimate occurs over several applications of a meme, we consider whether the extreme or mean improvements should be used, and whether this aggregation should be global, or local to some part of the solution space. To investigate these issues, we use the well-established COMA framework that coevolves the specification of a population of memes (representing different local search algorithms) alongside a population of candidate solutions to the problem at hand. Two very different memetic algorithms are considered: the first using adaptive operator pursuit to adjust the probabilities of applying a fixed set of memes, and a second which applies genetic operators to dynamically adapt and create memes and their functional definitions. For the latter, especially on combinatorial problems, credit assignment mechanisms based on historical records, or on notions of landscape locality, will have limited application, and it is necessary to estimate the value of a meme via some form of sampling. The results on a set of binary encoded combinatorial problems show that both methods are very effective, and that for some problems it is necessary to use thousands of variables in order to tease apart the differences between different reward schemes. However, for both memetic algorithms, a significant pattern emerges that reward based on mean improvement is better than that based on extreme improvement. This contradicts recent findings from adapting the parameters of operators involved in global evolutionary search. The results also show that local reward schemes
Directory of Open Access Journals (Sweden)
Xiaoyang Liu
2017-01-01
Full Text Available In order to analyze the channel estimation performance of near space high altitude platform station (HAPS in wireless communication system, the structure and formation of HAPS are studied in this paper. The traditional Least Squares (LS channel estimation method and Singular Value Decomposition-Linear Minimum Mean-Squared (SVD-LMMS channel estimation method are compared and investigated. A novel channel estimation method and model are proposed. The channel estimation performance of HAPS is studied deeply. The simulation and theoretical analysis results show that the performance of the proposed method is better than the traditional methods. The lower Bit Error Rate (BER and higher Signal Noise Ratio (SNR can be obtained by the proposed method compared with the LS and SVD-LMMS methods.
A Study of an Iterative Channel Estimation Scheme of FS-FBMC System
Directory of Open Access Journals (Sweden)
YongJu Won
2017-01-01
Full Text Available A filter bank multicarrier on offset-quadrature amplitude modulation (FBMC/OQAM system is an alternative multicarrier modulation scheme that does not need cyclic prefix (CP even in the presence of a multipath fading channel by the properties of prototype filter. The FBMC/OQAM system can be implemented either by using the poly-phase network with fast fourier transform (PPN-FFT or by using the extended FFT on a frequency-spreading (FS domain. In this paper, we propose an iterative channel estimation scheme for each sub channel of a FBMC/OQAM system over a frequency-spreading domain. The proposed scheme first estimates the channel using the received pilot signal in the subchannel domain and interpolates the estimated channel to fine frequency-spreading domain. Then the channel compensated FS domain pilot is despread again to modify the channel state information (CSI estimation. Computer simulation shows that the proposed method outperforms the conventional FBMC/OQAM channel estimator in a frequency selective channel.
Directory of Open Access Journals (Sweden)
Hongjun Xu
2011-07-01
Full Text Available A channel and delay estimation algorithm for both positive and negative delay, based on the distributed Alamouti scheme, has been recently discussed for base-station–based asynchronous cooperative systems in frequency-flat fading channels. This paper extends the algorithm, the maximum likelihood estimator, to work in frequency-selective fading channels. The minimum mean square error (MMSE performance of channel estimation for both packet schemes and normal schemes is discussed in this paper. The symbol error rate (SER performance of equalisation and detection for both time-reversal space-time block code (STBC and single-carrier STBC is also discussed in this paper. The MMSE simulation results demonstrated the superior performance of the packet scheme over the normal scheme with an improvement in performance of up to 6 dB when feedback was used in the frequency-selective channel at a MSE of 3 x 10^{–2}. The SER simulation results showed that, although both the normal and packet schemes achieved similar diversity orders, the packet scheme demonstrated a 1 dB coding gain over the normal scheme at a SER of 10^{–5}. Finally, the SER simulations showed that the frequency-selective fading system outperformed the frequency-flat fading system.
PERFORMANCE OF THE ZERO FORCING PRECODING MIMO BROADCAST SYSTEMS WITH CHANNEL ESTIMATION ERRORS
Institute of Scientific and Technical Information of China (English)
Wang Jing; Liu Zhanli; Wang Yan; You Xiaohu
2007-01-01
In this paper, the effect of channel estimation errors upon the Zero Forcing (ZF) precoding Multiple Input Multiple Output Broadcast (MIMO BC) systems was studied. Based on the two kinds of Gaussian estimation error models, the performance analysis is conducted under different power allocation strategies. Analysis and simulation show that if the covariance of channel estimation errors is independent of the received Signal to Noise Ratio (SNR), imperfect channel knowledge deteriorates the sum capacity and the Bit Error Rate (BER) performance severely. However, under the situation of orthogonal training and the Minimum Mean Square Error (MMSE) channel estimation, the sum capacity and BER performance are consistent with those of the perfect Channel State Information (CSI)with only a performance degradation.
Analysis of Traffic Parameter Estimation and Its Impacts on Wireless Channel
Institute of Scientific and Technical Information of China (English)
徐玉滨; 沙学军; 强蔚
2004-01-01
Wide band or broadband access was paid much attention with the development of radio transmission technique. The wireless access control procedure play an important role in this type of system and efficiency of control algorithm has a great impact on throughput of channel resource. Based on wide band network control model and the characteristics of radio channel, this paper proposed a channel traffic estimation method and then performed a dynamic parameter control procedure and give detail analysis on estimation error and its impact on channel throughput and delay performance. Computation and simulation of system performance show a positive solution on system design.
Advanced Channel Estimation and Multiuser Detection in GSM
DEFF Research Database (Denmark)
Arildsen, Thomas; Blauendahl, Jesper
A single-antenna interference cancellation-capable data detector employing the SAGE-algorithm for GSM downlink transmission with co-channel interference has been designed and tested. Two scenarios were considered: First, a frequency-flat Rayleigh fading scenario with synchronously received users...
CHANNEL ESTIMATION FOR ZT DFT-s-OFDM
DEFF Research Database (Denmark)
2018-01-01
A signal modulated according to zero-tail discrete Fourier transform spread orthogonal frequency division multiplexing (ZT DFT-s-OFDM) is received over a channel. The signal is down-sampled into a first sequence comprising N samples, N corresponding to the number of used subcarriers. The first Nh...
Conveyance estimation in channels with emergent bank vegetation
African Journals Online (AJOL)
2009-03-20
Mar 20, 2009 ... tion of the transverse distribution of the depth-averaged velocity. Recommendations ... resistance coefficient, and the coefficient for the vegetation interface. ... on the channel hydraulics, including the turbulence structure. (e.g. Choi .... characteristics within the zone as well as the flow conditions in the clear ...
Angular Domain Data-Assisted Channel Estimation for Pilot Decontamination in Massive MIMO
Directory of Open Access Journals (Sweden)
Yihenew Beyene
2017-01-01
Full Text Available Massive Multiple-Input-Multiple-Output (M-MIMO system is a promising technology that offers to mobile networks substantial increase in throughput. In Time-Division Duplexing (TDD, the uplink training allows a Base Station (BS to acquire Channel State Information (CSI for both uplink reception and downlink transmission. This is essential for M-MIMO systems where downlink training pilots would consume large portion of the bandwidth. In densely populated areas, pilot symbols are reused among neighboring cells. Pilot contamination is the fundamental bottleneck on the performance of M-MIMO systems. Pilot contamination effect in antenna arrays can be mitigated by treating the channel estimation problem in angular domain where channel sparsity can be exploited. In this paper, we introduce a codebook that projects the channel into orthogonal beams and apply Minimum Mean-Squared Error (MMSE criterion to estimate the channel. We also propose data-aided channel covariance matrix estimation algorithm for angular domain MMSE channel estimator by exploiting properties of linear antenna array. The algorithm is based on simple linear operations and no matrix inversion is involved. Numerical results show that the algorithm performs well in mitigating pilot contamination where the desired channel and other interfering channels span overlapping angle-of-arrivals.
A Rate Adaptation Scheme According to Channel Conditions in Wireless LANs
Numoto, Daisuke; Inai, Hiroshi
Rate adaptation in wireless LANs is to select the most suitable transmission rate automatically according to channel condition. If the channel condition is good, a station can choose a higher transmission rate, otherwise, it should choose a lower but noise-resistant transmission rate. Since IEEE 802.11 does not specify any rate adaptation scheme, several schemes have been proposed. However those schemes provide low throughput or unfair transmission opportunities among stations especially when the number of stations increases. In this paper, we propose a rate adaptation scheme under which the transmission rate quickly closes and then stays around an optimum rate even in the presence of a large number of stations. Via simulation, our scheme provides higher throughput than existing ones and almost equal fairness.
Performance of adaptive MS-GSC with co-channel interference
Daghfous, Mohamed A.
2011-06-01
Minimum selection generalized selection combining(MS-GSC) scheme has been proposed as a generalized power-saving variant of the conventional generalized selection combining(GSC) scheme. Previous analysis of the performance of MS-GSC has focused on interference-free environments. This paper aims to investigate the performance of adaptive signal-to-noise ratio (SNR)-based MS-GSC in the presence of co-channel interference over multipath fading channels. The adaptation thresholds are selected to enhance either the spectral efficiency or power efficiency of discrete-time rectangular signaling system. New closed-form expressions for the statistics of combined signal-to-interference-plus-noise ratio (SINR) are presented, which are then used to obtain analytical formulations for various performance measures. Numerical and simulation comparisons for the performance of the adaptation scheme are provided. © 2011 IEEE.
A Fast Iterative Bayesian Inference Algorithm for Sparse Channel Estimation
DEFF Research Database (Denmark)
Pedersen, Niels Lovmand; Manchón, Carles Navarro; Fleury, Bernard Henri
2013-01-01
representation of the Bessel K probability density function; a highly efficient, fast iterative Bayesian inference method is then applied to the proposed model. The resulting estimator outperforms other state-of-the-art Bayesian and non-Bayesian estimators, either by yielding lower mean squared estimation error...
AN ADAPTIVE MULTI-CHANNEL SPECTROELLIPSOMETER FOR ECOLOGICAL MONITORING
Directory of Open Access Journals (Sweden)
F. A. Mkrtchyan
2012-09-01
Full Text Available The creation of multichannel polarization optical instrumentation and use of spectroellipsometric technology are very important for the real-time ecological control of aquatic environment. Spectroellipsometric devices give us high precision of measurements. This report is aimed to describe: •A technology of combined use of spectroellipsometry and algorithms of identification and recognition that allowed the creation of a standard integral complex of instrumental, algorithmic, modular and software tools for the collection and processing of data on the aquatic environment quality with forecasting and decision - making functions. •A compact measuring - information multichannel spectroellipsometric system (device for monitoring the quality of aquatic environment, that is based on the combined use of spectroellipsometry and training, classification, and identification algorithms. This spectroellipsometric system will differ from modern foreign analogues by the use of a new and very promising method of ellipsometric measurements, an original element base of polarization optics and a complex mathematical approach to estimating the quality of a water object subjected to anthropogenic influence.Unlike foreign analogues, the system has no rotating polarization elements. This allows one to increase the signal-to-noise ratio and the long-term stability of measurements, to simplify and reduce the price of multichannel spectroellipsometers. The system will be trainable to the recognition of the pollutants of aquatic environment. A spectroellipsometer in laboratories of V.A. Kotelnikov's Institute of Radioengineering and Electronics, Russian Academy of Sciences is designed for in-situ real time measurements of spectra of ellipsometric parameters Psi and Delta with consequent changeover to spectra of transmitted and reflected signal from water media in frames of used physical model of water environment.
Gorshtein, Albert; Levy, Omri; Katz, Gilad; Sadot, Dan
2013-09-23
Blind channel estimation is critical for digital signal processing (DSP) compensation of optical fiber communications links. The overall channel consists of deterministic distortions such as chromatic dispersion, as well as random and time varying distortions including polarization mode dispersion and timing jitter. It is critical to obtain robust acquisition and tracking methods for estimating these distortions effects, which, in turn, can be compensated by means of DSP such as Maximum Likelihood Sequence Estimation (MLSE). Here, a novel blind estimation algorithm is developed, accompanied by inclusive mathematical modeling, and followed by extensive set of real time experiments that verify quantitatively its performance and convergence. The developed blind channel estimation is used as the basis of an MLSE receiver. The entire scheme is fully implemented in a 65 nm CMOS Application Specific Integrated Circuit (ASIC). Experimental measurements and results are presented, including Bit Error Rate (BER) measurements, which demonstrate the successful data recovery by the MLSE ASIC under various channel conditions and distances.
An Adaptive Motion Estimation Scheme for Video Coding
Directory of Open Access Journals (Sweden)
Pengyu Liu
2014-01-01
Full Text Available The unsymmetrical-cross multihexagon-grid search (UMHexagonS is one of the best fast Motion Estimation (ME algorithms in video encoding software. It achieves an excellent coding performance by using hybrid block matching search pattern and multiple initial search point predictors at the cost of the computational complexity of ME increased. Reducing time consuming of ME is one of the key factors to improve video coding efficiency. In this paper, we propose an adaptive motion estimation scheme to further reduce the calculation redundancy of UMHexagonS. Firstly, new motion estimation search patterns have been designed according to the statistical results of motion vector (MV distribution information. Then, design a MV distribution prediction method, including prediction of the size of MV and the direction of MV. At last, according to the MV distribution prediction results, achieve self-adaptive subregional searching by the new estimation search patterns. Experimental results show that more than 50% of total search points are dramatically reduced compared to the UMHexagonS algorithm in JM 18.4 of H.264/AVC. As a result, the proposed algorithm scheme can save the ME time up to 20.86% while the rate-distortion performance is not compromised.
Pilot-based parametric channel estimation algorithm for DCO-OFDM-based visual light communications
Qian, Xuewen; Deng, Honggui; He, Hailang
2017-10-01
Due to wide modulation bandwidth in optical communication, multipath channels may be non-sparse and deteriorate communication performance heavily. Traditional compressive sensing-based channel estimation algorithm cannot be employed in this kind of situation. In this paper, we propose a practical parametric channel estimation algorithm for orthogonal frequency division multiplexing (OFDM)-based visual light communication (VLC) systems based on modified zero correlation code (ZCC) pair that has the impulse-like correlation property. Simulation results show that the proposed algorithm achieves better performances than existing least squares (LS)-based algorithm in both bit error ratio (BER) and frequency response estimation.
Particle Filtering for Multiple Access DS/CDMA Systems DS/CDMA Channel Estimation
Directory of Open Access Journals (Sweden)
Rafael Oliveira Ribeiro
2013-09-01
Full Text Available This article discusses computational implementation aspects and performance of a Bayesian methodology, namely particle filter (PF. The PF channel estimation technique is directly applied to the channel coefficients estimation of DS/CDMA systems. Simulation results for non-line-of-sight (NLOS Rayleigh fading channel propagation have indicated that the bootstrap PF estimator is capable to provide RMSE in the range of [10-3 ; 10-2] for a wide range of multiple access interference (MAI levels and signal-noise ratio (SNR, and still be able to offer robustness to near-far ratio (NFR effect.
An Iterative Adaptive Approach for Blood Velocity Estimation Using Ultrasound
DEFF Research Database (Denmark)
Gudmundson, Erik; Jakobsson, Andreas; Jensen, Jørgen Arendt
2010-01-01
This paper proposes a novel iterative data-adaptive spectral estimation technique for blood velocity estimation using medical ultrasound scanners. The technique makes no assumption on the sampling pattern of the slow-time or the fast-time samples, allowing for duplex mode transmissions where B......-mode images are interleaved with the Doppler emissions. Furthermore, the technique is shown, using both simplified and more realistic Field II simulations, to outperform current state-of-the-art techniques, allowing for accurate estimation of the blood velocity spectrum using only 30% of the transmissions......, thereby allowing for the examination of two separate vessel regions while retaining an adequate updating rate of the B-mode images. In addition, the proposed method also allows for more flexible transmission patterns, as well as exhibits fewer spectral artifacts as compared to earlier techniques....
Channel estimation in few mode fiber mode division multiplexing transmission system
Hei, Yongqiang; Li, Li; Li, Wentao; Li, Xiaohui; Shi, Guangming
2018-03-01
It is abundantly clear that obtaining the channel state information (CSI) is of great importance for the equalization and detection in coherence receivers. However, to the best of the authors' knowledge, in most of the existing literatures, CSI is assumed to be perfectly known at the receiver. So far, few literature discusses the effects of imperfect CSI on MDM system performance caused by channel estimation. Motivated by that, in this paper, the channel estimation in few mode fiber (FMF) mode division multiplexing (MDM) system is investigated, in which two classical channel estimation methods, i.e., least square (LS) method and minimum mean square error (MMSE) method, are discussed with the assumption of the spatially white noise lumped at the receiver side of MDM system. Both the capacity and BER performance of MDM system affected by mode-dependent gain or loss (MDL) with different channel estimation errors have been studied. Simulation results show that the capacity and BER performance can be further deteriorated in MDM system by the channel estimation, and an 1e-3 variance of channel estimation error is acceptable in MDM system with 0-6 dB MDL values.
Al-Salihi, Hayder Qahtan Kshash; Nakhai, Mohammad Reza
2017-01-01
Efficient and highly accurate channel state information (CSI) at the base station (BS) is essential to achieve the potential benefits of massive multiple input multiple output (MIMO) systems. However, the achievable accuracy that is attainable is limited in practice due to the problem of pilot contamination. It has recently been shown that compressed sensing (CS) techniques can address the pilot contamination problem. However, CS-based channel estimation requires prior knowledge of channel sp...
Davletshin, I. A.; Dushina, O. A.; Mikheev, N. I.; Kolchin, S. A.
2017-11-01
The pulsating flow in a circular channel with semicircular annular ribs as discrete roughness elements has been studied experimentally. Air flow under atmospheric conditions at the channel inlet has been considered. Steady and pulsating air flow has been studied under different frequencies and amplitudes of forced pulsations generated by periodic blockage of the channel cross section by a rotating flap. Flow resistance in pulsating regimes has been estimated from the average static pressure drop. The resistance values attained twice the steady flow ones.
Wolf, Michael
2012-01-01
A document describes an algorithm created to estimate the mass placed on a sample verification sensor (SVS) designed for lunar or planetary robotic sample return missions. A novel SVS measures the capacitance between a rigid bottom plate and an elastic top membrane in seven locations. As additional sample material (soil and/or small rocks) is placed on the top membrane, the deformation of the membrane increases the capacitance. The mass estimation algorithm addresses both the calibration of each SVS channel, and also addresses how to combine the capacitances read from each of the seven channels into a single mass estimate. The probabilistic approach combines the channels according to the variance observed during the training phase, and provides not only the mass estimate, but also a value for the certainty of the estimate. SVS capacitance data is collected for known masses under a wide variety of possible loading scenarios, though in all cases, the distribution of sample within the canister is expected to be approximately uniform. A capacitance-vs-mass curve is fitted to this data, and is subsequently used to determine the mass estimate for the single channel s capacitance reading during the measurement phase. This results in seven different mass estimates, one for each SVS channel. Moreover, the variance of the calibration data is used to place a Gaussian probability distribution function (pdf) around this mass estimate. To blend these seven estimates, the seven pdfs are combined into a single Gaussian distribution function, providing the final mean and variance of the estimate. This blending technique essentially takes the final estimate as an average of the estimates of the seven channels, weighted by the inverse of the channel s variance.
The MISO Wiretap Channel with Noisy Main Channel Estimation in the High Power Regime
Rezki, Zouheir
2017-02-07
We improve upon our previous upper bound on the secrecy capacity of the wiretap channel with multiple transmit antennas and single-antenna receivers, with noisy main channel state information (CSI) at the transmitter (CSI-T). Specifically, we show that if the main CSI error does not scale with the power budget at the transmitter P̅, then the secrecy capacity is )bounded above essentially by log log (P̅ yielding a secure degree of freedom (sdof) equal to zero. However, if the main CSI error scales as O(P̅-β), for β ∈ [0,1], then the sdof is equal to β.
The MISO Wiretap Channel with Noisy Main Channel Estimation in the High Power Regime
Rezki, Zouheir; Chaaban, Anas; Alomair, Basel; Alouini, Mohamed-Slim
2017-01-01
We improve upon our previous upper bound on the secrecy capacity of the wiretap channel with multiple transmit antennas and single-antenna receivers, with noisy main channel state information (CSI) at the transmitter (CSI-T). Specifically, we show that if the main CSI error does not scale with the power budget at the transmitter P̅, then the secrecy capacity is )bounded above essentially by log log (P̅ yielding a secure degree of freedom (sdof) equal to zero. However, if the main CSI error scales as O(P̅-β), for β ∈ [0,1], then the sdof is equal to β.
Rotated Walsh-Hadamard Spreading with Robust Channel Estimation for a Coded MC-CDMA System
Directory of Open Access Journals (Sweden)
Raulefs Ronald
2004-01-01
Full Text Available We investigate rotated Walsh-Hadamard spreading matrices for a broadband MC-CDMA system with robust channel estimation in the synchronous downlink. The similarities between rotated spreading and signal space diversity are outlined. In a multiuser MC-CDMA system, possible performance improvements are based on the chosen detector, the channel code, and its Hamming distance. By applying rotated spreading in comparison to a standard Walsh-Hadamard spreading code, a higher throughput can be achieved. As combining the channel code and the spreading code forms a concatenated code, the overall minimum Hamming distance of the concatenated code increases. This asymptotically results in an improvement of the bit error rate for high signal-to-noise ratio. Higher convolutional channel code rates are mostly generated by puncturing good low-rate channel codes. The overall Hamming distance decreases significantly for the punctured channel codes. Higher channel code rates are favorable for MC-CDMA, as MC-CDMA utilizes diversity more efficiently compared to pure OFDMA. The application of rotated spreading in an MC-CDMA system allows exploiting diversity even further. We demonstrate that the rotated spreading gain is still present for a robust pilot-aided channel estimator. In a well-designed system, rotated spreading extends the performance by using a maximum likelihood detector with robust channel estimation at the receiver by about 1 dB.
Robust estimation of adaptive tensors of curvature by tensor voting.
Tong, Wai-Shun; Tang, Chi-Keung
2005-03-01
Although curvature estimation from a given mesh or regularly sampled point set is a well-studied problem, it is still challenging when the input consists of a cloud of unstructured points corrupted by misalignment error and outlier noise. Such input is ubiquitous in computer vision. In this paper, we propose a three-pass tensor voting algorithm to robustly estimate curvature tensors, from which accurate principal curvatures and directions can be calculated. Our quantitative estimation is an improvement over the previous two-pass algorithm, where only qualitative curvature estimation (sign of Gaussian curvature) is performed. To overcome misalignment errors, our improved method automatically corrects input point locations at subvoxel precision, which also rejects outliers that are uncorrectable. To adapt to different scales locally, we define the RadiusHit of a curvature tensor to quantify estimation accuracy and applicability. Our curvature estimation algorithm has been proven with detailed quantitative experiments, performing better in a variety of standard error metrics (percentage error in curvature magnitudes, absolute angle difference in curvature direction) in the presence of a large amount of misalignment noise.
Adaptive Distributed Video Coding with Correlation Estimation using Expectation Propagation.
Cui, Lijuan; Wang, Shuang; Jiang, Xiaoqian; Cheng, Samuel
2012-10-15
Distributed video coding (DVC) is rapidly increasing in popularity by the way of shifting the complexity from encoder to decoder, whereas no compression performance degrades, at least in theory. In contrast with conventional video codecs, the inter-frame correlation in DVC is explored at decoder based on the received syndromes of Wyner-Ziv (WZ) frame and side information (SI) frame generated from other frames available only at decoder. However, the ultimate decoding performances of DVC are based on the assumption that the perfect knowledge of correlation statistic between WZ and SI frames should be available at decoder. Therefore, the ability of obtaining a good statistical correlation estimate is becoming increasingly important in practical DVC implementations. Generally, the existing correlation estimation methods in DVC can be classified into two main types: pre-estimation where estimation starts before decoding and on-the-fly (OTF) estimation where estimation can be refined iteratively during decoding. As potential changes between frames might be unpredictable or dynamical, OTF estimation methods usually outperforms pre-estimation techniques with the cost of increased decoding complexity (e.g., sampling methods). In this paper, we propose a low complexity adaptive DVC scheme using expectation propagation (EP), where correlation estimation is performed OTF as it is carried out jointly with decoding of the factor graph-based DVC code. Among different approximate inference methods, EP generally offers better tradeoff between accuracy and complexity. Experimental results show that our proposed scheme outperforms the benchmark state-of-the-art DISCOVER codec and other cases without correlation tracking, and achieves comparable decoding performance but with significantly low complexity comparing with sampling method.
Adaptive distributed video coding with correlation estimation using expectation propagation
Cui, Lijuan; Wang, Shuang; Jiang, Xiaoqian; Cheng, Samuel
2012-10-01
Distributed video coding (DVC) is rapidly increasing in popularity by the way of shifting the complexity from encoder to decoder, whereas no compression performance degrades, at least in theory. In contrast with conventional video codecs, the inter-frame correlation in DVC is explored at decoder based on the received syndromes of Wyner-Ziv (WZ) frame and side information (SI) frame generated from other frames available only at decoder. However, the ultimate decoding performances of DVC are based on the assumption that the perfect knowledge of correlation statistic between WZ and SI frames should be available at decoder. Therefore, the ability of obtaining a good statistical correlation estimate is becoming increasingly important in practical DVC implementations. Generally, the existing correlation estimation methods in DVC can be classified into two main types: pre-estimation where estimation starts before decoding and on-the-fly (OTF) estimation where estimation can be refined iteratively during decoding. As potential changes between frames might be unpredictable or dynamical, OTF estimation methods usually outperforms pre-estimation techniques with the cost of increased decoding complexity (e.g., sampling methods). In this paper, we propose a low complexity adaptive DVC scheme using expectation propagation (EP), where correlation estimation is performed OTF as it is carried out jointly with decoding of the factor graph-based DVC code. Among different approximate inference methods, EP generally offers better tradeoff between accuracy and complexity. Experimental results show that our proposed scheme outperforms the benchmark state-of-the-art DISCOVER codec and other cases without correlation tracking, and achieves comparable decoding performance but with significantly low complexity comparing with sampling method.
Liang Yang,
2013-06-01
In this paper, we consider the performance of a two-way amplify-and-forward relaying network (AF TWRN) in the presence of unequal power co-channel interferers (CCI). Specifically, we first consider AF TWRN with an interference-limited relay and two noisy-nodes with channel estimation errors and CCI. We derive the approximate signal-to-interference plus noise ratio expressions and then use them to evaluate the outage probability, error probability, and achievable rate. Subsequently, to investigate the joint effects of the channel estimation error and CCI on the system performance, we extend our analysis to a multiple-relay network and derive several asymptotic performance expressions. For comparison purposes, we also provide the analysis for the relay selection scheme under the total power constraint at the relays. For AF TWRN with channel estimation error and CCI, numerical results show that the performance of the relay selection scheme is not always better than that of the all-relay participating case. In particular, the relay selection scheme can improve the system performance in the case of high power levels at the sources and small powers at the relays.
Yang, Liang
2013-04-01
In this paper, we consider the performance of a two-way amplify-and-forward relaying network (AF TWRN) in the presence of unequal power co-channel interferers (CCI). Specifically, we consider AF TWRN with an interference-limited relay and two noisy-nodes with channel estimation error and CCI. We derive the approximate signal-to-interference plus noise ratio expressions and then use these expressions to evaluate the outage probability and error probability. Numerical results show that the approximate closed-form expressions are very close to the exact ones. © 2013 IEEE.
Overlay Cognitive Radios With Channel-Aware Adaptive Link Selection and Buffer-Aided Relaying
Shaqfeh, Mohammad
2015-08-01
The aim of this work is to maximize the long-term average achievable rate region of a primary and a secondary source-destination pairs operating in an overlay setup over block-fading channels. To achieve this objective, we propose an opportunistic strategy to grant channel access to the primary and secondary sources based on the channel conditions in order to exploit the available multiple-link diversity gains in the system. The secondary source has causal knowledge of the primary messages and it acts as a relay of the primary source in return for getting access to the channel. To maximize the gains of relaying, the relay and destination are equipped with buffers to enable the use of channel-aware adaptive link selection. We propose and optimize different link selection policies and characterize their expected achievable rates. Also, we provide several numerical results to demonstrate the evident mutual benefits of buffer-aided cooperation and adaptive link selection to the primary and the secondary source-destination pairs. © 1972-2012 IEEE.
Overlay Cognitive Radios With Channel-Aware Adaptive Link Selection and Buffer-Aided Relaying
Shaqfeh, Mohammad; Zafar, Ammar; Alnuweiri, Hussein; Alouini, Mohamed-Slim
2015-01-01
The aim of this work is to maximize the long-term average achievable rate region of a primary and a secondary source-destination pairs operating in an overlay setup over block-fading channels. To achieve this objective, we propose an opportunistic strategy to grant channel access to the primary and secondary sources based on the channel conditions in order to exploit the available multiple-link diversity gains in the system. The secondary source has causal knowledge of the primary messages and it acts as a relay of the primary source in return for getting access to the channel. To maximize the gains of relaying, the relay and destination are equipped with buffers to enable the use of channel-aware adaptive link selection. We propose and optimize different link selection policies and characterize their expected achievable rates. Also, we provide several numerical results to demonstrate the evident mutual benefits of buffer-aided cooperation and adaptive link selection to the primary and the secondary source-destination pairs. © 1972-2012 IEEE.
Unification of Frequency direction Pilot-symbol Aided Channel Estimation (PACE) for OFDM
DEFF Research Database (Denmark)
Rom, Christian; Manchón, Carles Navarro; Deneire, Luc
2007-01-01
their specificities, namely the presence of virtual subcarriers and non-sample-spaced channels. To ease this choice, we propose a unified presentation of estimators encompassing most of the algorithms that can be found in literature, which only differ by the assumptions made on the channel. This unification leads...
DEFF Research Database (Denmark)
Pittalà, Fabio; Hauske, Fabian N.; Ye, Yabin
2012-01-01
Efficient channel estimation for signal equalization and OPM based on short CAZAC sequences with QPSK and 8PSK constellation formats is demonstrated in a 224-Gb/s PDM 16-QAM optical linear transmission system....
Sparse Channel Estimation for MIMO-OFDM Two-Way Relay Network with Compressed Sensing
Directory of Open Access Journals (Sweden)
Aihua Zhang
2013-01-01
Full Text Available Accurate channel impulse response (CIR is required for equalization and can help improve communication service quality in next-generation wireless communication systems. An example of an advanced system is amplify-and-forward multiple-input multiple-output two-way relay network, which is modulated by orthogonal frequency-division multiplexing. Linear channel estimation methods, for example, least squares and expectation conditional maximization, have been proposed previously for the system. However, these methods do not take advantage of channel sparsity, and they decrease estimation performance. We propose a sparse channel estimation scheme, which is different from linear methods, at end users under the relay channel to enable us to exploit sparsity. First, we formulate the sparse channel estimation problem as a compressed sensing problem by using sparse decomposition theory. Second, the CIR is reconstructed by CoSaMP and OMP algorithms. Finally, computer simulations are conducted to confirm the superiority of the proposed methods over traditional linear channel estimation methods.
Impact of Channel Estimation Errors on Multiuser Detection via the Replica Method
Directory of Open Access Journals (Sweden)
Li Husheng
2005-01-01
Full Text Available For practical wireless DS-CDMA systems, channel estimation is imperfect due to noise and interference. In this paper, the impact of channel estimation errors on multiuser detection (MUD is analyzed under the framework of the replica method. System performance is obtained in the large system limit for optimal MUD, linear MUD, and turbo MUD, and is validated by numerical results for finite systems.
On the estimation of channel power distribution for PHWRs (Paper No. HMT-66-87)
International Nuclear Information System (INIS)
Parikh, M.V.; Kumar, A.N.; Krishnamohan, B.; Bhaskara Rao, P.
1987-01-01
In the case of PHWRs the estimation of channel power distribution is an important safety criteria. In this paper two methods based on theoretical estimation and the measured parameter are described. The comparison made shows good agreement in the prediction of channel power by both the methods. A parametric study in one of the measured parameters is also made which gives better agreement in results obtained. (author). 3 tabs
Multi-channel PSD Estimators for Speech Dereverberation
DEFF Research Database (Denmark)
Kuklasinski, Adam; Doclo, Simon; Gerkmann, Timo
2015-01-01
densities (PSDs). We first derive closed-form expressions for the mean square error (MSE) of both PSD estimators and then show that one estimator – previously used for speech dereverberation by the authors – always yields a better MSE. Only in the case of a two microphone array or for special spatial...... distributions of the interference both estimators yield the same MSE. The theoretically derived MSE values are in good agreement with numerical simulation results and with instrumental speech quality measures in a realistic speech dereverberation task for binaural hearing aids....
A Perspective for Time-Varying Channel Compensation with Model-Based Adaptive Passive Time-Reversal
Directory of Open Access Journals (Sweden)
Lussac P. MAIA
2015-06-01
in high frequency underwater acoustics is intended to be explored in future, based on the idea that a set of oceanic acoustic physical parameters – which are generally estimated in well-known low frequency matched field processing problems like geoacoustic assessment, ocean tomography and source localization – could be conveniently used on adaptive filters for channel compensation in DAUC systems.
Adaptive optimisation-offline cyber attack on remote state estimator
Huang, Xin; Dong, Jiuxiang
2017-10-01
Security issues of cyber-physical systems have received increasing attentions in recent years. In this paper, deception attacks on the remote state estimator equipped with the chi-squared failure detector are considered, and it is assumed that the attacker can monitor and modify all the sensor data. A novel adaptive optimisation-offline cyber attack strategy is proposed, where using the current and previous sensor data, the attack can yield the largest estimation error covariance while ensuring to be undetected by the chi-squared monitor. From the attacker's perspective, the attack is better than the existing linear deception attacks to degrade the system performance. Finally, some numerical examples are provided to demonstrate theoretical results.
Data adaptive estimation of transversal blood flow velocities
DEFF Research Database (Denmark)
Pirnia, E.; Jakobsson, A.; Gudmundson, E.
2014-01-01
the transversal blood flow. In this paper, we propose a novel data-adaptive blood flow estimator exploiting this modulation scheme. Using realistic Field II simulations, the proposed estimator is shown to achieve a notable performance improvement as compared to current state-of-the-art techniques.......The examination of blood flow inside the body may yield important information about vascular anomalies, such as possible indications of, for example, stenosis. Current Medical ultrasound systems suffer from only allowing for measuring the blood flow velocity along the direction of irradiation......, posing natural difficulties due to the complex behaviour of blood flow, and due to the natural orientation of most blood vessels. Recently, a transversal modulation scheme was introduced to induce also an oscillation along the transversal direction, thereby allowing for the measurement of also...
Raiche, Gilles; Blais, Jean-Guy
In a computerized adaptive test (CAT), it would be desirable to obtain an acceptable precision of the proficiency level estimate using an optimal number of items. Decreasing the number of items is accompanied, however, by a certain degree of bias when the true proficiency level differs significantly from the a priori estimate. G. Raiche (2000) has…
Adaptive Modulation with Best User Selection over Non-Identical Nakagami Fading Channels
Rao, Anlei
2012-09-08
In this paper, we analyze the performance of adaptive modulation with single-cell multiuser scheduling over independent but not identical distributed (i.n.i.d.) Nakagami fading channels. Closed-form expressions are derived for the average channel capacity, spectral efficiency, and bit-error-rate (BER) for both constant-power variable-rate and variable-power variable-rate uncoded M-ary quadrature amplitude modulation (M-QAM) schemes. We also study the impact of time delay on the average BER of adaptive M-QAM. Selected numerical results show that the multiuser diversity brings a considerably better performance even over i.n.i.d. fading environments.
Application of the Evidence Procedure to the Estimation of Wireless Channels
Directory of Open Access Journals (Sweden)
Fleury Bernard H
2007-01-01
Full Text Available We address the application of the Bayesian evidence procedure to the estimation of wireless channels. The proposed scheme is based on relevance vector machines (RVM originally proposed by M. Tipping. RVMs allow to estimate channel parameters as well as to assess the number of multipath components constituting the channel within the Bayesian framework by locally maximizing the evidence integral. We show that, in the case of channel sounding using pulse-compression techniques, it is possible to cast the channel model as a general linear model, thus allowing RVM methods to be applied. We extend the original RVM algorithm to the multiple-observation/multiple-sensor scenario by proposing a new graphical model to represent multipath components. Through the analysis of the evidence procedure we develop a thresholding algorithm that is used in estimating the number of components. We also discuss the relationship of the evidence procedure to the standard minimum description length (MDL criterion. We show that the maximum of the evidence corresponds to the minimum of the MDL criterion. The applicability of the proposed scheme is demonstrated with synthetic as well as real-world channel measurements, and a performance increase over the conventional MDL criterion applied to maximum-likelihood estimates of the channel parameters is observed.
Shanafield, Margaret; Niswonger, Richard G.; Prudic, David E.; Pohll, Greg; Susfalk, Richard; Panday, Sorab
2014-01-01
Infiltration along ephemeral channels plays an important role in groundwater recharge in arid regions. A model is presented for estimating spatial variability of seepage due to streambed heterogeneity along channels based on measurements of streamflow-front velocities in initially dry channels. The diffusion-wave approximation to the Saint-Venant equations, coupled with Philip's equation for infiltration, is connected to the groundwater model MODFLOW and is calibrated by adjusting the saturated hydraulic conductivity of the channel bed. The model is applied to portions of two large water delivery canals, which serve as proxies for natural ephemeral streams. Estimated seepage rates compare well with previously published values. Possible sources of error stem from uncertainty in Manning's roughness coefficients, soil hydraulic properties and channel geometry. Model performance would be most improved through more frequent longitudinal estimates of channel geometry and thalweg elevation, and with measurements of stream stage over time to constrain wave timing and shape. This model is a potentially valuable tool for estimating spatial variability in longitudinal seepage along intermittent and ephemeral channels over a wide range of bed slopes and the influence of seepage rates on groundwater levels.
Joint channel/frequency offset estimation and correction for coherent optical FBMC/OQAM system
Wang, Daobin; Yuan, Lihua; Lei, Jingli; wu, Gang; Li, Suoping; Ding, Runqi; Wang, Dongye
2017-12-01
In this paper, we focus on analysis of the preamble-based joint estimation for channel and laser-frequency offset (LFO) in coherent optical filter bank multicarrier systems with offset quadrature amplitude modulation (CO-FBMC/OQAM). In order to reduce the noise impact on the estimation accuracy, we proposed an estimation method based on inter-frame averaging. This method averages the cross-correlation function of real-valued pilots within multiple FBMC frames. The laser-frequency offset is estimated according to the phase of this average. After correcting LFO, the final channel response is also acquired by averaging channel estimation results within multiple frames. The principle of the proposed method is analyzed theoretically, and the preamble structure is thoroughly designed and optimized to suppress the impact of inherent imaginary interference (IMI). The effectiveness of our method is demonstrated numerically using different fiber and LFO values. The obtained results show that the proposed method can improve transmission performance significantly.
A Balanced Approach to Adaptive Probability Density Estimation
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Julio A. Kovacs
2017-04-01
Full Text Available Our development of a Fast (Mutual Information Matching (FIM of molecular dynamics time series data led us to the general problem of how to accurately estimate the probability density function of a random variable, especially in cases of very uneven samples. Here, we propose a novel Balanced Adaptive Density Estimation (BADE method that effectively optimizes the amount of smoothing at each point. To do this, BADE relies on an efficient nearest-neighbor search which results in good scaling for large data sizes. Our tests on simulated data show that BADE exhibits equal or better accuracy than existing methods, and visual tests on univariate and bivariate experimental data show that the results are also aesthetically pleasing. This is due in part to the use of a visual criterion for setting the smoothing level of the density estimate. Our results suggest that BADE offers an attractive new take on the fundamental density estimation problem in statistics. We have applied it on molecular dynamics simulations of membrane pore formation. We also expect BADE to be generally useful for low-dimensional applications in other statistical application domains such as bioinformatics, signal processing and econometrics.
A virtually blind spectrum efficient channel estimation technique for mimo-ofdm system
International Nuclear Information System (INIS)
Ullah, M.O.
2015-01-01
Multiple-Input Multiple-Output antennas in conjunction with Orthogonal Frequency-Division Multiplexing is a dominant air interface for 4G and 5G cellular communication systems. Additionally, MIMO- OFDM based air interface is the foundation for latest wireless Local Area Networks, wireless Personal Area Networks, and digital multimedia broadcasting. Whether it is a single antenna or a multi-antenna OFDM system, accurate channel estimation is required for coherent reception. Training-based channel estimation methods require multiple pilot symbols and therefore waste a significant portion of channel bandwidth. This paper describes a virtually blind spectrum efficient channel estimation scheme for MIMO-OFDM systems which operates well below the Nyquist criterion. (author)
Doppler-shift estimation of flat underwater channel using data-aided least-square approach
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Weiqiang Pan
2015-03-01
Full Text Available In this paper we proposed a dada-aided Doppler estimation method for underwater acoustic communication. The training sequence is non-dedicate, hence it can be designed for Doppler estimation as well as channel equalization. We assume the channel has been equalized and consider only flat-fading channel. First, based on the training symbols the theoretical received sequence is composed. Next the least square principle is applied to build the objective function, which minimizes the error between the composed and the actual received signal. Then an iterative approach is applied to solve the least square problem. The proposed approach involves an outer loop and inner loop, which resolve the channel gain and Doppler coefficient, respectively. The theoretical performance bound, i.e. the Cramer-Rao Lower Bound (CRLB of estimation is also derived. Computer simulations results show that the proposed algorithm achieves the CRLB in medium to high SNR cases.
Doppler-shift estimation of flat underwater channel using data-aided least-square approach
Pan, Weiqiang; Liu, Ping; Chen, Fangjiong; Ji, Fei; Feng, Jing
2015-06-01
In this paper we proposed a dada-aided Doppler estimation method for underwater acoustic communication. The training sequence is non-dedicate, hence it can be designed for Doppler estimation as well as channel equalization. We assume the channel has been equalized and consider only flat-fading channel. First, based on the training symbols the theoretical received sequence is composed. Next the least square principle is applied to build the objective function, which minimizes the error between the composed and the actual received signal. Then an iterative approach is applied to solve the least square problem. The proposed approach involves an outer loop and inner loop, which resolve the channel gain and Doppler coefficient, respectively. The theoretical performance bound, i.e. the Cramer-Rao Lower Bound (CRLB) of estimation is also derived. Computer simulations results show that the proposed algorithm achieves the CRLB in medium to high SNR cases.
Delayed-rectifier K channels contribute to contrast adaptation in mammalian retinal ganglion cells.
Weick, Michael; Demb, Jonathan B
2011-07-14
Retinal ganglion cells adapt by reducing their sensitivity during periods of high contrast. Contrast adaptation in the firing response depends on both presynaptic and intrinsic mechanisms. Here, we investigated intrinsic mechanisms for contrast adaptation in OFF Alpha ganglion cells in the in vitro guinea pig retina. Using either visual stimulation or current injection, we show that brief depolarization evoked spiking and suppressed firing during subsequent depolarization. The suppression could be explained by Na channel inactivation, as shown in salamander cells. However, brief hyperpolarization in the physiological range (5-10 mV) also suppressed firing during subsequent depolarization. This suppression was selectively sensitive to blockers of delayed-rectifier K channels (K(DR)). In somatic membrane patches, we observed tetraethylammonium-sensitive K(DR) currents that activated near -25 mV. Recovery from inactivation occurred at potentials hyperpolarized to V(rest). Brief periods of hyperpolarization apparently remove K(DR) inactivation and thereby increase the channel pool available to suppress excitability during subsequent depolarization. Copyright © 2011 Elsevier Inc. All rights reserved.
System health monitoring using multiple-model adaptive estimation techniques
Sifford, Stanley Ryan
Monitoring system health for fault detection and diagnosis by tracking system parameters concurrently with state estimates is approached using a new multiple-model adaptive estimation (MMAE) method. This novel method is called GRid-based Adaptive Parameter Estimation (GRAPE). GRAPE expands existing MMAE methods by using new techniques to sample the parameter space. GRAPE expands on MMAE with the hypothesis that sample models can be applied and resampled without relying on a predefined set of models. GRAPE is initially implemented in a linear framework using Kalman filter models. A more generalized GRAPE formulation is presented using extended Kalman filter (EKF) models to represent nonlinear systems. GRAPE can handle both time invariant and time varying systems as it is designed to track parameter changes. Two techniques are presented to generate parameter samples for the parallel filter models. The first approach is called selected grid-based stratification (SGBS). SGBS divides the parameter space into equally spaced strata. The second approach uses Latin Hypercube Sampling (LHS) to determine the parameter locations and minimize the total number of required models. LHS is particularly useful when the parameter dimensions grow. Adding more parameters does not require the model count to increase for LHS. Each resample is independent of the prior sample set other than the location of the parameter estimate. SGBS and LHS can be used for both the initial sample and subsequent resamples. Furthermore, resamples are not required to use the same technique. Both techniques are demonstrated for both linear and nonlinear frameworks. The GRAPE framework further formalizes the parameter tracking process through a general approach for nonlinear systems. These additional methods allow GRAPE to either narrow the focus to converged values within a parameter range or expand the range in the appropriate direction to track the parameters outside the current parameter range boundary
Lebaudy, Anne; Vavasseur, Alain; Hosy, Eric; Dreyer, Ingo; Leonhardt, Nathalie; Thibaud, Jean-Baptiste; Véry, Anne-Aliénor; Simonneau, Thierry; Sentenac, Hervé
2008-01-01
At least four genes encoding plasma membrane inward K+ channels (Kin channels) are expressed in Arabidopsis guard cells. A double mutant plant was engineered by disruption of a major Kin channel gene and expression of a dominant negative channel construct. Using the patch-clamp technique revealed that this mutant was totally deprived of guard cell Kin channel (GCKin) activity, providing a model to investigate the roles of this activity in the plant. GCKin activity was found to be an essential effector of stomatal opening triggered by membrane hyperpolarization and thereby of blue light-induced stomatal opening at dawn. It improved stomatal reactivity to external or internal signals (light, CO2 availability, and evaporative demand). It protected stomatal function against detrimental effects of Na+ when plants were grown in the presence of physiological concentrations of this cation, probably by enabling guard cells to selectively and rapidly take up K+ instead of Na+ during stomatal opening, thereby preventing deleterious effects of Na+ on stomatal closure. It was also shown to be a key component of the mechanisms that underlie the circadian rhythm of stomatal opening, which is known to gate stomatal responses to extracellular and intracellular signals. Finally, in a meteorological scenario with higher light intensity during the first hours of the photophase, GCKin activity was found to allow a strong increase (35%) in plant biomass production. Thus, a large diversity of approaches indicates that GCKin activity plays pleiotropic roles that crucially contribute to plant adaptation to fluctuating and stressing natural environments. PMID:18367672
Adaptive recurrence quantum entanglement distillation for two-Kraus-operator channels
Ruan, Liangzhong; Dai, Wenhan; Win, Moe Z.
2018-05-01
Quantum entanglement serves as a valuable resource for many important quantum operations. A pair of entangled qubits can be shared between two agents by first preparing a maximally entangled qubit pair at one agent, and then sending one of the qubits to the other agent through a quantum channel. In this process, the deterioration of entanglement is inevitable since the noise inherent in the channel contaminates the qubit. To address this challenge, various quantum entanglement distillation (QED) algorithms have been developed. Among them, recurrence algorithms have advantages in terms of implementability and robustness. However, the efficiency of recurrence QED algorithms has not been investigated thoroughly in the literature. This paper puts forth two recurrence QED algorithms that adapt to the quantum channel to tackle the efficiency issue. The proposed algorithms have guaranteed convergence for quantum channels with two Kraus operators, which include phase-damping and amplitude-damping channels. Analytical results show that the convergence speed of these algorithms is improved from linear to quadratic and one of the algorithms achieves the optimal speed. Numerical results confirm that the proposed algorithms significantly improve the efficiency of QED.
Directory of Open Access Journals (Sweden)
Jingbo Zhang
2018-01-01
Full Text Available In the field of cognitive radio spectrum sensing, the adaptive silence period management mechanism (ASPM has improved the problem of the low time-resource utilization rate of the traditional silence period management mechanism (TSPM. However, in the case of the low signal-to-noise ratio (SNR, the ASPM algorithm will increase the probability of missed detection for the primary user (PU. Focusing on this problem, this paper proposes an improved adaptive silence period management (IA-SPM algorithm which can adaptively adjust the sensing parameters of the current period in combination with the feedback information from the data communication with the sensing results of the previous period. The feedback information in the channel is achieved with frequency resources rather than time resources in order to adapt to the parameter change in the time-varying channel. The Monte Carlo simulation results show that the detection probability of the IA-SPM is 10–15% higher than that of the ASPM under low SNR conditions.
On-line adaptive line frequency noise cancellation from a nuclear power measuring channel
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Qadir Javed
2011-01-01
Full Text Available On-line software for adaptively canceling 50 Hz line frequency noise has been designed and tested at Pakistan Research Reactor 1. Line frequency noise causes much problem in weak signals acquisition. Sometimes this noise is so dominant that original signal is totally corrupted. Although notch filter can be used for eliminating this noise, but if signal of interest is in close vicinity of 50 Hz, then original signal is also attenuated and hence overall performance is degraded. Adaptive noise removal is a technique which could be employed for removing line frequency without degrading the desired signal. In this paper line frequency noise has been eliminated on-line from a nuclear power measuring channel. The adaptive LMS algorithm has been used to cancel 50 Hz noise. The algorithm has been implemented in labVIEW with NI 6024 data acquisition card. The quality of the acquired signal has been improved much as can be seen in experimental results.
Savaux, Vincent
2014-01-01
This book presents an algorithm for the detection of an orthogonal frequency division multiplexing (OFDM) signal in a cognitive radio context by means of a joint and iterative channel and noise estimation technique. Based on the minimum mean square criterion, it performs an accurate detection of a user in a frequency band, by achieving a quasi-optimal channel and noise variance estimation if the signal is present, and by estimating the noise level in the band if the signal is absent. Organized into three chapters, the first chapter provides the background against which the system model is pr
Minimum Mean-Square Error Single-Channel Signal Estimation
DEFF Research Database (Denmark)
Beierholm, Thomas
2008-01-01
This topic of this thesis is MMSE signal estimation for hearing aids when only one microphone is available. The research is relevant for noise reduction systems in hearing aids. To fully benefit from the amplification provided by a hearing aid, noise reduction functionality is important as hearin...... algorithm. Although performance of the two algorithms is found comparable then the particle filter algorithm is doing a much better job tracking the noise.......-impaired persons in some noisy situations need a higher signal to noise ratio for speech to be intelligible when compared to normal-hearing persons. In this thesis two different methods to approach the MMSE signal estimation problem is examined. The methods differ in the way that models for the signal and noise...... inference is performed by particle filtering. The speech model is a time-varying auto-regressive model reparameterized by formant frequencies and bandwidths. The noise is assumed non-stationary and white. Compared to the case of using the AR coefficients directly then it is found very beneficial to perform...
Fused Adaptive Lasso for Spatial and Temporal Quantile Function Estimation
Sun, Ying
2015-09-01
Quantile functions are important in characterizing the entire probability distribution of a random variable, especially when the tail of a skewed distribution is of interest. This article introduces new quantile function estimators for spatial and temporal data with a fused adaptive Lasso penalty to accommodate the dependence in space and time. This method penalizes the difference among neighboring quantiles, hence it is desirable for applications with features ordered in time or space without replicated observations. The theoretical properties are investigated and the performances of the proposed methods are evaluated by simulations. The proposed method is applied to particulate matter (PM) data from the Community Multiscale Air Quality (CMAQ) model to characterize the upper quantiles, which are crucial for studying spatial association between PM concentrations and adverse human health effects. © 2016 American Statistical Association and the American Society for Quality.
Distributed Channel Estimation and Pilot Contamination Analysis for Massive MIMO-OFDM Systems
Zaib, Alam
2016-07-22
By virtue of large antenna arrays, massive MIMO systems have a potential to yield higher spectral and energy efficiency in comparison with the conventional MIMO systems. This paper addresses uplink channel estimation in massive MIMO-OFDM systems with frequency selective channels. We propose an efficient distributed minimum mean square error (MMSE) algorithm that can achieve near optimal channel estimates at low complexity by exploiting the strong spatial correlation among antenna array elements. The proposed method involves solving a reduced dimensional MMSE problem at each antenna followed by a repetitive sharing of information through collaboration among neighboring array elements. To further enhance the channel estimates and/or reduce the number of reserved pilot tones, we propose a data-aided estimation technique that relies on finding a set of most reliable data carriers. Furthermore, we use stochastic geometry to quantify the pilot contamination, and in turn use this information to analyze the effect of pilot contamination on channel MSE. The simulation results validate our analysis and show near optimal performance of the proposed estimation algorithms.
Multiuser detection and channel estimation: Exact and approximate methods
DEFF Research Database (Denmark)
Fabricius, Thomas
2003-01-01
subtractive interference cancellation with hyperbolic tangent tentative decision device, in statistical mechanics and machine learning called the naive mean field approach. The differences between the proposed algorithms lie in how the bias is estimated/approximated. We propose approaches based on a second...... propose here to use accurate approximations borrowed from statistical mechanics and machine learning. These give us various algorithms that all can be formulated in a subtractive interference cancellation formalism. The suggested algorithms can e ectively be seen as bias corrections to standard...... of the Junction Tree Algorithm, which is a generalisation of Pearl's Belief Propagation, the BCJR, sum product, min/max sum, and Viterbi's algorithm. Although efficient algoithms, they have an inherent exponential complexity in the number of users when applied to CDMA multiuser detection. For this reason we...
ITER FW cooling by a flat channel, adapted to low flow rate and high pressure drop
International Nuclear Information System (INIS)
Ovchinnikov, I.B.; Bondarchuk, D.E.; Gervash, A.A.; Glazunov, D.A.; Komarov, A.O.; Kuznetsov, V.E.; Mazul, I.V.; Rulev, R.V.; Yablokov, N.A.
2011-01-01
Highlights: ► ITER FW cooling: pressure drop quotation must be assigned according to thermal load. ► Flat channel solutions with wide range (1:500) of hydraulic resistivity are presented. ► Simulations in Ansys CFX were carried out for presented designs. ► Usage of pressure drop quotation significantly reduces surface temperature. ► Experiments in TSEFEY-M facility confirm simulations. - Abstract: Application of hypervapotron (HV) to cool in-vessel components of ITER – divertor and first wall (FW) – is characterized by the same design load (5 MW/m 2 ) but water flow rate for FW is 8–9 times (almost by order!) less for parallel feeding elements so it seems it would be better to use other design. Several variants of a flat channel design different from HV are suggested that enable to adapt a channel to pressure quota up to 1 MPa and higher. A main feature of the suggested variants is a spiral or multi-spiral stream (flat multi spiral––FMS) that improves heat rejection and can be obtained both by exciting of such mode and forced by channel geometry. Comparison of the variants was carried out in simulations (Ansys CFX) as well as in experiments on the TSEFEY-M facility with electron-beam gun. It is shown that excitation of a spiral stream in a channel significantly reduces a temperature of a loaded surface of a channel. Miniature thermocouples were used to measure temperature near the surface.
Estimation of MIMO channel capacity from phase-noise impaired measurements
DEFF Research Database (Denmark)
Pedersen, Troels; Yin, Xuefeng; Fleury, Bernard Henri
2008-01-01
Due to the significantly reduced cost and effort for system calibration time-division multiplexing (TDM) is a commonly used technique to switch between the transmit and receive antennas in multiple-input multiple-output (MIMO) radio channel sounding. Nonetheless, Baum et al. [1], [2] have shown t...... matrix. It is shown by means of Monte Carlo simulations assuming a measurementbased phase noise model, that the MIMO channel capacity can be estimated accurately for signal to noise ratios up to about 35 dB......Due to the significantly reduced cost and effort for system calibration time-division multiplexing (TDM) is a commonly used technique to switch between the transmit and receive antennas in multiple-input multiple-output (MIMO) radio channel sounding. Nonetheless, Baum et al. [1], [2] have shown...... that phase noise of the transmitter and receiver local oscillators, when it is assumed to be a white Gaussian random process, can cause large errors of the estimated channel capacity of a low-rank MIMO channel when the standard channel matrix estimator is used. Experimental evidence shows that consecutive...
International Nuclear Information System (INIS)
Siddiqui, M.S.
1992-06-01
COFTAN is a computer code for actual estimation of flows and temperatures in the coolant channels of a pressure tube heavy water reactor. The code is being used for Candu type reactor with coolant flowing 208 channels. The simulation model first performs the detailed calculation of flux and power distribution based on two groups diffusion theory treatment on a three dimensional mesh and then channel powers, resulting from the summation of eleven bundle powers in each of the 208 channels, are employed to make actual estimation of coolant flows using channel powers and channel outlet temperature monitored by digital computers. The code by using the design flows in individual channels and applying a correction factor based on control room monitored flows in eight selected channels, can also provide a reserve computational tool of estimating individual channel outlet temperatures, thus providing an alternate arrangements for checking Rads performance. 42 figs. (Orig./A.B.)
Directory of Open Access Journals (Sweden)
Yishan He
2015-01-01
Full Text Available Fast frequency hopping (FFH is commonly used as an antijamming communication method. In this paper, we propose efficient adaptive jamming suppression schemes for binary phase shift keying (BPSK based coherent FFH system, namely, weighted equal gain combining (W-EGC with the optimum and suboptimum weighting coefficient. We analyze the bit error ratio (BER of EGC and W-EGC receivers with partial band noise jamming (PBNJ, frequency selective Rayleigh fading, and channel estimation errors. Particularly, closed-form BER expressions are presented with diversity order two. Our analysis is verified by simulations. It is shown that W-EGC receivers significantly outperform EGC. As compared to the maximum likelihood (ML receiver in conventional noncoherent frequency shift keying (FSK based FFH, coherent FFH/BPSK W-EGC receivers also show significant advantages in terms of BER. Moreover, W-EGC receivers greatly reduce the hostile jammers’ jamming efficiency.
In-vivo studies of new vector velocity and adaptive spectral estimators in medical ultrasound
DEFF Research Database (Denmark)
Hansen, Kristoffer Lindskov
2010-01-01
New ultrasound techniques for blood flow estimation have been investigated in-vivo. These are vector velocity estimators (Transverse Oscillation, Synthetic Transmit Aperture, Directional Beamforming and Plane Wave Excitation) and adaptive spectral estimators (Blood spectral Power Capon and Blood...
Preamble and pilot symbol design for channel estimation in OFDM systems with null subcarriers
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Ohno Shuichi
2011-01-01
Full Text Available Abstract In this article, design of preamble for channel estimation and pilot symbols for pilot-assisted channel estimation in orthogonal frequency division multiplexing system with null subcarriers is studied. Both the preambles and pilot symbols are designed to minimize the l 2 or the l ∞ norm of the channel estimate mean-squared errors (MSE in frequency-selective environments. We use convex optimization technique to find optimal power distribution to the preamble by casting the MSE minimization problem into a semidefinite programming problem. Then, using the designed optimal preamble as an initial value, we iteratively select the placement and optimally distribute power to the selected pilot symbols. Design examples consistent with IEEE 802.11a as well as IEEE 802.16e are provided to illustrate the superior performance of our proposed method over the equi-spaced equi-powered pilot symbols and the partially equi-spaced pilot symbols.
Dermoune, Azzouz; Simon, Eric Pierre
2017-12-01
This paper is a theoretical analysis of the maximum likelihood (ML) channel estimator for orthogonal frequency-division multiplexing (OFDM) systems in the presence of unknown interference. The following theoretical results are presented. Firstly, the uniqueness of the ML solution for practical applications, i.e., when thermal noise is present, is analytically demonstrated when the number of transmitted OFDM symbols is strictly greater than one. The ML solution is then derived from the iterative conditional ML (CML) algorithm. Secondly, it is shown that the channel estimate can be described as an algebraic function whose inputs are the initial value and the means and variances of the received samples. Thirdly, it is theoretically demonstrated that the channel estimator is not biased. The second and the third results are obtained by employing oblique projection theory. Furthermore, these results are confirmed by numerical results.
Application of a Channel Estimation Algorithm to Spectrum Sensing in a Cognitive Radio Context
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Vincent Savaux
2014-01-01
Full Text Available This paper deals with spectrum sensing in an orthogonal frequency division multiplexing (OFDM context, allowing an opportunistic user to detect a vacant spectrum resource in a licensed band. The proposed method is based on an iterative algorithm used for the joint estimation of noise variance and frequency selective channel. It can be seen as a second-order detector, since it is performed by means of the minimum mean square error criterion. The main advantage of the proposed algorithm is its capability to perform spectrum sensing, noise variance estimation, and channel estimation in the presence of a signal. Furthermore, the sensing duration is limited to only one OFDM symbol. We theoretically show the convergence of the algorithm, and we derive its analytical detection and false alarm probabilities. Furthermore, we show that the detector is very efficient, even for low SNR values, and is robust against a channel uncertainty.
A survey on OFDM channel estimation techniques based on denoising strategies
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Pallaviram Sure
2017-04-01
Full Text Available Channel estimation forms the heart of any orthogonal frequency division multiplexing (OFDM based wireless communication receiver. Frequency domain pilot aided channel estimation techniques are either least squares (LS based or minimum mean square error (MMSE based. LS based techniques are computationally less complex. Unlike MMSE ones, they do not require a priori knowledge of channel statistics (KCS. However, the mean square error (MSE performance of the channel estimator incorporating MMSE based techniques is better compared to that obtained with the incorporation of LS based techniques. To enhance the MSE performance using LS based techniques, a variety of denoising strategies have been developed in the literature, which are applied on the LS estimated channel impulse response (CIR. The advantage of denoising threshold based LS techniques is that, they do not require KCS but still render near optimal MMSE performance similar to MMSE based techniques. In this paper, a detailed survey on various existing denoising strategies, with a comparative discussion of these strategies is presented.
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Sonia Aïssa
2008-05-01
Full Text Available This paper investigates the effects of channel estimation error at the receiver on the achievable rate of distributed space-time block coded transmission. We consider that multiple transmitters cooperate to send the signal to the receiver and derive lower and upper bounds on the mutual information of distributed space-time block codes (D-STBCs when the channel gains and channel estimation error variances pertaining to different transmitter-receiver links are unequal. Then, assessing the gap between these two bounds, we provide a limiting value that upper bounds the latter at any input transmit powers, and also show that the gap is minimum if the receiver can estimate the channels of different transmitters with the same accuracy. We further investigate positioning the receiving node such that the mutual information bounds of D-STBCs and their robustness to the variations of the subchannel gains are maximum, as long as the summation of these gains is constant. Furthermore, we derive the optimum power transmission strategy to achieve the outage capacity lower bound of D-STBCs under arbitrary numbers of transmit and receive antennas, and provide closed-form expressions for this capacity metric. Numerical simulations are conducted to corroborate our analysis and quantify the effects of imperfect channel estimation.
Performance analysis of power-efficient adaptive interference cancelation in fading channels
Radaydeh, Redha Mahmoud Mesleh; Alouini, Mohamed-Slim
2010-01-01
This paper analyzes the performance of a -steering scheme for highly correlated receive antennas in the presence of statistically unordered co-channel interferers over multipath fading channels. An adaptive activation of receive antennas according to the interfering signals fading conditions is considered in the analysis. Analytical expressions for various system performance measures, including the outage probability, average error probability of different signaling schemes, and raw moments of the combined signal-to-interference-plus-noise ratio (SINR) are obtained in exact forms. Numerical and simulation results for the performance-complexity tradeoff of this scheme is presented and then compared with that of full-size arbitrary interference cancelation and no cancelation scenarios. ©2010 IEEE.
Performance analysis of power-efficient adaptive interference cancelation in fading channels
Radaydeh, Redha Mahmoud Mesleh
2010-12-01
This paper analyzes the performance of a -steering scheme for highly correlated receive antennas in the presence of statistically unordered co-channel interferers over multipath fading channels. An adaptive activation of receive antennas according to the interfering signals fading conditions is considered in the analysis. Analytical expressions for various system performance measures, including the outage probability, average error probability of different signaling schemes, and raw moments of the combined signal-to-interference-plus-noise ratio (SINR) are obtained in exact forms. Numerical and simulation results for the performance-complexity tradeoff of this scheme is presented and then compared with that of full-size arbitrary interference cancelation and no cancelation scenarios. ©2010 IEEE.
Adaptive co-channel interference cancelation for power-limited applications
Radaydeh, Redha Mahmoud Mesleh
2010-09-01
This paper proposes an adaptive co-channel interference -steering algorithm for highly correlated receive antenna channels with an aim of reducing the power consumption at the receiver. With this algorithm, the receiver activates as many antennas as necessary to maintain the residual total interference instantaneous power within a tolerable range, which can be set to guarantee a target performance level. The mode of operation does not require perfect knowledge of the statistical ordering of interfering signals instantaneous powers, which further reduces the complexity of implementation. It is shown that the arbitrary interference cancelation technique and no cancelation scenario can be studied as limiting cases of the proposed scheme. Analytical expressions for the statistics of the residual total interference instantaneous power are derived, which are then used to obtain results for the average number of active antennas and system outage performance. Numerical studies supported by simulations are presented to clarify the usefulness of the proposed scheme. ©2010 IEEE.
Rank-defective millimeter-wave channel estimation based on subspace-compressive sensing
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Majid Shakhsi Dastgahian
2016-11-01
Full Text Available Millimeter-wave communication (mmWC is considered as one of the pioneer candidates for 5G indoor and outdoor systems in E-band. To subdue the channel propagation characteristics in this band, high dimensional antenna arrays need to be deployed at both the base station (BS and mobile sets (MS. Unlike the conventional MIMO systems, Millimeter-wave (mmW systems lay away to employ the power predatory equipment such as ADC or RF chain in each branch of MIMO system because of hardware constraints. Such systems leverage to the hybrid precoding (combining architecture for downlink deployment. Because there is a large array at the transceiver, it is impossible to estimate the channel by conventional methods. This paper develops a new algorithm to estimate the mmW channel by exploiting the sparse nature of the channel. The main contribution is the representation of a sparse channel model and the exploitation of a modified approach based on Multiple Measurement Vector (MMV greedy sparse framework and subspace method of Multiple Signal Classification (MUSIC which work together to recover the indices of non-zero elements of an unknown channel matrix when the rank of the channel matrix is defected. In practical rank-defective channels, MUSIC fails, and we need to propose new extended MUSIC approaches based on subspace enhancement to compensate the limitation of MUSIC. Simulation results indicate that our proposed extended MUSIC algorithms will have proper performances and moderate computational speeds, and that they are even able to work in channels with an unknown sparsity level.
A Pilot-Pattern Based Algorithm for MIMO-OFDM Channel Estimation
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Guomin Li
2016-12-01
Full Text Available An improved pilot pattern algorithm for facilitating the channel estimation in multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM systems is proposed in this paper. The presented algorithm reconfigures the parameter in the least square (LS algorithm, which belongs to the space-time block-coded (STBC category for channel estimation in pilot-based MIMO-OFDM system. Simulation results show that the algorithm has better performance in contrast to the classical single symbol scheme. In contrast to the double symbols scheme, the proposed algorithm can achieve nearly the same performance with only half of the complexity of the double symbols scheme.
Optimal power allocation for SM-OFDM systems with imperfect channel estimation
International Nuclear Information System (INIS)
Yu, Feng; Song, Lijun; Lei, Xia; Xiao, Yue; Jiang, Zhao Xiang; Jin, Maozhu
2016-01-01
This paper analyses the bit error rate (BER) of the spatial modulation orthogonal frequency division multiplex (SM-OFDM) system and derives the optimal power allocation between the data and the pilot symbols by minimizing the upper bound for the BER operating with imperfect channel estimation. Furthermore, we prove the proposed optimal power allocation scheme applies to all generalized linear interpolation techniques with the minimum mean square error (MMSE) channel estimation . Simulation results show that employing the proposed optimal power allocation provides a substantial gain in terms of the average BER performance for the SM-OFDM system compared to its equal-power-allocation counterpart.
2014-01-01
We propose a smooth approximation l 0-norm constrained affine projection algorithm (SL0-APA) to improve the convergence speed and the steady-state error of affine projection algorithm (APA) for sparse channel estimation. The proposed algorithm ensures improved performance in terms of the convergence speed and the steady-state error via the combination of a smooth approximation l 0-norm (SL0) penalty on the coefficients into the standard APA cost function, which gives rise to a zero attractor that promotes the sparsity of the channel taps in the channel estimation and hence accelerates the convergence speed and reduces the steady-state error when the channel is sparse. The simulation results demonstrate that our proposed SL0-APA is superior to the standard APA and its sparsity-aware algorithms in terms of both the convergence speed and the steady-state behavior in a designated sparse channel. Furthermore, SL0-APA is shown to have smaller steady-state error than the previously proposed sparsity-aware algorithms when the number of nonzero taps in the sparse channel increases. PMID:24790588
Channel Equalization and Phase Estimation for Reduced-Guard-Interval CO-OFDM Systems
Zhuge, Qunbi
Reduced-guard-interval (RGI) coherent optical (CO) orthogonal frequency-division multiplexing (OFDM) is a potential candidate for next generation 100G beyond optical transports, attributed to its advantages such as high spectral efficiency and high tolerance to optical channel impairments. First of all, we review the coherent optical systems with an emphasis on CO-OFDM systems as well as the optical channel impairments and the general digital signal processing techniques to combat them. This work focuses on the channel equalization and phase estimation of RGI CO-OFDM systems. We first propose a novel equalization scheme based on the equalization structure of RGI CO-OFDM to reduce the cyclic prefix overhead to zero. Then we show that intra-channel nonlinearities should be considered when designing the training symbols for channel estimation. Afterwards, we propose and analyze the phenomenon of dispersion-enhanced phase noise (DEPN) caused by the interaction between the laser phase noise and the chromatic dispersion in RGI CO-OFDM transmissions. DEPN induces a non-negligible performance degradation and limits the tolerant laser linewidth. However, it can be compensated by the grouped maximum-likelihood phase estimation proposed in this work.
PERFORMANCE ANALYSIS OF PILOT BASED CHANNEL ESTIMATION TECHNIQUES IN MB OFDM SYSTEMS
Directory of Open Access Journals (Sweden)
M. Madheswaran
2011-12-01
Full Text Available Ultra wideband (UWB communication is mainly used for short range of communication in wireless personal area networks. Orthogonal Frequency Division Multiplexing (OFDM is being used as a key physical layer technology for Fourth Generation (4G wireless communication. OFDM based communication gives high spectral efficiency and mitigates Inter-symbol Interference (ISI in a wireless medium. In this paper the IEEE 802.15.3a based Multiband OFDM (MB OFDM system is considered. The pilot based channel estimation techniques are considered to analyze the performance of MB OFDM systems over Liner Time Invariant (LTI Channel models. In this paper, pilot based Least Square (LS and Least Minimum Mean Square Error (LMMSE channel estimation technique has been considered for UWB OFDM system. In the proposed method, the estimated Channel Impulse Responses (CIRs are filtered in the time domain for the consideration of the channel delay spread. Also the performance of proposed system has been analyzed for different modulation techniques for various pilot density patterns.
Khan, Fahd Ahmed
2012-04-01
New coherent receivers are derived for a pilot-symbol-aided distributed space-time block-coded system with imperfect channel state information which do not perform channel estimation at the destination by using the received pilot signals directly for decoding. The derived receivers are based on new metrics that use distribution of the channels and the noise to achieve improved symbol-error-rate (SER) performance. The SER performance of the derived receivers is further improved by utilizing the decision history in the receivers. The decision history is also incorporated in the existing Euclidean metric to improve its performance. Simulation results show that, for 16-quadrature-amplitude-modulation in a Rayleigh fading channel, a performance gain of up to 2.5 dB can be achieved for the new receivers compared with the conventional mismatched coherent receiver. © 2012 IEEE.
Basis expansion model for channel estimation in LTE-R communication system
Directory of Open Access Journals (Sweden)
Ling Deng
2016-05-01
Full Text Available This paper investigates fast time-varying channel estimation in LTE-R communication systems. The Basis Expansion Model (BEM is adopted to fit the fast time-varying channel in a high-speed railway communication scenario. The channel impulse response is modeled as the sum of basis functions multiplied by different coefficients. The optimal coefficients are obtained by theoretical analysis. Simulation results show that a Generalized Complex-Exponential BEM (GCE-BEM outperforms a Complex-Exponential BEM (CE-BEM and a polynomial BEM in terms of Mean Squared Error (MSE. Besides, the MSE of the CE-BEM decreases gradually as the number of basis functions increases. The GCE-BEM has a satisfactory performance with the serious fading channel.
Aarthi, G.; Ramachandra Reddy, G.
2018-03-01
In our paper, the impact of adaptive transmission schemes: (i) optimal rate adaptation (ORA) and (ii) channel inversion with fixed rate (CIFR) on the average spectral efficiency (ASE) are explored for free-space optical (FSO) communications with On-Off Keying (OOK), Polarization shift keying (POLSK), and Coherent optical wireless communication (Coherent OWC) systems under different turbulence regimes. Further to enhance the ASE we have incorporated aperture averaging effects along with the above adaptive schemes. The results indicate that ORA adaptation scheme has the advantage of improving the ASE performance compared with CIFR under moderate and strong turbulence regime. The coherent OWC system with ORA excels the other modulation schemes and could achieve ASE performance of 49.8 bits/s/Hz at the average transmitted optical power of 6 dBm under strong turbulence. By adding aperture averaging effect we could achieve an ASE of 50.5 bits/s/Hz under the same conditions. This makes ORA with Coherent OWC modulation as a favorable candidate for improving the ASE of the FSO communication system.
Digital baseline estimation method for multi-channel pulse height analyzing
International Nuclear Information System (INIS)
Xiao Wuyun; Wei Yixiang; Ai Xianyun
2005-01-01
The basic features of digital baseline estimation for multi-channel pulse height analysis are introduced. The weight-function of minimum-noise baseline filter is deduced with functional variational calculus. The frequency response of this filter is also deduced with Fourier transformation, and the influence of parameters on amplitude frequency response characteristics is discussed. With MATLAB software, the noise voltage signal from the charge sensitive preamplifier is simulated, and the processing effect of minimum-noise digital baseline estimation is verified. According to the results of this research, digital baseline estimation method can estimate baseline optimally, and it is very suitable to be used in digital multi-channel pulse height analysis. (authors)
DEFF Research Database (Denmark)
Shutin, Dmitriy; Fleury, Bernard Henri
2011-01-01
In this paper, we develop a sparse variational Bayesian (VB) extension of the space-alternating generalized expectation-maximization (SAGE) algorithm for the high resolution estimation of the parameters of relevant multipath components in the response of frequency and spatially selective wireless...... channels. The application context of the algorithm considered in this contribution is parameter estimation from channel sounding measurements for radio channel modeling purpose. The new sparse VB-SAGE algorithm extends the classical SAGE algorithm in two respects: i) by monotonically minimizing...... parametric sparsity priors for the weights of the multipath components. We revisit the Gaussian sparsity priors within the sparse VB-SAGE framework and extend the results by considering Laplace priors. The structure of the VB-SAGE algorithm allows for an analytical stability analysis of the update expression...
Capacity estimation and verification of quantum channels with arbitrarily correlated errors.
Pfister, Corsin; Rol, M Adriaan; Mantri, Atul; Tomamichel, Marco; Wehner, Stephanie
2018-01-02
The central figure of merit for quantum memories and quantum communication devices is their capacity to store and transmit quantum information. Here, we present a protocol that estimates a lower bound on a channel's quantum capacity, even when there are arbitrarily correlated errors. One application of these protocols is to test the performance of quantum repeaters for transmitting quantum information. Our protocol is easy to implement and comes in two versions. The first estimates the one-shot quantum capacity by preparing and measuring in two different bases, where all involved qubits are used as test qubits. The second verifies on-the-fly that a channel's one-shot quantum capacity exceeds a minimal tolerated value while storing or communicating data. We discuss the performance using simple examples, such as the dephasing channel for which our method is asymptotically optimal. Finally, we apply our method to a superconducting qubit in experiment.
Kojima, Yohei; Takeda, Kazuaki; Adachi, Fumiyuki
Frequency-domain equalization (FDE) based on the minimum mean square error (MMSE) criterion can provide better downlink bit error rate (BER) performance of direct sequence code division multiple access (DS-CDMA) than the conventional rake combining in a frequency-selective fading channel. FDE requires accurate channel estimation. In this paper, we propose a new 2-step maximum likelihood channel estimation (MLCE) for DS-CDMA with FDE in a very slow frequency-selective fading environment. The 1st step uses the conventional pilot-assisted MMSE-CE and the 2nd step carries out the MLCE using decision feedback from the 1st step. The BER performance improvement achieved by 2-step MLCE over pilot assisted MMSE-CE is confirmed by computer simulation.
Directory of Open Access Journals (Sweden)
Yang Lie-Liang
2005-01-01
Full Text Available In this contribution, the performance of wideband code-division multiple-access (W-CDMA systems using space-time-spreading- (STS- based transmit diversity is investigated, when frequency-selective Nakagami- fading channels, multiuser interference, and background noise are considered. The analysis and numerical results suggest that the achievable diversity order is the product of the frequency-selective diversity order and the transmit diversity order. Furthermore, both the transmit diversity and the frequency-selective diversity have the same order of importance. Since W-CDMA signals are subjected to frequency-selective fading, the number of resolvable paths at the receiver may vary over a wide range depending on the transmission environment encountered. It can be shown that, for wireless channels where the frequency selectivity is sufficiently high, transmit diversity may be not necessitated. Under this case, multiple transmission antennas can be leveraged into an increased bitrate. Therefore, an adaptive STS-based transmission scheme is then proposed for improving the throughput of W-CDMA systems. Our numerical results demonstrate that this adaptive STS-based transmission scheme is capable of significantly improving the effective throughput of W-CDMA systems. Specifically, the studied W-CDMA system's bitrate can be increased by a factor of three at the modest cost of requiring an extra 0.4 dB or 1.2 dB transmitted power in the context of the investigated urban or suburban areas, respectively.
The split symbol moments SNR estimator in narrow-band channels
Shah, Biren; Hinedi, Sami
1990-01-01
The split symbol moments estimator is an algorithm that is designed to estimate symbol SNR in the presence of additive white Gaussian noise. The performance of the algorithm in band-limited channels is examined, and the effects of the resulting intersymbol interference are quantified. All results obtained are in closed form and can be easily evaluated numerically for performance-prediction purposes. The results are also validated through digital simulations.
On the BER and capacity analysis of MIMO MRC systems with channel estimation error
Yang, Liang; Alouini, Mohamed-Slim
2011-01-01
In this paper, we investigate the effect of channel estimation error on the capacity and bit-error rate (BER) of a multiple-input multiple-output (MIMO) transmit maximal ratio transmission (MRT) and receive maximal ratio combining (MRC) systems over
Low Complexity Iterative Joint Channel Estimation and Multiuser Detection for DS-CDMA
DEFF Research Database (Denmark)
Christensen, Søren Skovgård; Kocian, Alexander; Fleury, Bernard Henri
2004-01-01
Previously the SAGE algorithm was applied to sub-optimal yet efficient Joint data Detection and channel Estimation (JDE) for DS-CDMA of moderate time complexity. Modifying the expectation and maximization steps of the SAGE-JDE scheme, it is possible to obtain an efficient receiver architecture...
Channel estimation in DFT-based offset-QAM OFDM systems.
Zhao, Jian
2014-10-20
Offset quadrature amplitude modulation (offset-QAM) orthogonal frequency division multiplexing (OFDM) exhibits enhanced net data rates compared to conventional OFDM, and reduced complexity compared to Nyquist FDM (N-FDM). However, channel estimation in discrete-Fourier-transform (DFT) based offset-QAM OFDM is different from that in conventional OFDM and requires particular study. In this paper, we derive a closed-form expression for the demultiplexed signal in DFT-based offset-QAM systems and show that although the residual crosstalk is orthogonal to the decoded signal, its existence degrades the channel estimation performance when the conventional least-square method is applied. We propose and investigate four channel estimation algorithms for offset-QAM OFDM that vary in terms of performance, complexity, and tolerance to system parameters. It is theoretically and experimentally shown that simple channel estimation can be realized in offset-QAM OFDM with the achieved performance close to the theoretical limit. This, together with the existing advantages over conventional OFDM and N-FDM, makes this technology very promising for optical communication systems.
DEFF Research Database (Denmark)
Pittalà, Fabio; Msallem, Majdi; Hauske, Fabian N.
2012-01-01
We propose a non-weighted feed-forward equalization method with filter update by averaging channel estimations based on short CAZAC sequences. Three averaging methods are presented and tested by simulations in a time-varying 2×2 MIMO optical system....
Estimation and Mitigation of Channel Non-Reciprocity in Massive MIMO
Raeesi, Orod; Gokceoglu, Ahmet; Valkama, Mikko
2018-05-01
Time-division duplex (TDD) based massive MIMO systems rely on the reciprocity of the wireless propagation channels when calculating the downlink precoders based on uplink pilots. However, the effective uplink and downlink channels incorporating the analog radio front-ends of the base station (BS) and user equipments (UEs) exhibit non-reciprocity due to non-identical behavior of the individual transmit and receive chains. When downlink precoder is not aware of such channel non-reciprocity (NRC), system performance can be significantly degraded due to NRC induced interference terms. In this work, we consider a general TDD-based massive MIMO system where frequency-response mismatches at both the BS and UEs, as well as the mutual coupling mismatch at the BS large-array system all coexist and induce channel NRC. Based on the NRC-impaired signal models, we first propose a novel iterative estimation method for acquiring both the BS and UE side NRC matrices and then also propose a novel NRC-aware downlink precoder design which utilizes the obtained estimates. Furthermore, an efficient pilot signaling scheme between the BS and UEs is introduced in order to facilitate executing the proposed estimation method and the NRC-aware precoding technique in practical systems. Comprehensive numerical results indicate substantially improved spectral efficiency performance when the proposed NRC estimation and NRC-aware precoding methods are adopted, compared to the existing state-of-the-art methods.
He, Hao; Wang, Jun; Zhu, Jiang; Li, Shaoqian
2010-12-01
In this paper, we investigate the cross-layer design of joint channel access and transmission rate adaptation in CR networks with multiple channels for both centralized and decentralized cases. Our target is to maximize the throughput of CR network under transmission power constraint by taking spectrum sensing errors into account. In centralized case, this problem is formulated as a special constrained Markov decision process (CMDP), which can be solved by standard linear programming (LP) method. As the complexity of finding the optimal policy by LP increases exponentially with the size of action space and state space, we further apply action set reduction and state aggregation to reduce the complexity without loss of optimality. Meanwhile, for the convenience of implementation, we also consider the pure policy design and analyze the corresponding characteristics. In decentralized case, where only local information is available and there is no coordination among the CR users, we prove the existence of the constrained Nash equilibrium and obtain the optimal decentralized policy. Finally, in the case that the traffic load parameters of the licensed users are unknown for the CR users, we propose two methods to estimate the parameters for two different cases. Numerical results validate the theoretic analysis.
Directory of Open Access Journals (Sweden)
Jiang Zhu
2010-01-01
Full Text Available In this paper, we investigate the cross-layer design of joint channel access and transmission rate adaptation in CR networks with multiple channels for both centralized and decentralized cases. Our target is to maximize the throughput of CR network under transmission power constraint by taking spectrum sensing errors into account. In centralized case, this problem is formulated as a special constrained Markov decision process (CMDP, which can be solved by standard linear programming (LP method. As the complexity of finding the optimal policy by LP increases exponentially with the size of action space and state space, we further apply action set reduction and state aggregation to reduce the complexity without loss of optimality. Meanwhile, for the convenience of implementation, we also consider the pure policy design and analyze the corresponding characteristics. In decentralized case, where only local information is available and there is no coordination among the CR users, we prove the existence of the constrained Nash equilibrium and obtain the optimal decentralized policy. Finally, in the case that the traffic load parameters of the licensed users are unknown for the CR users, we propose two methods to estimate the parameters for two different cases. Numerical results validate the theoretic analysis.
DEFF Research Database (Denmark)
Kock, Anders Bredahl; Callot, Laurent
We show that the adaptive Lasso (aLasso) and the adaptive group Lasso (agLasso) are oracle efficient in stationary vector autoregressions where the number of parameters per equation is smaller than the number of observations. In particular, this means that the parameters are estimated consistently...
Low-sampling-rate ultra-wideband channel estimation using a bounded-data-uncertainty approach
Ballal, Tarig
2014-01-01
This paper proposes a low-sampling-rate scheme for ultra-wideband channel estimation. In the proposed scheme, P pulses are transmitted to produce P observations. These observations are exploited to produce channel impulse response estimates at a desired sampling rate, while the ADC operates at a rate that is P times less. To avoid loss of fidelity, the interpulse interval, given in units of sampling periods of the desired rate, is restricted to be co-prime with P. This condition is affected when clock drift is present and the transmitted pulse locations change. To handle this situation and to achieve good performance without using prior information, we derive an improved estimator based on the bounded data uncertainty (BDU) model. This estimator is shown to be related to the Bayesian linear minimum mean squared error (LMMSE) estimator. The performance of the proposed sub-sampling scheme was tested in conjunction with the new estimator. It is shown that high reduction in sampling rate can be achieved. The proposed estimator outperforms the least squares estimator in most cases; while in the high SNR regime, it also outperforms the LMMSE estimator. © 2014 IEEE.
Energy Technology Data Exchange (ETDEWEB)
Ben Youssef, C; Dahhou, B; Roux, G [Centre National de la Recherche Scientifique (CNRS), 31 - Toulouse (France); Rols, J L [Institut National des Sciences Appliquees (INSA), 31 - Toulouse (France)
1996-12-31
Controlling the process of a fixed bed bioreactor imply solving filtering and adaptative control problems. Estimation processes have been developed for unmeasurable parameters. An adaptative non linear control has been built, instead of conventional approaches trying to linearize the system and apply a linear control system. (D.L.) 10 refs.
Bruning, Eric C.; Thomas, Ronald J.; Krehbiel, Paul R.; Rison, William; Carey, Larry D.; Koshak, William; Peterson, Harold; MacGorman, Donald R.
2013-01-01
We will use VHF Lightning Mapping Array data to estimate NOx per flash and per unit channel length, including the vertical distribution of channel length. What s the best way to find channel length from VHF sources? This paper presents the rationale for the fractal method, which is closely related to the box-covering method.
Joint Symbol Timing and CFO Estimation for OFDM/OQAM Systems in Multipath Channels
Directory of Open Access Journals (Sweden)
Petrella Angelo
2010-01-01
Full Text Available The problem of data-aided synchronization for orthogonal frequency division multiplexing (OFDM systems based on offset quadrature amplitude modulation (OQAM in multipath channels is considered. In particular, the joint maximum-likelihood (ML estimator for carrier-frequency offset (CFO, amplitudes, phases, and delays, exploiting a short known preamble, is derived. The ML estimators for phases and amplitudes are in closed form. Moreover, under the assumption that the CFO is sufficiently small, a closed form approximate ML (AML CFO estimator is obtained. By exploiting the obtained closed form solutions a cost function whose peaks provide an estimate of the delays is derived. In particular, the symbol timing (i.e., the delay of the first multipath component is obtained by considering the smallest estimated delay. The performance of the proposed joint AML estimator is assessed via computer simulations and compared with that achieved by the joint AML estimator designed for AWGN channel and that achieved by a previously derived joint estimator for OFDM systems.
Sparse Channel Estimation Including the Impact of the Transceiver Filters with Application to OFDM
DEFF Research Database (Denmark)
Barbu, Oana-Elena; Pedersen, Niels Lovmand; Manchón, Carles Navarro
2014-01-01
Traditionally, the dictionary matrices used in sparse wireless channel estimation have been based on the discrete Fourier transform, following the assumption that the channel frequency response (CFR) can be approximated as a linear combination of a small number of multipath components, each one......) and receive (demodulation) filters. Hence, the assumption of the CFR being sparse in the canonical Fourier dictionary may no longer hold. In this work, we derive a signal model and subsequently a novel dictionary matrix for sparse estimation that account for the impact of transceiver filters. Numerical...... results obtained in an OFDM transmission scenario demonstrate the superior accuracy of a sparse estimator that uses our proposed dictionary rather than the classical Fourier dictionary, and its robustness against a mismatch in the assumed transmit filter characteristics....
Extended Kalman Filter Channel Estimation for Line-of-Sight Detection in WCDMA Mobile Positioning
Directory of Open Access Journals (Sweden)
Abdelmonaem Lakhzouri
2003-12-01
Full Text Available In mobile positioning, it is very important to estimate correctly the delay between the transmitter and the receiver. When the receiver is in line-of-sight (LOS condition with the transmitter, the computation of the mobile position in two dimensions becomes straightforward. In this paper, the problem of LOS detection in WCDMA for mobile positioning is considered, together with joint estimation of the delays and channel coefficients. These are very challenging topics in multipath fading channels because LOS component is not always present, and when it is present, it might be severely affected by interfering paths spaced at less than one chip distance (closely spaced paths. The extended Kalman filter (EKF is used to estimate jointly the delays and complex channel coefficients. The decision whether the LOS component is present or not is based on statistical tests to determine the distribution of the channel coefficient corresponding to the first path. The statistical test-based techniques are practical, simple, and of low computation complexity, which is suitable for WCDMA receivers. These techniques can provide an accurate decision whether LOS component is present or not.
Efficient optimal joint channel estimation and data detection for massive MIMO systems
Alshamary, Haider Ali Jasim
2016-08-15
In this paper, we propose an efficient optimal joint channel estimation and data detection algorithm for massive MIMO wireless systems. Our algorithm is optimal in terms of the generalized likelihood ratio test (GLRT). For massive MIMO systems, we show that the expected complexity of our algorithm grows polynomially in the channel coherence time. Simulation results demonstrate significant performance gains of our algorithm compared with suboptimal non-coherent detection algorithms. To the best of our knowledge, this is the first algorithm which efficiently achieves GLRT-optimal non-coherent detections for massive MIMO systems with general constellations.
Adaptive single-antenna transmit selection with interference suppression
Radaydeh, Redha Mahmoud Mesleh; Alouini, Mohamed-Slim
2011-01-01
-efficient transmission with as low transmit channel estimations as possible. Due to the fact that the number of active co-channel interfering signals and their corresponding powers experience random behavior, the adaptation to channels conditions, assuming uniform buffer
Maximum Likelihood Blind Channel Estimation for Space-Time Coding Systems
Directory of Open Access Journals (Sweden)
Hakan A. Çırpan
2002-05-01
Full Text Available Sophisticated signal processing techniques have to be developed for capacity enhancement of future wireless communication systems. In recent years, space-time coding is proposed to provide significant capacity gains over the traditional communication systems in fading wireless channels. Space-time codes are obtained by combining channel coding, modulation, transmit diversity, and optional receive diversity in order to provide diversity at the receiver and coding gain without sacrificing the bandwidth. In this paper, we consider the problem of blind estimation of space-time coded signals along with the channel parameters. Both conditional and unconditional maximum likelihood approaches are developed and iterative solutions are proposed. The conditional maximum likelihood algorithm is based on iterative least squares with projection whereas the unconditional maximum likelihood approach is developed by means of finite state Markov process modelling. The performance analysis issues of the proposed methods are studied. Finally, some simulation results are presented.
Estimation of Channel-Forming Discharge and Large-Event Geomorphic Response Using HEC-RAS
Hamilton, P.; Strom, K.; Hosseiny, S. M. H.
2015-12-01
The goal of the present work was to consider the functionality and applicability of HEC-RAS sediment transport simulations in two situations. The first was as a mode for obtaining quick estimates of the effective discharge, one measure of channel-forming discharge, and the second was as a mode to quickly estimate sediment transport and the commensurate potential erosion and deposition during large flood events. Though there are many other sediment transport and morphodynamic models available, e.g., CCHE1D, Nays2DH, we were interested in using HEC-RAS since this is the model of choice for many regulatory bodies, e.g., FEMA, cities, and counties. This makes using the sediment transport capability of HEC-RAS a natural extension of models that already otherwise exist and are well calibrated. In first looking at the utility of these models, we wanted to estimate the effective discharge of streams. Effective discharge is one way of defining the channel-forming discharge for a stream and is therefore an important parameter in natural channel design and restoration efforts. By running this range of floods, one can easily obtain an estimate for recurrence interval most responsible for moving the majority of sediment over a long time period. Results were compared to data collected within our research group on the Brazos River (TX). Effective discharge is an important estimate, particularly in understanding the equilibrium channel condition. Nevertheless, large floods are contemporaneously catastrophic and understanding their potential effects is desirable. Finally, we performed some sensitivity analysis to better understand the underlying assumptions of the various sediment transport model options and how they might affect the outcome of the aforementioned computations.
Fault Adaptive Control of Overactuated Systems Using Prognostic Estimation
National Aeronautics and Space Administration — Most fault adaptive control research addresses the preservation of system stability or functionality in the presence of a specific failure (fault). This paper...
Fused Adaptive Lasso for Spatial and Temporal Quantile Function Estimation
Sun, Ying; Wang, Huixia J.; Fuentes, Montserrat
2015-01-01
and temporal data with a fused adaptive Lasso penalty to accommodate the dependence in space and time. This method penalizes the difference among neighboring quantiles, hence it is desirable for applications with features ordered in time or space without
Carrier frequency offset estimation for an acoustic-electric channel using 16 QAM modulation
Cunningham, Michael T.; Anderson, Leonard A.; Wilt, Kyle R.; Chakraborty, Soumya; Saulnier, Gary J.; Scarton, Henry A.
2016-05-01
Acoustic-electric channels can be used to send data through metallic barriers, enabling communications where electromagnetic signals are ineffective. This paper considers an acoustic-electric channel that is formed by mounting piezoelectric transducers on metallic barriers that are separated by a thin water layer. The transducers are coupled to the barriers using epoxy and the barriers are positioned to axially-align the PZTs, maximizing energy transfer efficiency. The electrical signals are converted by the transmitting transducers into acoustic waves, which propagate through the elastic walls and water medium to the receiving transducers. The reverberation of the acoustic signals in these channels can produce multipath distortion with a significant delay spread that introduces inter-symbol interference (ISI) into the received signal. While the multipath effects can be severe, the channel does not change rapidly which makes equalization easier. Here we implement a 16-QAM system on this channel, including a method for obtaining accurate carrier frequency offset (CFO) estimates in the presence of the quasi-static multipath propagation. A raised-power approach is considered but found to suffer from excessive data noise resulting from the ISI. An alternative approach that utilizes a pilot tone burst at the start of a data packet is used for CFO estimation and found to be effective. The autocorrelation method is used to estimate the frequency of the received burst. A real-time prototype of the 16 QAM system that uses a Texas Instruments MSP430 microcontroller-based transmitter and a personal computer-based receiver is presented along with performance results.
Real-time image dehazing using local adaptive neighborhoods and dark-channel-prior
Valderrama, Jesus A.; Díaz-Ramírez, Víctor H.; Kober, Vitaly; Hernandez, Enrique
2015-09-01
A real-time algorithm for single image dehazing is presented. The algorithm is based on calculation of local neighborhoods of a hazed image inside a moving window. The local neighborhoods are constructed by computing rank-order statistics. Next the dark-channel-prior approach is applied to the local neighborhoods to estimate the transmission function of the scene. By using the suggested approach there is no need for applying a refining algorithm to the estimated transmission such as the soft matting algorithm. To achieve high-rate signal processing the proposed algorithm is implemented exploiting massive parallelism on a graphics processing unit (GPU). Computer simulation results are carried out to test the performance of the proposed algorithm in terms of dehazing efficiency and speed of processing. These tests are performed using several synthetic and real images. The obtained results are analyzed and compared with those obtained with existing dehazing algorithms.
Energy Technology Data Exchange (ETDEWEB)
Eldred, Michael Scott; Subia, Samuel Ramirez; Neckels, David; Hopkins, Matthew Morgan; Notz, Patrick K.; Adams, Brian M.; Carnes, Brian; Wittwer, Jonathan W.; Bichon, Barron J.; Copps, Kevin D.
2006-10-01
This report documents the results for an FY06 ASC Algorithms Level 2 milestone combining error estimation and adaptivity, uncertainty quantification, and probabilistic design capabilities applied to the analysis and design of bistable MEMS. Through the use of error estimation and adaptive mesh refinement, solution verification can be performed in an automated and parameter-adaptive manner. The resulting uncertainty analysis and probabilistic design studies are shown to be more accurate, efficient, reliable, and convenient.
An Off-Grid Turbo Channel Estimation Algorithm for Millimeter Wave Communications
Directory of Open Access Journals (Sweden)
Lingyi Han
2016-09-01
Full Text Available The bandwidth shortage has motivated the exploration of the millimeter wave (mmWave frequency spectrum for future communication networks. To compensate for the severe propagation attenuation in the mmWave band, massive antenna arrays can be adopted at both the transmitter and receiver to provide large array gains via directional beamforming. To achieve such array gains, channel estimation (CE with high resolution and low latency is of great importance for mmWave communications. However, classic super-resolution subspace CE methods such as multiple signal classification (MUSIC and estimation of signal parameters via rotation invariant technique (ESPRIT cannot be applied here due to RF chain constraints. In this paper, an enhanced CE algorithm is developed for the off-grid problem when quantizing the angles of mmWave channel in the spatial domain where off-grid problem refers to the scenario that angles do not lie on the quantization grids with high probability, and it results in power leakage and severe reduction of the CE performance. A new model is first proposed to formulate the off-grid problem. The new model divides the continuously-distributed angle into a quantized discrete grid part, referred to as the integral grid angle, and an offset part, termed fractional off-grid angle. Accordingly, an iterative off-grid turbo CE (IOTCE algorithm is proposed to renew and upgrade the CE between the integral grid part and the fractional off-grid part under the Turbo principle. By fully exploiting the sparse structure of mmWave channels, the integral grid part is estimated by a soft-decoding based compressed sensing (CS method called improved turbo compressed channel sensing (ITCCS. It iteratively updates the soft information between the linear minimum mean square error (LMMSE estimator and the sparsity combiner. Monte Carlo simulations are presented to evaluate the performance of the proposed method, and the results show that it enhances the angle
Simulation of devices mobility to estimate wireless channel quality metrics in 5G networks
Orlov, Yu.; Fedorov, S.; Samuylov, A.; Gaidamaka, Yu.; Molchanov, D.
2017-07-01
The problem of channel quality estimation for devices in a wireless 5G network is formulated. As a performance metrics of interest we choose the signal-to-interference-plus-noise ratio, which depends essentially on the distance between the communicating devices. A model with a plurality of moving devices in a bounded three-dimensional space and a simulation algorithm to determine the distances between the devices for a given motion model are devised.
Optimal Superimposed Training Sequences for Channel Estimation in MIMO-OFDM Systems
Directory of Open Access Journals (Sweden)
Ratnam V. Raja Kumar
2010-01-01
Full Text Available In this work an iterative time domain Least Squares (LS based channel estimation method using superimposed training (ST for a Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM system over time varying frequency selective fading channels is proposed. The performance of the channel estimator is analyzed in terms of the Mean Square Estimation Error (MSEE and its impact on the uncoded Bit Error Rate (BER of the MIMO-OFDM system is studied. A new selection criterion for the training sequences that jointly optimizes the MSEE and the BER of the OFDM system is proposed. Chirp based sequences are proposed and shown to satisfy the same. These are compared with the other sequences proposed in the literature and are found to yield a superior performance. The sequences, one for each transmitting antenna, offers fairness through providing equal interference in all the data carriers unlike earlier proposals. The effectiveness of the mathematical analysis presented is demonstrated through a comparison with the simulation studies. Experimental studies are carried out to study and validate the improved performance of the proposed scheme. The scheme is applied to the IEEE 802.16e OFDM standard and a case is made with the required design of the sequence.
Directory of Open Access Journals (Sweden)
Stefan Berger
2010-01-01
Full Text Available Channel estimation protocols for wireless two-hop networks with amplify-and-forward (AF relays are compared. We consider multiuser relaying networks, where the gain factors are chosen such that the signals from all relays add up coherently at the destinations. While the destinations require channel knowledge in order to decode, our focus lies on the channel estimates that are used to calculate the relay gains. Since knowledge of the compound two-hop channels is generally not sufficient to do this, the protocols considered here measure all single-hop coefficients in the network. We start from the observation that the direction in which the channels are measured determines (1 the number of channel uses required to estimate all coefficient and (2 the need for global carrier phase reference. Four protocols are identified that differ in the direction in which the first-hop and the second-hop channels are measured. We derive a sensible measure for the accuracy of the channel estimates in the presence of additive noise and phase noise and compare the protocols based on this measure. Finally, we provide a quantitative performance comparison for a simple single-user application example. It is important to note that the results can be used to compare the channel estimation protocols for any two-hop network configuration and gain allocation scheme.
A qualitative assessment of climate adaptation options and some estimates of adaptation costs
International Nuclear Information System (INIS)
Van Ierland, E.C.; De Bruin, K.; Dellink, R.B.; Ruijs, A.
2006-12-01
The Routeplanner project aims to provide a 'systematic assessment' of potential adaptation options to respond to climate change in the Netherlands in connection to spatial planning. The study is the result of a policy oriented project that took place between May and September 2006. The aim of the current study is to provide a 'qualitative assessment' of the direct and indirect effects of adaptation options and to provide an assessment of some of the costs and benefits of adaptation options. The present report presents and summarizes the results of all phases of the study: an inventory of adaptation options, a qualitative assessment of the effects of the adaptation options for the Netherlands in the long run, a database which allows to rank the various options according to a set of criteria and a relative ranking on the basis of these criteria. Finally, the report also contains the best available information on costs and benefits of various adaptation options.
Adaptive Flight Envelope Estimation and Protection, Phase I
National Aeronautics and Space Administration — Impact Technologies, in collaboration with the Georgia Institute of Technology, proposes to develop and demonstrate an innovative flight envelope estimation and...
Forecasting the international diffusion of innovations: An adaptive estimation approach
Y.M. van Everdingen (Yvonne); W.B. Aghina (Wouter)
2003-01-01
textabstractWe introduce an international, adaptive diffusion model that can be used to forecast the cross-national diffusion of an innovation at early stages of the diffusion curve. We model the mutual influence between the diffusion processes in the different social systems (countries) by mixing
Chabdarov, Shamil M.; Nadeev, Adel F.; Chickrin, Dmitry E.; Faizullin, Rashid R.
2011-04-01
In this paper we discuss unconventional detection technique also known as «full resolution receiver». This receiver uses Gaussian probability mixtures for interference structure adaptation. Full resolution receiver is alternative to conventional matched filter receivers in the case of non-Gaussian interferences. For the DS-CDMA forward channel with presence of complex interferences sufficient performance increasing was shown.
Space-Time Coded MC-CDMA: Blind Channel Estimation, Identifiability, and Receiver Design
Directory of Open Access Journals (Sweden)
Li Hongbin
2002-01-01
Full Text Available Integrating the strengths of multicarrier (MC modulation and code division multiple access (CDMA, MC-CDMA systems are of great interest for future broadband transmissions. This paper considers the problem of channel identification and signal combining/detection schemes for MC-CDMA systems equipped with multiple transmit antennas and space-time (ST coding. In particular, a subspace based blind channel identification algorithm is presented. Identifiability conditions are examined and specified which guarantee unique and perfect (up to a scalar channel estimation when knowledge of the noise subspace is available. Several popular single-user based signal combining schemes, namely the maximum ratio combining (MRC and the equal gain combining (EGC, which are often utilized in conventional single-transmit-antenna based MC-CDMA systems, are extended to the current ST-coded MC-CDMA (STC-MC-CDMA system to perform joint combining and decoding. In addition, a linear multiuser minimum mean-squared error (MMSE detection scheme is also presented, which is shown to outperform the MRC and EGC at some increased computational complexity. Numerical examples are presented to evaluate and compare the proposed channel identification and signal detection/combining techniques.
International Nuclear Information System (INIS)
Piquin, Ruben; Zanni, Pablo
2003-01-01
The widespread replacement of reactor internals generates a substantial volume of active material.It is essential to work with these components at least in a partial way before the next planned stop.Due to the fact that the reactor internals pool and the storage pools for irradiated nuclear fuel have limited capacities, it has been proposed to compact an experimental shift of 50 irradiated coolant channels, that are currently placed in storage pools.Basically the processed waste will be put in baskets at the bottom of the storage pools.The alternative choice proposes to divide an irradiation coolant channel tube into different parts: stainless steel section, zircaloy-4 section and stainless steel section with hardened zones with cobalt alloys named Estelite-6.Having planned the constructive and operative solutions, the mechanical characterization of the different parts of the channel tube remains to be done.In the present paper, the necessary compacted strength of the irradiation coolant channel tube will be estimated for the stainless steel section and for the zircaloy-4 section, starting from experiment with unirradiated material and considering effects of radiation damage and hydrides on the ductility.These results will be used to design the necessary compacted tools for the semi-industrial installation
Directory of Open Access Journals (Sweden)
Waqas Rehan
2016-09-01
Full Text Available Wireless sensor networks (WSNs have become more and more diversified and are today able to also support high data rate applications, such as multimedia. In this case, per-packet channel handshaking/switching may result in inducing additional overheads, such as energy consumption, delays and, therefore, data loss. One of the solutions is to perform stream-based channel allocation where channel handshaking is performed once before transmitting the whole data stream. Deciding stream-based channel allocation is more critical in case of multichannel WSNs where channels of different quality/stability are available and the wish for high performance requires sensor nodes to switch to the best among the available channels. In this work, we will focus on devising mechanisms that perform channel quality/stability estimation in order to improve the accommodation of stream-based communication in multichannel wireless sensor networks. For performing channel quality assessment, we have formulated a composite metric, which we call channel rank measurement (CRM, that can demarcate channels into good, intermediate and bad quality on the basis of the standard deviation of the received signal strength indicator (RSSI and the average of the link quality indicator (LQI of the received packets. CRM is then used to generate a data set for training a supervised machine learning-based algorithm (which we call Normal Equation based Channel quality prediction (NEC algorithm in such a way that it may perform instantaneous channel rank estimation of any channel. Subsequently, two robust extensions of the NEC algorithm are proposed (which we call Normal Equation based Weighted Moving Average Channel quality prediction (NEWMAC algorithm and Normal Equation based Aggregate Maturity Criteria with Beta Tracking based Channel weight prediction (NEAMCBTC algorithm, that can perform channel quality estimation on the basis of both current and past values of channel rank estimation
Rehan, Waqas; Fischer, Stefan; Rehan, Maaz
2016-09-12
Wireless sensor networks (WSNs) have become more and more diversified and are today able to also support high data rate applications, such as multimedia. In this case, per-packet channel handshaking/switching may result in inducing additional overheads, such as energy consumption, delays and, therefore, data loss. One of the solutions is to perform stream-based channel allocation where channel handshaking is performed once before transmitting the whole data stream. Deciding stream-based channel allocation is more critical in case of multichannel WSNs where channels of different quality/stability are available and the wish for high performance requires sensor nodes to switch to the best among the available channels. In this work, we will focus on devising mechanisms that perform channel quality/stability estimation in order to improve the accommodation of stream-based communication in multichannel wireless sensor networks. For performing channel quality assessment, we have formulated a composite metric, which we call channel rank measurement (CRM), that can demarcate channels into good, intermediate and bad quality on the basis of the standard deviation of the received signal strength indicator (RSSI) and the average of the link quality indicator (LQI) of the received packets. CRM is then used to generate a data set for training a supervised machine learning-based algorithm (which we call Normal Equation based Channel quality prediction (NEC) algorithm) in such a way that it may perform instantaneous channel rank estimation of any channel. Subsequently, two robust extensions of the NEC algorithm are proposed (which we call Normal Equation based Weighted Moving Average Channel quality prediction (NEWMAC) algorithm and Normal Equation based Aggregate Maturity Criteria with Beta Tracking based Channel weight prediction (NEAMCBTC) algorithm), that can perform channel quality estimation on the basis of both current and past values of channel rank estimation. In the end
Massive-MIMO Sparse Uplink Channel Estimation Using Implicit Training and Compressed Sensing
Directory of Open Access Journals (Sweden)
Babar Mansoor
2017-01-01
Full Text Available Massive multiple-input multiple-output (massive-MIMO is foreseen as a potential technology for future 5G cellular communication networks due to its substantial benefits in terms of increased spectral and energy efficiency. These advantages of massive-MIMO are a consequence of equipping the base station (BS with quite a large number of antenna elements, thus resulting in an aggressive spatial multiplexing. In order to effectively reap the benefits of massive-MIMO, an adequate estimate of the channel impulse response (CIR between each transmit–receive link is of utmost importance. It has been established in the literature that certain specific multipath propagation environments lead to a sparse structured CIR in spatial and/or delay domains. In this paper, implicit training and compressed sensing based CIR estimation techniques are proposed for the case of massive-MIMO sparse uplink channels. In the proposed superimposed training (SiT based techniques, a periodic and low power training sequence is superimposed (arithmetically added over the information sequence, thus avoiding any dedicated time/frequency slots for the training sequence. For the estimation of such massive-MIMO sparse uplink channels, two greedy pursuits based compressed sensing approaches are proposed, viz: SiT based stage-wise orthogonal matching pursuit (SiT-StOMP and gradient pursuit (SiT-GP. In order to demonstrate the validity of proposed techniques, a performance comparison in terms of normalized mean square error (NCMSE and bit error rate (BER is performed with a notable SiT based least squares (SiT-LS channel estimation technique. The effect of channels’ sparsity, training-to-information power ratio (TIR and signal-to-noise ratio (SNR on BER and NCMSE performance of proposed schemes is thoroughly studied. For a simulation scenario of: 4 × 64 massive-MIMO with a channel sparsity level of 80 % and signal-to-noise ratio (SNR of 10 dB , a performance gain of 18 dB and 13 d
A qualitative assessment of climate adaptation options and some estimates of adaptation costs
International Nuclear Information System (INIS)
Van Ierland, E.C.; De Bruin, K.; Dellink, R.B.; Ruijs, A.
2007-02-01
The Routeplanner project aims to provide a 'systematic assessment' of potential adaptation options to respond to climate change in the Netherlands in connection to spatial planning. The study is the result of a policy oriented project that took place between May and September 2006. The aim of the current study is to provide a 'qualitative assessment' of the direct and indirect effects of adaptation options and to provide an assessment of some of the costs and benefits of adaptation options. The present report presents and summarizes the results of all phases of the study: an inventory of adaptation options, a qualitative assessment of the effects of the adaptation options for the Netherlands in the long run, a database which allows to rank the various options according to a set of criteria and a relative ranking on the basis of these criteria. Finally, the report also contains the best available information on costs and benefits of various adaptation options. However, while conducting the study the project team observed that reliable information in this respect is in many cases still lacking and an urgent need exists for more detailed studies on costs and benefits of adaptation options and the design of the best options to cope with climate change
Adaptive Disturbance Estimation for Offset-Free SISO Model Predictive Control
DEFF Research Database (Denmark)
Huusom, Jakob Kjøbsted; Poulsen, Niels Kjølstad; Jørgensen, Sten Bay
2011-01-01
Offset free tracking in Model Predictive Control requires estimation of unmeasured disturbances or the inclusion of an integrator. An algorithm for estimation of an unknown disturbance based on adaptive estimation with time varying forgetting is introduced and benchmarked against the classical...
Adaptive Estimation and Heuristic Optimization of Nonlinear Spacecraft Attitude Dynamics
2016-09-15
Biology, Control and Artificial Intelligence , MIT Press, Cambridge, MA, USA, 1992. 177 [89] Thompson, R. E., Colombi, J. M., Black, J. T., and Ayres...utilized for parameter and state estimates. MMAE algorithms involve constructing a bank of recursive estimators, each assuming a different hypothesis for...this research, MMAE routines employing parallel banks of unscented attitude filters are applied to analytical models of spacecraft with time- varying
Directory of Open Access Journals (Sweden)
Ser Javier Del
2005-01-01
Full Text Available We consider the case of two correlated sources, and . The correlation between them has memory, and it is modelled by a hidden Markov chain. The paper studies the problem of reliable communication of the information sent by the source over an additive white Gaussian noise (AWGN channel when the output of the other source is available as side information at the receiver. We assume that the receiver has no a priori knowledge of the correlation statistics between the sources. In particular, we propose the use of a turbo code for joint source-channel coding of the source . The joint decoder uses an iterative scheme where the unknown parameters of the correlation model are estimated jointly within the decoding process. It is shown that reliable communication is possible at signal-to-noise ratios close to the theoretical limits set by the combination of Shannon and Slepian-Wolf theorems.
Channel Selection and Feature Projection for Cognitive Load Estimation Using Ambulatory EEG
Directory of Open Access Journals (Sweden)
Tian Lan
2007-01-01
Full Text Available We present an ambulatory cognitive state classification system to assess the subject's mental load based on EEG measurements. The ambulatory cognitive state estimator is utilized in the context of a real-time augmented cognition (AugCog system that aims to enhance the cognitive performance of a human user through computer-mediated assistance based on assessments of cognitive states using physiological signals including, but not limited to, EEG. This paper focuses particularly on the offline channel selection and feature projection phases of the design and aims to present mutual-information-based techniques that use a simple sample estimator for this quantity. Analyses conducted on data collected from 3 subjects performing 2 tasks (n-back/Larson at 2 difficulty levels (low/high demonstrate that the proposed mutual-information-based dimensionality reduction scheme can achieve up to 94% cognitive load estimation accuracy.
Shima, Tomoyuki; Tomeba, Hiromichi; Adachi, Fumiyuki
Orthogonal multi-carrier direct sequence code division multiple access (orthogonal MC DS-CDMA) is a combination of time-domain spreading and orthogonal frequency division multiplexing (OFDM). In orthogonal MC DS-CDMA, the frequency diversity gain can be obtained by applying frequency-domain equalization (FDE) based on minimum mean square error (MMSE) criterion to a block of OFDM symbols and can improve the bit error rate (BER) performance in a severe frequency-selective fading channel. FDE requires an accurate estimate of the channel gain. The channel gain can be estimated by removing the pilot modulation in the frequency domain. In this paper, we propose a pilot-assisted channel estimation suitable for orthogonal MC DS-CDMA with FDE and evaluate, by computer simulation, the BER performance in a frequency-selective Rayleigh fading channel.
Blind CP-OFDM and ZP-OFDM Parameter Estimation in Frequency Selective Channels
Directory of Open Access Journals (Sweden)
Vincent Le Nir
2009-01-01
Full Text Available A cognitive radio system needs accurate knowledge of the radio spectrum it operates in. Blind modulation recognition techniques have been proposed to discriminate between single-carrier and multicarrier modulations and to estimate their parameters. Some powerful techniques use autocorrelation- and cyclic autocorrelation-based features of the transmitted signal applying to OFDM signals using a Cyclic Prefix time guard interval (CP-OFDM. In this paper, we propose a blind parameter estimation technique based on a power autocorrelation feature applying to OFDM signals using a Zero Padding time guard interval (ZP-OFDM which in particular excludes the use of the autocorrelation- and cyclic autocorrelation-based techniques. The proposed technique leads to an efficient estimation of the symbol duration and zero padding duration in frequency selective channels, and is insensitive to receiver phase and frequency offsets. Simulation results are given for WiMAX and WiMedia signals using realistic Stanford University Interim (SUI and Ultra-Wideband (UWB IEEE 802.15.4a channel models, respectively.
Directory of Open Access Journals (Sweden)
E. Romero-Aguirre
2012-01-01
Full Text Available In this paper, a configurable superimposed training (ST/data-dependent ST (DDST transmitter and architecture based on array processors (APs for DDST channel estimation are presented. Both architectures, designed under full-hardware paradigm, were described using Verilog HDL, targeted in Xilinx Virtex-5 and they were compared with existent approaches. The synthesis results showed a FPGA slice consumption of 1% for the transmitter and 3% for the estimator with 160 and 115 MHz operating frequencies, respectively. The signal-to-quantization-noise ratio (SQNR performance of the transmitter is about 82 dB to support 4/16/64-QAM modulation. A Monte Carlo simulation demonstrates that the mean square error (MSE of the channel estimator implemented in hardware is practically the same as the one obtained with the floating-point golden model. The high performance and reduced hardware of the proposed architectures lead to the conclusion that the DDST concept can be applied in current communications standards.
Channel Parameter Estimation for Scatter Cluster Model Using Modified MUSIC Algorithm
Directory of Open Access Journals (Sweden)
Jinsheng Yang
2012-01-01
Full Text Available Recently, the scatter cluster models which precisely evaluate the performance of the wireless communication system have been proposed in the literature. However, the conventional SAGE algorithm does not work for these scatter cluster-based models because it performs poorly when the transmit signals are highly correlated. In this paper, we estimate the time of arrival (TOA, the direction of arrival (DOA, and Doppler frequency for scatter cluster model by the modified multiple signal classification (MUSIC algorithm. Using the space-time characteristics of the multiray channel, the proposed algorithm combines the temporal filtering techniques and the spatial smoothing techniques to isolate and estimate the incoming rays. The simulation results indicated that the proposed algorithm has lower complexity and is less time-consuming in the dense multipath environment than SAGE algorithm. Furthermore, the estimations’ performance increases with elements of receive array and samples length. Thus, the problem of the channel parameter estimation of the scatter cluster model can be effectively addressed with the proposed modified MUSIC algorithm.
Verification of “Channel-Probability Model” of Grain Yield Estimation
Directory of Open Access Journals (Sweden)
ZHENG Hong-yan
2016-07-01
Full Text Available The "channel-probability model" of grain yield estimation was verified and discussed systematically by using the grain production data from 1949 to 2014 in 16 typical counties, and 6 typical districts, and 31 provinces of China. The results showed as follows:(1Due to the geographical spatial scale was large enough, different climate zones and different meteorological conditions could compensated, and grain yield estimation error was small in the scale of nation. Therefore, it was not necessary to modify the grain yield estimation error by mirco-trend and the climate year types in the scale of nation. However, the grain yield estimation in the scale of province was located at the same of a climate zone,the scale was small, so the impact of the meteorological conditions on grain yield was less complementary than the scale of nation. While the spatial scale of districts and counties was smaller, accordingly the compensation of the impact of the meteorological conditions on grain yield was least. Therefore, it was necessary to use mrico-trend amendment and the climate year types amendment to modify the grain yield estimation in districts and counties.(2Mirco-trend modification had two formulas, generally, when the error of grain yield estimation was less than 10%, it could be modified by Y×(1-K; while the error of grain yield estimation was more than 10%, it could be modified by Y/(1+K.(3Generally, the grain estimation had 5 grades, and some had 7 grades because of large error fluctuation. The parameters modified of super-high yield year and super-low yield year must be depended on the real-time crop growth and the meteorological condition. (4By plenty of demonstration analysis, it was proved that the theory and method of "channel-probability model" was scientific and practical. In order to improve the accuracy of grain yield estimation, the parameters could be modified with micro-trend amendment and the climate year types amendment. If the
A PCA and ELM Based Adaptive Method for Channel Equalization in MFL Inspection
Directory of Open Access Journals (Sweden)
Zhenning Wu
2014-01-01
Full Text Available Magnetic flux leakage (MFL as an efficient method for pipeline flaw detection plays important role in pipeline safety. This nondestructive test technique assesses the health of the buried pipeline. The signal is gathered by an array of hall-effect sensors disposed at the magnetic neutral plane of a pair of permanent magnet in the pipeline inspection gauge (PIG clinging to the inner surface of the pipe wall. The magnetic flux measured by the sensors reflects the health condition of the pipe. The signal is influenced by not only the condition of the pipe, but also by the lift-off value of the sensors and various properties of electronic component. The consistency of the position of the sensors is almost never satisfied and each sensor measures differently. In this paper, a new scheme of channel equalization is proposed for MFL signal in order to correct sensor misalignments, which eventually improves accuracy of defect characterization. The algorithm proposed in this paper is adaptive to the effects of error on the disposition of the sensor due to manufacturing imperfections and movements of the sensors. The algorithm is tested by data acquired from an experimental pipeline. The results show the effectiveness of the proposed algorithm.
Round-Trip Delay Estimation in OPC UA Server-Client Communication Channel
Nakutis, Zilvinas; Deksnys, Vytautas; Jarusevicius, Ignas; Dambrauskas, Vilius; Cincikas, Gediminas; Kriauceliunas, Alenas
2017-01-01
In this paper an estimation of round-trip delay (RTD) in OPC UA server-client channel was investigated in various data communication networks including Ethernet, WiFi, and 3G. Testing was carried out using the developed IoT gateway device running OPC UA server and remote computer running OPC UA client. The server and the client machines were configured to operate in Virtual Private Network powered by OpenVPN. Experimental analysis revealed that RTD values are distributed in the wide range exh...
Institute of Scientific and Technical Information of China (English)
Xiaogu ZHENG
2009-01-01
An adaptive estimation of forecast error covariance matrices is proposed for Kalman filtering data assimilation. A forecast error covariance matrix is initially estimated using an ensemble of perturbation forecasts. This initially estimated matrix is then adjusted with scale parameters that are adaptively estimated by minimizing -2log-likelihood of observed-minus-forecast residuals. The proposed approach could be applied to Kalman filtering data assimilation with imperfect models when the model error statistics are not known. A simple nonlinear model (Burgers' equation model) is used to demonstrate the efficacy of the proposed approach.
Adaptive nonparametric estimation for L\\'evy processes observed at low frequency
Kappus, Johanna
2013-01-01
This article deals with adaptive nonparametric estimation for L\\'evy processes observed at low frequency. For general linear functionals of the L\\'evy measure, we construct kernel estimators, provide upper risk bounds and derive rates of convergence under regularity assumptions. Our focus lies on the adaptive choice of the bandwidth, using model selection techniques. We face here a non-standard problem of model selection with unknown variance. A new approach towards this problem is proposed, ...
Sun, Xiaole; Djordjevic, Ivan B.; Neifeld, Mark A.
2016-03-01
Free-space optical (FSO) channels can be characterized by random power fluctuations due to atmospheric turbulence, which is known as scintillation. Weak coherent source based FSO quantum key distribution (QKD) systems suffer from the scintillation effect because during the deep channel fading the expected detection rate drops, which then gives an eavesdropper opportunity to get additional information about protocol by performing photon number splitting (PNS) attack and blocking single-photon pulses without changing QBER. To overcome this problem, in this paper, we study a large-alphabet QKD protocol, which is achieved by using pulse-position modulation (PPM)-like approach that utilizes the time-frequency uncertainty relation of the weak coherent photon state, called here TF-PPM-QKD protocol. We first complete finite size analysis for TF-PPM-QKD protocol to give practical bounds against non-negligible statistical fluctuation due to finite resources in practical implementations. The impact of scintillation under strong atmospheric turbulence regime is studied then. To overcome the secure key rate performance degradation of TF-PPM-QKD caused by scintillation, we propose an adaptation method for compensating the scintillation impact. By changing source intensity according to the channel state information (CSI), obtained by classical channel, the adaptation method improves the performance of QKD system with respect to the secret key rate. The CSI of a time-varying channel can be predicted using stochastic models, such as autoregressive (AR) models. Based on the channel state predictions, we change the source intensity to the optimal value to achieve a higher secret key rate. We demonstrate that the improvement of the adaptation method is dependent on the prediction accuracy.
Data adaptive control parameter estimation for scaling laws
Energy Technology Data Exchange (ETDEWEB)
Dinklage, Andreas [Max-Planck-Institut fuer Plasmaphysik, Teilinstitut Greifswald, Wendelsteinstrasse 1, D-17491 Greifswald (Germany); Dose, Volker [Max-Planck- Institut fuer Plasmaphysik, Boltzmannstrasse 2, D-85748 Garching (Germany)
2007-07-01
Bayesian experimental design quantifies the utility of data expressed by the information gain. Data adaptive exploration determines the expected utility of a single new measurement using existing data and a data descriptive model. In other words, the method can be used for experimental planning. As an example for a multivariate linear case, we apply this method for constituting scaling laws of fusion devices. In detail, the scaling of the stellarator W7-AS is examined for a subset of {iota}=1/3 data. The impact of the existing data on the scaling exponents is presented. Furthermore, in control parameter space regions of high utility are identified which improve the accuracy of the scaling law. This approach is not restricted to the presented example only, but can also be extended to non-linear models.
Brown, Maile R; Kronengold, Jack; Gazula, Valeswara-Rao; Spilianakis, Charalampos G; Flavell, Richard A; von Hehn, Christian A A; Bhattacharjee, Arin; Kaczmarek, Leonard K
2008-11-01
The rates of activation and unitary properties of Na+-activated K+ (K(Na)) currents have been found to vary substantially in different types of neurones. One class of K(Na) channels is encoded by the Slack gene. We have now determined that alternative RNA splicing gives rise to at least five different transcripts for Slack, which produce Slack channels that differ in their predicted cytoplasmic amino-termini and in their kinetic properties. Two of these, termed Slack-A channels, contain an amino-terminus domain closely resembling that of another class of K(Na) channels encoded by the Slick gene. Neuronal expression of Slack-A channels and of the previously described Slack isoform, now called Slack-B, are driven by independent promoters. Slack-A mRNAs were enriched in the brainstem and olfactory bulb and detected at significant levels in four different brain regions. When expressed in CHO cells, Slack-A channels activate rapidly upon depolarization and, in single channel recordings in Xenopus oocytes, are characterized by multiple subconductance states with only brief transient openings to the fully open state. In contrast, Slack-B channels activate slowly over hundreds of milliseconds, with openings to the fully open state that are approximately 6-fold longer than those for Slack-A channels. In numerical simulations, neurones in which outward currents are dominated by a Slack-A-like conductance adapt very rapidly to repeated or maintained stimulation over a wide range of stimulus strengths. In contrast, Slack-B currents promote rhythmic firing during maintained stimulation, and allow adaptation rate to vary with stimulus strength. Using an antibody that recognizes all amino-termini isoforms of Slack, Slack immunoreactivity is present at locations that have no Slack-B-specific staining, including olfactory bulb glomeruli and the dendrites of hippocampal neurones, suggesting that Slack channels with alternate amino-termini such as Slack-A channels are present at
Adaptive algorithm for mobile user positioning based on environment estimation
Directory of Open Access Journals (Sweden)
Grujović Darko
2014-01-01
Full Text Available This paper analyzes the challenges to realize an infrastructure independent and a low-cost positioning method in cellular networks based on RSS (Received Signal Strength parameter, auxiliary timing parameter and environment estimation. The proposed algorithm has been evaluated using field measurements collected from GSM (Global System for Mobile Communications network, but it is technology independent and can be applied in UMTS (Universal Mobile Telecommunication Systems and LTE (Long-Term Evolution networks, also.
Nonlinear adaptive control system design with asymptotically stable parameter estimation error
Mishkov, Rumen; Darmonski, Stanislav
2018-01-01
The paper presents a new general method for nonlinear adaptive system design with asymptotic stability of the parameter estimation error. The advantages of the approach include asymptotic unknown parameter estimation without persistent excitation and capability to directly control the estimates transient response time. The method proposed modifies the basic parameter estimation dynamics designed via a known nonlinear adaptive control approach. The modification is based on the generalised prediction error, a priori constraints with a hierarchical parameter projection algorithm, and the stable data accumulation concepts. The data accumulation principle is the main tool for achieving asymptotic unknown parameter estimation. It relies on the parametric identifiability system property introduced. Necessary and sufficient conditions for exponential stability of the data accumulation dynamics are derived. The approach is applied in a nonlinear adaptive speed tracking vector control of a three-phase induction motor.
Liao, Anwen
2017-11-01
Millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) with hybrid precoding is a promising technique for the future 5G wireless communications. Due to a large number of antennas but a much smaller number of radio frequency (RF) chains, estimating the high-dimensional mmWave massive MIMO channel will bring the large pilot overhead. To overcome this challenge, this paper proposes a super-resolution channel estimation scheme based on two-dimensional (2D) unitary ESPRIT algorithm. By exploiting the angular sparsity of mmWave channels, the continuously distributed angle of arrivals/departures (AoAs/AoDs) can be jointly estimated with high accuracy. Specifically, by designing the uplink training signals at both base station (BS) and mobile station (MS), we first use low pilot overhead to estimate a low-dimensional effective channel, which has the same shift-invariance of array response as the high-dimensional mmWave MIMO channel to be estimated. From the low-dimensional effective channel, the superresolution estimates of AoAs and AoDs can be jointly obtained by exploiting the 2D unitary ESPRIT channel estimation algorithm. Furthermore, the associated path gains can be acquired based on the least squares (LS) criterion. Finally, we can reconstruct the high-dimensional mmWave MIMO channel according to the obtained AoAs, AoDs, and path gains. Simulation results have confirmed that the proposed scheme is superior to conventional schemes with a much lower pilot overhead.
Liao, Anwen; Gao, Zhen; Wu, Yongpeng; Wang, Hua; Alouini, Mohamed-Slim
2017-01-01
Millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) with hybrid precoding is a promising technique for the future 5G wireless communications. Due to a large number of antennas but a much smaller number of radio frequency (RF) chains, estimating the high-dimensional mmWave massive MIMO channel will bring the large pilot overhead. To overcome this challenge, this paper proposes a super-resolution channel estimation scheme based on two-dimensional (2D) unitary ESPRIT algorithm. By exploiting the angular sparsity of mmWave channels, the continuously distributed angle of arrivals/departures (AoAs/AoDs) can be jointly estimated with high accuracy. Specifically, by designing the uplink training signals at both base station (BS) and mobile station (MS), we first use low pilot overhead to estimate a low-dimensional effective channel, which has the same shift-invariance of array response as the high-dimensional mmWave MIMO channel to be estimated. From the low-dimensional effective channel, the superresolution estimates of AoAs and AoDs can be jointly obtained by exploiting the 2D unitary ESPRIT channel estimation algorithm. Furthermore, the associated path gains can be acquired based on the least squares (LS) criterion. Finally, we can reconstruct the high-dimensional mmWave MIMO channel according to the obtained AoAs, AoDs, and path gains. Simulation results have confirmed that the proposed scheme is superior to conventional schemes with a much lower pilot overhead.
Estimating Position of Mobile Robots From Omnidirectional Vision Using an Adaptive Algorithm.
Li, Luyang; Liu, Yun-Hui; Wang, Kai; Fang, Mu
2015-08-01
This paper presents a novel and simple adaptive algorithm for estimating the position of a mobile robot with high accuracy in an unknown and unstructured environment by fusing images of an omnidirectional vision system with measurements of odometry and inertial sensors. Based on a new derivation where the omnidirectional projection can be linearly parameterized by the positions of the robot and natural feature points, we propose a novel adaptive algorithm, which is similar to the Slotine-Li algorithm in model-based adaptive control, to estimate the robot's position by using the tracked feature points in image sequence, the robot's velocity, and orientation angles measured by odometry and inertial sensors. It is proved that the adaptive algorithm leads to global exponential convergence of the position estimation errors to zero. Simulations and real-world experiments are performed to demonstrate the performance of the proposed algorithm.
Key Parameters Estimation and Adaptive Warning Strategy for Rear-End Collision of Vehicle
Directory of Open Access Journals (Sweden)
Xiang Song
2015-01-01
Full Text Available The rear-end collision warning system requires reliable warning decision mechanism to adapt the actual driving situation. To overcome the shortcomings of existing warning methods, an adaptive strategy is proposed to address the practical aspects of the collision warning problem. The proposed strategy is based on the parameter-adaptive and variable-threshold approaches. First, several key parameter estimation algorithms are developed to provide more accurate and reliable information for subsequent warning method. They include a two-stage algorithm which contains a Kalman filter and a Luenberger observer for relative acceleration estimation, a Bayesian theory-based algorithm of estimating the road friction coefficient, and an artificial neural network for estimating the driver’s reaction time. Further, the variable-threshold warning method is designed to achieve the global warning decision. In the method, the safety distance is employed to judge the dangerous state. The calculation method of the safety distance in this paper can be adaptively adjusted according to the different driving conditions of the leading vehicle. Due to the real-time estimation of the key parameters and the adaptive calculation of the warning threshold, the strategy can adapt to various road and driving conditions. Finally, the proposed strategy is evaluated through simulation and field tests. The experimental results validate the feasibility and effectiveness of the proposed strategy.
Uncertainty of feedback and state estimation determines the speed of motor adaptation
Directory of Open Access Journals (Sweden)
Kunlin Wei
2010-05-01
Full Text Available Humans can adapt their motor behaviors to deal with ongoing changes. To achieve this, the nervous system needs to estimate central variables for our movement based on past knowledge and new feedback, both of which are uncertain. In the Bayesian framework, rates of adaptation characterize how noisy feedback is in comparison to the uncertainty of the state estimate. The predictions of Bayesian models are intuitive: the nervous system should adapt slower when sensory feedback is more noisy and faster when its state estimate is more uncertain. Here we want to quantitatively understand how uncertainty in these two factors affects motor adaptation. In a hand reaching experiment we measured trial-by-trial adaptation to a randomly changing visual perturbation to characterize the way the nervous system handles uncertainty in state estimation and feedback. We found both qualitative predictions of Bayesian models confirmed. Our study provides evidence that the nervous system represents and uses uncertainty in state estimate and feedback during motor adaptation.
Mohamed, Refaat; Ismail, Mahmoud H.; Newagy, Fatma; Mourad, Heba M.
2013-03-01
Stemming from the fact that the α-μ fading distribution is one of the very general fading models used in the literature to describe the small scale fading phenomenon, in this paper, closed-form expressions for the Shannon capacity of the α-μ fading channel operating under four main adaptive transmission strategies are derived assuming integer values for μ. These expressions are derived for the case of no diversity as well as for selection combining diversity with independent and identically distributed branches. The obtained expressions reduce to those previously derived in the literature for the Weibull as well as the Rayleigh fading cases, which are both special cases of the α-μ channel. Numerical results are presented for the capacity under the four adaptive transmission strategies and the effect of the fading parameter as well as the number of diversity branches is studied.
Directory of Open Access Journals (Sweden)
Salim Bahçeci
2010-01-01
Full Text Available In impulse radio ultra-wideband (IR-UWB systems where the channel lengths are on the order of a few hundred taps, conventional use of frequency-domain (FD processing for channel estimation and equalization may not be feasible because the need to add a cyclic prefix (CP to each block causes a significant reduction in the spectral efficiency. On the other hand, using no or short CP causes the interblock interference (IBI and thus degradation in the receiver performance. Therefore, in order to utilize FD receiver processing UWB systems without a significant loss in the spectral efficiency and the performance, IBI cancellation mechanisms are needed in both the channel estimation and equalization operations. For this reason, in this paper, we consider the joint FD channel estimation and equalization for IR-UWB systems with short cyclic prefix (CP and propose a novel iterative receiver employing soft IBI estimation and cancellation within both its FD channel estimator and FD equalizer components. We show by simulation results that the proposed FD receiver attains performances close to that of the full CP case in both line-of-sight (LOS and non-line-of-sight (NLOS UWB channels after only a few iterations.
Directory of Open Access Journals (Sweden)
Stacie B Dusetzina
Full Text Available Channeling occurs when a medication and its potential comparators are selectively prescribed based on differences in underlying patient characteristics. Drug safety advisories can provide new information regarding the relative safety or effectiveness of a drug product which might increase selective prescribing. In particular, when reported adverse effects vary among drugs within a therapeutic class, clinicians may channel patients toward or away from a drug based on the patient's underlying risk for an adverse outcome. If channeling is not identified and appropriately managed it might lead to confounding in observational comparative effectiveness studies.To demonstrate channeling among new users of second generation antipsychotics following a Food and Drug Administration safety advisory and to evaluate the impact of channeling on cardiovascular risk estimates over time.Florida Medicaid data from 2001-2006.Retrospective cohort of adults initiating second generation antipsychotics. We used propensity scores to match olanzapine initiators with other second generation antipsychotic initiators. To evaluate channeling away from olanzapine following an FDA safety advisory, we estimated calendar time-specific propensity scores. We compare the performance of these calendar time-specific propensity scores with conventionally-estimated propensity scores on estimates of cardiovascular risk.Increased channeling away from olanzapine was evident for some, but not all, cardiovascular risk factors and corresponded with the timing of the FDA advisory. Covariate balance was optimized within period and across all periods when using the calendar time-specific propensity score. Hazard ratio estimates for cardiovascular outcomes did not differ across models (Conventional PS: 0.97, 95%CI: 0.81-3.18 versus calendar time-specific PS: 0.93, 95%CI: 0.77-3.04.Changes in channeling over time was evident for several covariates but had limited impact on cardiovascular risk
Fractional-order adaptive fault estimation for a class of nonlinear fractional-order systems
N'Doye, Ibrahima; Laleg-Kirati, Taous-Meriem
2015-01-01
This paper studies the problem of fractional-order adaptive fault estimation for a class of fractional-order Lipschitz nonlinear systems using fractional-order adaptive fault observer. Sufficient conditions for the asymptotical convergence of the fractional-order state estimation error, the conventional integer-order and the fractional-order faults estimation error are derived in terms of linear matrix inequalities (LMIs) formulation by introducing a continuous frequency distributed equivalent model and using an indirect Lyapunov approach where the fractional-order α belongs to 0 < α < 1. A numerical example is given to demonstrate the validity of the proposed approach.
Fractional-order adaptive fault estimation for a class of nonlinear fractional-order systems
N'Doye, Ibrahima
2015-07-01
This paper studies the problem of fractional-order adaptive fault estimation for a class of fractional-order Lipschitz nonlinear systems using fractional-order adaptive fault observer. Sufficient conditions for the asymptotical convergence of the fractional-order state estimation error, the conventional integer-order and the fractional-order faults estimation error are derived in terms of linear matrix inequalities (LMIs) formulation by introducing a continuous frequency distributed equivalent model and using an indirect Lyapunov approach where the fractional-order α belongs to 0 < α < 1. A numerical example is given to demonstrate the validity of the proposed approach.
Nonlinear Adaptive Descriptor Observer for the Joint States and Parameters Estimation
2016-08-29
In this note, the joint state and parameters estimation problem for nonlinear multi-input multi-output descriptor systems is considered. Asymptotic convergence of the adaptive descriptor observer is established by a sufficient set of linear matrix inequalities for the noise-free systems. The noise corrupted systems are also considered and it is shown that the state and parameters estimation errors are bounded for bounded noises. In addition, if the noises are bounded and have zero mean, then the estimation errors asymptotically converge to zero in the mean. The performance of the proposed adaptive observer is illustrated by a numerical example.
Nonlinear Adaptive Descriptor Observer for the Joint States and Parameters Estimation
Unknown author
2016-01-01
In this note, the joint state and parameters estimation problem for nonlinear multi-input multi-output descriptor systems is considered. Asymptotic convergence of the adaptive descriptor observer is established by a sufficient set of linear matrix inequalities for the noise-free systems. The noise corrupted systems are also considered and it is shown that the state and parameters estimation errors are bounded for bounded noises. In addition, if the noises are bounded and have zero mean, then the estimation errors asymptotically converge to zero in the mean. The performance of the proposed adaptive observer is illustrated by a numerical example.
Adaptive Kalman filter based state of charge estimation algorithm for lithium-ion battery
International Nuclear Information System (INIS)
Zheng Hong; Liu Xu; Wei Min
2015-01-01
In order to improve the accuracy of the battery state of charge (SOC) estimation, in this paper we take a lithium-ion battery as an example to study the adaptive Kalman filter based SOC estimation algorithm. Firstly, the second-order battery system model is introduced. Meanwhile, the temperature and charge rate are introduced into the model. Then, the temperature and the charge rate are adopted to estimate the battery SOC, with the help of the parameters of an adaptive Kalman filter based estimation algorithm model. Afterwards, it is verified by the numerical simulation that in the ideal case, the accuracy of SOC estimation can be enhanced by adding two elements, namely, the temperature and charge rate. Finally, the actual road conditions are simulated with ADVISOR, and the simulation results show that the proposed method improves the accuracy of battery SOC estimation under actual road conditions. Thus, its application scope in engineering is greatly expanded. (paper)
Directory of Open Access Journals (Sweden)
Imran Khan
2018-01-01
Full Text Available Uplink and Downlink channel estimation in massive Multiple Input Multiple Output (MIMO systems is an intricate issue because of the increasing channel matrix dimensions. The channel feedback overhead using traditional codebook schemes is very large, which consumes more bandwidth and decreases the overall system efficiency. The purpose of this paper is to decrease the channel estimation overhead by taking the advantage of sparse attributes and also to optimize the Energy Efficiency (EE of the system. To cope with this issue, we propose a novel approach by using Compressed-Sensing (CS, Block Iterative-Support-Detection (Block-ISD, Angle-of-Departure (AoD and Structured Compressive Sampling Matching Pursuit (S-CoSaMP algorithms to reduce the channel estimation overhead and compare them with the traditional algorithms. The CS uses temporal-correlation of time-varying channels to produce Differential-Channel Impulse Response (DCIR among two CIRs that are adjacent in time-slots. DCIR has greater sparsity than the conventional CIRs as it can be easily compressed. The Block-ISD uses spatial-correlation of the channels to obtain the block-sparsity which results in lower pilot-overhead. AoD quantizes the channels whose path-AoDs variation is slower than path-gains and such information is utilized for reducing the overhead. S-CoSaMP deploys structured-sparsity to obtain reliable Channel-State-Information (CSI. MATLAB simulation results show that the proposed CS based algorithms reduce the feedback and pilot-overhead by a significant percentage and also improve the system capacity as compared with the traditional algorithms. Moreover, the EE level increases with increasing Base Station (BS density, UE density and lowering hardware impairments level.
An adaptive observer for on-line tool wear estimation in turning, Part I: Theory
Danai, Kourosh; Ulsoy, A. Galip
1987-04-01
On-line sensing of tool wear has been a long-standing goal of the manufacturing engineering community. In the absence of any reliable on-line tool wear sensors, a new model-based approach for tool wear estimation has been proposed. This approach is an adaptive observer, based on force measurement, which uses both parameter and state estimation techniques. The design of the adaptive observer is based upon a dynamic state model of tool wear in turning. This paper (Part I) presents the model, and explains its use as the basis for the adaptive observer design. This model uses flank wear and crater wear as state variables, feed as the input, and the cutting force as the output. The suitability of the model as the basis for adaptive observation is also verified. The implementation of the adaptive observer requires the design of a state observer and a parameter estimator. To obtain the model parameters for tuning the adaptive observer procedures for linearisation of the non-linear model are specified. The implementation of the adaptive observer in turning and experimental results are presented in a companion paper (Part II).
DEFF Research Database (Denmark)
Morningstar, Colin; Bulava, John; Singha, Bijit
2017-01-01
An implementation of estimating the two-to-two $K$-matrix from finite-volume energies based on the L\\"uscher formalism and involving a Hermitian matrix known as the "box matrix" is described. The method includes higher partial waves and multiple decay channels. Two fitting procedures for estimating...
Equations for estimating bankfull channel geometry and discharge for streams in Massachusetts
Bent, Gardner C.; Waite, Andrew M.
2013-01-01
Regression equations were developed for estimating bankfull geometry—width, mean depth, cross-sectional area—and discharge for streams in Massachusetts. The equations provide water-resource and conservation managers with methods for estimating bankfull characteristics at specific stream sites in Massachusetts. This information can be used for the adminstration of the Commonwealth of Massachusetts Rivers Protection Act of 1996, which establishes a protected riverfront area extending from the mean annual high-water line corresponding to the elevation of bankfull discharge along each side of a perennial stream. Additionally, information on bankfull channel geometry and discharge are important to Federal, State, and local government agencies and private organizations involved in stream assessment and restoration projects. Regression equations are based on data from stream surveys at 33 sites (32 streamgages and 1 crest-stage gage operated by the U.S. Geological Survey) in and near Massachusetts. Drainage areas of the 33 sites ranged from 0.60 to 329 square miles (mi2). At 27 of the 33 sites, field data were collected and analyses were done to determine bankfull channel geometry and discharge as part of the present study. For 6 of the 33 sites, data on bankfull channel geometry and discharge were compiled from other studies done by the U.S. Geological Survey, Natural Resources Conservation Service of the U.S. Department of Agriculture, and the Vermont Department of Environmental Conservation. Similar techniques were used for field data collection and analysis for bankfull channel geometry and discharge at all 33 sites. Recurrence intervals of the bankfull discharge, which represent the frequency with which a stream fills its channel, averaged 1.53 years (median value 1.34 years) at the 33 sites. Simple regression equations were developed for bankfull width, mean depth, cross-sectional area, and discharge using drainage area, which is the most significant explanatory
Abuzaid, Abdulrahman I.
2014-09-01
Efficient receiver designs for cooperative communication systems are becoming increasingly important. In previous work, cooperative networks communicated with the use of $L$ relays. As the receiver is constrained, it can only process $U$ out of $L$ relays. Channel shortening and reduced-rank techniques were employed to design the preprocessing matrix. In this paper, a receiver structure is proposed which combines the joint iterative optimization (JIO) algorithm and our proposed threshold selection criteria. This receiver structure assists in determining the optimal $U-{opt}$. Furthermore, this receiver provides the freedom to choose $U ≤ U-{opt}$ for each frame depending upon the tolerable difference allowed for mean square error (MSE). Our study and simulation results show that by choosing an appropriate threshold, it is possible to gain in terms of complexity savings without affecting the BER performance of the system. Furthermore, in this paper the effect of channel estimation errors is investigated on the MSE performance of the amplify-and-forward (AF) cooperative relaying system.
Individual Channel Estimation in a Diamond Relay Network Using Relay-Assisted Training
Directory of Open Access Journals (Sweden)
Xianwen He
2017-01-01
Full Text Available We consider the training design and channel estimation in the amplify-and-forward (AF diamond relay network. Our strategy is to transmit the source training in time-multiplexing (TM mode while each relay node superimposes its own relay training over the amplified received data signal without bandwidth expansion. The principal challenge is to obtain accurate channel state information (CSI of second-hop link due to the multiaccess interference (MAI and cooperative data interference (CDI. To maintain the orthogonality between data and training, a modified relay-assisted training scheme is proposed to migrate the CDI, where some of the cooperative data at the relay are discarded to accommodate relay training. Meanwhile, a couple of optimal zero-correlation zone (ZCZ relay-assisted sequences are designed to avoid MAI. At the destination node, the received signals from the two relay nodes are combined to achieve spatial diversity and enhanced data reliability. The simulation results are presented to validate the performance of the proposed schemes.
Fast Spectral Velocity Estimation Using Adaptive Techniques: In-Vivo Results
DEFF Research Database (Denmark)
Gran, Fredrik; Jakobsson, Andreas; Udesen, Jesper
2007-01-01
Adaptive spectral estimation techniques are known to provide good spectral resolution and contrast even when the observation window(OW) is very sbort. In this paper two adaptive techniques are tested and compared to the averaged perlodogram (Welch) for blood velocity estimation. The Blood Power...... the blood process over slow-time and averaging over depth to find the power spectral density estimate. In this paper, the two adaptive methods are explained, and performance Is assessed in controlled steady How experiments and in-vivo measurements. The three methods were tested on a circulating How rig...... with a blood mimicking fluid flowing in the tube. The scanning section is submerged in water to allow ultrasound data acquisition. Data was recorded using a BK8804 linear array transducer and the RASMUS ultrasound scanner. The controlled experiments showed that the OW could be significantly reduced when...
A new anisotropic mesh adaptation method based upon hierarchical a posteriori error estimates
Huang, Weizhang; Kamenski, Lennard; Lang, Jens
2010-03-01
A new anisotropic mesh adaptation strategy for finite element solution of elliptic differential equations is presented. It generates anisotropic adaptive meshes as quasi-uniform ones in some metric space, with the metric tensor being computed based on hierarchical a posteriori error estimates. A global hierarchical error estimate is employed in this study to obtain reliable directional information of the solution. Instead of solving the global error problem exactly, which is costly in general, we solve it iteratively using the symmetric Gauß-Seidel method. Numerical results show that a few GS iterations are sufficient for obtaining a reasonably good approximation to the error for use in anisotropic mesh adaptation. The new method is compared with several strategies using local error estimators or recovered Hessians. Numerical results are presented for a selection of test examples and a mathematical model for heat conduction in a thermal battery with large orthotropic jumps in the material coefficients.
Wang, Rui; Tao, Meixia; Mehrpouyan, Hani; Hua, Yingbo
2014-01-01
In this paper, while considering the impact of antenna correlation and the interference from neighboring users, we analyze channel estimation and training sequence design for multi-input multi-output (MIMO) two-way relay (TWR) systems. To this end, we propose to decompose the bidirectional transmission links into two phases, i.e., the multiple access (MAC) phase and the broadcasting (BC) phase. By considering the Kronecker-structured channel model, we derive the optimal linear minimum mean-sq...
Channel geometry and discharge estimates for Dao and Niger Valles, Mars
Musiol, S.; van Gasselt, S.; Neukum, G.
2008-09-01
Dao Vallis and appear to be truncated by the channeled plains, indicating that the erosion of Hadriaca Patera preceded erosion on the plains [1]. Data sets and additional information For the eastern-Hellas region a sufficient HRSC coverage exists. In addition, age estimates for the channel floors and the surrounding plains are available [7]. For detailed studies we processed MOC and HIRISE images also. Moreover, a detailed geologic map of the Hellas region has been made [8] which was utilized to constrain the channel boundaries and the main branches. Computations are actually done with MOLA data, but will be further improved by a high resolution mosaic DTM created out of HRSC stereo data of the eastern Hellas area. Water flow experiments within a Mars Simulation Chamber conducted at the Open University London, Department of Earth and Environmental Sciences (pers. comm.), suggest a complex interaction of phase changes (boiling and freezing) which have to be kept in mind when modeling the discharge of water from the subsurface. Such experiments will be improved in further investigations to give a better input to numerical modeling. Work plan The objective of the ongoing work is to make a quantitative comparison between the amount of water that could be melted by volcano-permafrost interaction and the outflow volume derived from channel and chaotic terrain morphology. The melted water is supposed to be initially stored as ice in a subsurface porous medium, so that the quested volume depends on the pore space and drainage area to be reached by a heat supplier. To find an approach to this problem, we want to reconstruct the outflow event by computing the discharge and sediment transport rate for Dao and Niger Valles under consideration of flow and transport processes in martian channels reviewed by [9]. The theoretical background of this work is used to derive model parameters. Channel width and water depth were obtained using individual MOLA tracks. Together with an
Cenci, Simone; Montero-Castaño, Ana; Saavedra, Serguei
2018-01-21
A major challenge in community ecology is to understand how species respond to environmental changes. Previous studies have shown that the reorganization of interactions among co-occurring species can modulate their chances to adapt to novel environmental conditions. Moreover, empirical evidence has shown that these ecological dynamics typically facilitate the persistence of groups of species rather than entire communities. However, so far, we have no systematic methodology to identify those groups of species with the highest or lowest chances to adapt to new environments through a reorganization of their interactions. Yet, this could prove extremely valuable for developing new conservation strategies. Here, we introduce a theoretical framework to estimate the effect of the reorganization of interactions on the adaptability of a group of species, within a community, to novel environmental conditions. We introduce the concept of the adaptation space of a group of species based on a feasibility analysis of a population dynamics model. We define the adaptation space of a group as the set of environmental conditions that can be made compatible with its persistence thorough the reorganization of interactions among species within the group. The larger the adaptation space of a group, the larger its likelihood to adapt to a novel environment. We show that the interactions in the community outside a group can act as structural constraints and be used to quantitatively compare the size of the adaptation space among different groups of species within a community. To test our theoretical framework, we perform a data analysis on several pairs of natural and artificially perturbed ecological communities. Overall, we find that the groups of species present in both control and perturbed communities are among the ones with the largest adaptation space. We believe that the results derived from our framework point out towards new directions to understand and estimate the
Delay Estimator and Improved Proportionate Multi-Delay Adaptive Filtering Algorithm
Directory of Open Access Journals (Sweden)
E. Verteletskaya
2012-04-01
Full Text Available This paper pertains to speech and acoustic signal processing, and particularly to a determination of echo path delay and operation of echo cancellers. To cancel long echoes, the number of weights in a conventional adaptive filter must be large. The length of the adaptive filter will directly affect both the degree of accuracy and the convergence speed of the adaptation process. We present a new adaptive structure which is capable to deal with multiple dispersive echo paths. An adaptive filter according to the present invention includes means for storing an impulse response in a memory, the impulse response being indicative of the characteristics of a transmission line. It also includes a delay estimator for detecting ranges of samples within the impulse response having relatively large distribution of echo energy. These ranges of samples are being indicative of echoes on the transmission line. An adaptive filter has a plurality of weighted taps, each of the weighted taps having an associated tap weight value. A tap allocation/control circuit establishes the tap weight values in response to said detecting means so that only taps within the regions of relatively large distributions of echo energy are turned on. Thus, the convergence speed and the degree of estimation in the adaptation process can be improved.
Power Adaptive Feedback Communication over an Additive Individual Noise Sequence Channel
Lomnitz, Yuval; Feder, Meir
2009-01-01
We consider a real-valued additive channel with an individual unknown noise sequence. We present a simple sequential communication scheme based on the celebrated Schalkwijk-Kailath scheme, which varies the transmit power according to the power of the sequence, so that asymptotically the relation between the SNR and the rate matches the Gaussian channel capacity 1/2 log(1+SNR)for almost every noise sequence.
An Affine Combination of Adaptive Filters for Channels with Different Sparsity Levels
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M. Butsenko
2016-06-01
Full Text Available In this paper we present an affine combination strategy for two adaptive filters. One filter is designed to handle sparse impulse responses and the other one performs better if impulse response is dispersive. Filter outputs are combined using an adaptive mixing parameter and the resulting output shows a better performance than each of the combining filters separately. We also demonstrate that affine combination results in faster convergence than a convex combination of two adaptive filters.
Directory of Open Access Journals (Sweden)
Buzzi Stefano
2006-01-01
Full Text Available The problem of joint channel estimation, equalization, and multiuser detection for a multiantenna DS/CDMA system operating over a frequency-selective fading channel and adopting long aperiodic spreading codes is considered in this paper. First of all, we present several channel estimation and multiuser data detection schemes suited for multiantenna long-code DS/CDMA systems. Then, a multipass strategy, wherein the data detection and the channel estimation procedures exchange information in a recursive fashion, is introduced and analyzed for the proposed scenario. Remarkably, this strategy provides, at the price of some attendant computational complexity increase, excellent performance even when very short training sequences are transmitted, and thus couples together the conflicting advantages of both trained and blind systems, that is, good performance and no wasted bandwidth, respectively. Space-time coded systems are also considered, and it is shown that the multipass strategy provides excellent results for such systems also. Likewise, it is also shown that excellent performance is achieved also when each user adopts the same spreading code for all of its transmit antennas. The validity of the proposed procedure is corroborated by both simulation results and analytical findings. In particular, it is shown that adopting the multipass strategy results in a remarkable reduction of the channel estimation mean-square error and of the optimal length of the training sequence.
Jiang, Geng-Ming; Li, Zhao-Liang
2008-11-10
This work intercompared two Bi-directional Reflectance Distribution Function (BRDF) models, the modified Minnaert's model and the RossThick-LiSparse-R model, in the estimation of the directional emissivity in Middle Infra-Red (MIR) channel from the data acquired by the Spinning Enhanced Visible and Infra-Red Imager (SEVIRI) onboard the first Meteosat Second Generation (MSG1). The bi-directional reflectances in SEVIRI channel 4 (3.9 microm) were estimated from the combined MIR and Thermal Infra-Red (TIR) data and then were used to estimate the directional emissivity in this channel with aid of the BRDF models. The results show that: (1) Both models can relatively well describe the non-Lambertian reflective behavior of land surfaces in SEVIRI channel 4; (2) The RossThick-LiSparse-R model is better than the modified Minnaert's model in modeling the bi-directional reflectances, and the directional emissivities modeled by the modified Minnaert's model are always lower than the ones obtained by the RossThick-LiSparse-R model with averaged emissivity differences of approximately 0.01 and approximately 0.04 over the vegetated and bare areas, respectively. The use of the RossThick-LiSparse-R model in the estimation of the directional emissivity in MIR channel is recommended.
A Design-Adaptive Local Polynomial Estimator for the Errors-in-Variables Problem
Delaigle, Aurore
2009-03-01
Local polynomial estimators are popular techniques for nonparametric regression estimation and have received great attention in the literature. Their simplest version, the local constant estimator, can be easily extended to the errors-in-variables context by exploiting its similarity with the deconvolution kernel density estimator. The generalization of the higher order versions of the estimator, however, is not straightforward and has remained an open problem for the last 15 years. We propose an innovative local polynomial estimator of any order in the errors-in-variables context, derive its design-adaptive asymptotic properties and study its finite sample performance on simulated examples. We provide not only a solution to a long-standing open problem, but also provide methodological contributions to error-invariable regression, including local polynomial estimation of derivative functions.
Radaydeh, Redha Mahmoud
2013-06-01
This paper proposes a reduced-complexity downlink multi-channel assignment scheme when feedback links are capacity-limited. The system model treats the case when multiple access points are allocated to serve scheduled users in over-loaded (i.e. dense) pico/femtocell networks. It assumes that the deployed access points can be shared simultaneously and employ isotropic antenna arrays of arbitrary sizes. Moreover, they transmit their data on a common physical channel and can not coordinate their transmissions. On the other hand, each scheduled user can be served by single transmit channel from each active access point at a time, and it lacks coordination with concurrent active users. The scheme operates according to the occupancy of available transmit channels, wherein extensively occupied access points are avoided adaptively, while reducing the load of processing. The operation is linked to a target performance via controlling the observed aggregate interference from the projected set of serving points. Through the analysis, results for the scheduled user outage performance, and the average number of active access points are presented. Numerical and simulations studies clarify the gains of the proposed scheme for different operating conditions. © 2013 IEEE.
Radaydeh, Redha Mahmoud; Qaraqe, Khalid A.; Alouini, Mohamed-Slim
2013-01-01
This paper proposes a reduced-complexity downlink multi-channel assignment scheme when feedback links are capacity-limited. The system model treats the case when multiple access points are allocated to serve scheduled users in over-loaded (i.e. dense) pico/femtocell networks. It assumes that the deployed access points can be shared simultaneously and employ isotropic antenna arrays of arbitrary sizes. Moreover, they transmit their data on a common physical channel and can not coordinate their transmissions. On the other hand, each scheduled user can be served by single transmit channel from each active access point at a time, and it lacks coordination with concurrent active users. The scheme operates according to the occupancy of available transmit channels, wherein extensively occupied access points are avoided adaptively, while reducing the load of processing. The operation is linked to a target performance via controlling the observed aggregate interference from the projected set of serving points. Through the analysis, results for the scheduled user outage performance, and the average number of active access points are presented. Numerical and simulations studies clarify the gains of the proposed scheme for different operating conditions. © 2013 IEEE.
Gruneisen, Mark T.; Flanagan, Michael B.; Sickmiller, Brett A.
2017-12-01
The efficient coupling of photons from a free-space quantum channel into a single-mode optical fiber (SMF) has important implications for quantum network concepts involving SMF interfaces to quantum detectors, atomic systems, integrated photonics, and direct coupling to a fiber network. Propagation through atmospheric turbulence, however, leads to wavefront errors that degrade mode matching with SMFs. In a free-space quantum channel, this leads to photon losses in proportion to the severity of the aberration. This is particularly problematic for satellite-Earth quantum channels, where atmospheric turbulence can lead to significant wavefront errors. This report considers propagation from low-Earth orbit to a terrestrial ground station and evaluates the efficiency with which photons couple either through a circular field stop or into an SMF situated in the focal plane of the optical receiver. The effects of atmospheric turbulence on the quantum channel are calculated numerically and quantified through the quantum bit error rate and secure key generation rates in a decoy-state BB84 protocol. Numerical simulations include the statistical nature of Kolmogorov turbulence, sky radiance, and an adaptive-optics system under closed-loop control.
Dominant wave frequency and amplitude estimation for adaptive control of wave energy converters
Nguyen , Hoai-Nam; Tona , Paolino; Sabiron , Guillaume
2017-01-01
International audience; Adaptive control is of great interest for wave energy converters (WEC) due to the inherent time-varying nature of sea conditions. Robust and accurate estimation algorithms are required to improve the knowledge of the current sea state on a wave-to-wave basis in order to ensure power harvesting as close as possible to optimal behavior. In this paper, we present a simple but innovative approach for estimating the wave force dominant frequency and wave force dominant ampl...
Nonparametric adaptive estimation of linear functionals for low frequency observed Lévy processes
Kappus, Johanna
2012-01-01
For a Lévy process X having finite variation on compact sets and finite first moments, Âµ( dx) = xv( dx) is a finite signed measure which completely describes the jump dynamics. We construct kernel estimators for linear functionals of Âµ and provide rates of convergence under regularity assumptions. Moreover, we consider adaptive estimation via model selection and propose a new strategy for the data driven choice of the smoothing parameter.
ADAPTIVE PARAMETER ESTIMATION OF PERSON RECOGNITION MODEL IN A STOCHASTIC HUMAN TRACKING PROCESS
W. Nakanishi; T. Fuse; T. Ishikawa
2015-01-01
This paper aims at an estimation of parameters of person recognition models using a sequential Bayesian filtering method. In many human tracking method, any parameters of models used for recognize the same person in successive frames are usually set in advance of human tracking process. In real situation these parameters may change according to situation of observation and difficulty level of human position prediction. Thus in this paper we formulate an adaptive parameter estimation ...
Estimation of black carbon content for biomass burning aerosols from multi-channel Raman lidar data
Talianu, Camelia; Marmureanu, Luminita; Nicolae, Doina
2015-04-01
Biomass burning due to natural processes (forest fires) or anthropical activities (agriculture, thermal power stations, domestic heating) is an important source of aerosols with a high content of carbon components (black carbon and organic carbon). Multi-channel Raman lidars provide information on the spectral dependence of the backscatter and extinction coefficients, embedding information on the black carbon content. Aerosols with a high content of black carbon have large extinction coefficients and small backscatter coefficients (strong absorption), while aerosols with high content of organic carbon have large backscatter coefficients (weak absorption). This paper presents a method based on radiative calculations to estimate the black carbon content of biomass burning aerosols from 3b+2a+1d lidar signals. Data is collected at Magurele, Romania, at the cross-road of air masses coming from Ukraine, Russia and Greece, where burning events are frequent during both cold and hot seasons. Aerosols are transported in the free troposphere, generally in the 2-4 km altitude range, and reaches the lidar location after 2-3 days. Optical data are collected between 2011-2012 by a multi-channel Raman lidar and follows the quality assurance program of EARLINET. Radiative calculations are made with libRadTran, an open source radiative model developed by ESA. Validation of the retrievals is made by comparison to a co-located C-ToF Aerosol Mass Spectrometer. Keywords: Lidar, aerosols, biomass burning, radiative model, black carbon Acknowledgment: This work has been supported by grants of the Romanian National Authority for Scientific Research, Programme for Research- Space Technology and Advanced Research - STAR, project no. 39/2012 - SIAFIM, and by Romanian Partnerships in priority areas PNII implemented with MEN-UEFISCDI support, project no. 309/2014 - MOBBE
Using statistical sensitivities for adaptation of a best-estimate thermo-hydraulic simulation model
International Nuclear Information System (INIS)
Liu, X.J.; Kerner, A.; Schaefer, A.
2010-01-01
On-line adaptation of best-estimate simulations of NPP behaviour to time-dependent measurement data can be used to insure that simulations performed in parallel to plant operation develop synchronously with the real plant behaviour even over extended periods of time. This opens a range of applications including operator support in non-standard-situations, improving diagnostics and validation of measurements in real plants or experimental facilities. A number of adaptation methods have been proposed and successfully applied to control problems. However, these methods are difficult to be applied to best-estimate thermal-hydraulic codes, such as TRACE and ATHLET, with their large nonlinear differential equation systems and sophisticated time integration techniques. This paper presents techniques to use statistical sensitivity measures to overcome those problems by reducing the number of parameters subject to adaptation. It describes how to identify the most significant parameters for adaptation and how this information can be used by combining: -decomposition techniques splitting the system into a small set of component parts with clearly defined interfaces where boundary conditions can be derived from the measurement data, -filtering techniques to insure that the time frame for adaptation is meaningful, -numerical sensitivities to find minimal error conditions. The suitability of combining those techniques is shown by application to an adaptive simulation of the PKL experiment.
Directory of Open Access Journals (Sweden)
David G. Daut
2007-03-01
Full Text Available A joint source-channel decoding method is designed to accelerate the iterative log-domain sum-product decoding procedure of LDPC codes as well as to improve the reconstructed image quality. Error resilience modes are used in the JPEG2000 source codec making it possible to provide useful source decoded information to the channel decoder. After each iteration, a tentative decoding is made and the channel decoded bits are then sent to the JPEG2000 decoder. The positions of bits belonging to error-free coding passes are then fed back to the channel decoder. The log-likelihood ratios (LLRs of these bits are then modified by a weighting factor for the next iteration. By observing the statistics of the decoding procedure, the weighting factor is designed as a function of the channel condition. Results show that the proposed joint decoding methods can greatly reduce the number of iterations, and thereby reduce the decoding delay considerably. At the same time, this method always outperforms the nonsource controlled decoding method by up to 3 dB in terms of PSNR.
Directory of Open Access Journals (Sweden)
Liu Weiliang
2007-01-01
Full Text Available A joint source-channel decoding method is designed to accelerate the iterative log-domain sum-product decoding procedure of LDPC codes as well as to improve the reconstructed image quality. Error resilience modes are used in the JPEG2000 source codec making it possible to provide useful source decoded information to the channel decoder. After each iteration, a tentative decoding is made and the channel decoded bits are then sent to the JPEG2000 decoder. The positions of bits belonging to error-free coding passes are then fed back to the channel decoder. The log-likelihood ratios (LLRs of these bits are then modified by a weighting factor for the next iteration. By observing the statistics of the decoding procedure, the weighting factor is designed as a function of the channel condition. Results show that the proposed joint decoding methods can greatly reduce the number of iterations, and thereby reduce the decoding delay considerably. At the same time, this method always outperforms the nonsource controlled decoding method by up to 3 dB in terms of PSNR.
Uncertainty quantification in a chemical system using error estimate-based mesh adaption
International Nuclear Information System (INIS)
Mathelin, Lionel; Le Maitre, Olivier P.
2012-01-01
This paper describes a rigorous a posteriori error analysis for the stochastic solution of non-linear uncertain chemical models. The dual-based a posteriori stochastic error analysis extends the methodology developed in the deterministic finite elements context to stochastic discretization frameworks. It requires the resolution of two additional (dual) problems to yield the local error estimate. The stochastic error estimate can then be used to adapt the stochastic discretization. Different anisotropic refinement strategies are proposed, leading to a cost-efficient tool suitable for multi-dimensional problems of moderate stochastic dimension. The adaptive strategies allow both for refinement and coarsening of the stochastic discretization, as needed to satisfy a prescribed error tolerance. The adaptive strategies were successfully tested on a model for the hydrogen oxidation in supercritical conditions having 8 random parameters. The proposed methodologies are however general enough to be also applicable for a wide class of models such as uncertain fluid flows. (authors)
Harutyunyan, D.; Izsak, F.; van der Vegt, Jacobus J.W.; Bochev, Mikhail A.
For the adaptive solution of the Maxwell equations on three-dimensional domains with N´ed´elec edge finite element methods, we consider an implicit a posteriori error estimation technique. On each element of the tessellation an equation for the error is formulated and solved with a properly chosen
Rahimi, Afshin; Kumar, Krishna Dev; Alighanbari, Hekmat
2017-05-01
Reaction wheels, as one of the most commonly used actuators in satellite attitude control systems, are prone to malfunction which could lead to catastrophic failures. Such malfunctions can be detected and addressed in time if proper analytical redundancy algorithms such as parameter estimation and control reconfiguration are employed. Major challenges in parameter estimation include speed and accuracy of the employed algorithm. This paper presents a new approach for improving parameter estimation with adaptive unscented Kalman filter. The enhancement in tracking speed of unscented Kalman filter is achieved by systematically adapting the covariance matrix to the faulty estimates using innovation and residual sequences combined with an adaptive fault annunciation scheme. The proposed approach provides the filter with the advantage of tracking sudden changes in the system non-measurable parameters accurately. Results showed successful detection of reaction wheel malfunctions without requiring a priori knowledge about system performance in the presence of abrupt, transient, intermittent, and incipient faults. Furthermore, the proposed approach resulted in superior filter performance with less mean squared errors for residuals compared to generic and adaptive unscented Kalman filters, and thus, it can be a promising method for the development of fail-safe satellites.
Wheeled vehicle deceleration as estimation parameter of adaptive brake control system state
Directory of Open Access Journals (Sweden)
Turenko A.
2012-06-01
Full Text Available The method of stability estimation of adaptive control system with signal adjustment based on Lyapunov’s direct method that allows to take into account the nonstationarity of the basic system and non-linearity in the form of limitation on control action restriction as well as error control is stated.
DEFF Research Database (Denmark)
Wang, Yunlong; Soltani, Mohsen; Hussain, Dil muhammed Akbar
2016-01-01
, an adaptive Multiplicative Extended Kalman Filter (MEKF) for attitude estimation of Marine Satellite Tracking Antenna (MSTA) is presented with the measurement noise covariance matrix adjusted according to the norm of accelerometer measurements, which can significantly reduce the slamming influence from waves...
Zeng, X.
2015-12-01
A large number of model executions are required to obtain alternative conceptual models' predictions and their posterior probabilities in Bayesian model averaging (BMA). The posterior model probability is estimated through models' marginal likelihood and prior probability. The heavy computation burden hinders the implementation of BMA prediction, especially for the elaborated marginal likelihood estimator. For overcoming the computation burden of BMA, an adaptive sparse grid (SG) stochastic collocation method is used to build surrogates for alternative conceptual models through the numerical experiment of a synthetical groundwater model. BMA predictions depend on model posterior weights (or marginal likelihoods), and this study also evaluated four marginal likelihood estimators, including arithmetic mean estimator (AME), harmonic mean estimator (HME), stabilized harmonic mean estimator (SHME), and thermodynamic integration estimator (TIE). The results demonstrate that TIE is accurate in estimating conceptual models' marginal likelihoods. The BMA-TIE has better predictive performance than other BMA predictions. TIE has high stability for estimating conceptual model's marginal likelihood. The repeated estimated conceptual model's marginal likelihoods by TIE have significant less variability than that estimated by other estimators. In addition, the SG surrogates are efficient to facilitate BMA predictions, especially for BMA-TIE. The number of model executions needed for building surrogates is 4.13%, 6.89%, 3.44%, and 0.43% of the required model executions of BMA-AME, BMA-HME, BMA-SHME, and BMA-TIE, respectively.
He, Jing; Shi, Jin; Deng, Rui; Chen, Lin
2017-08-01
Recently, visible light communication (VLC) based on light-emitting diodes (LEDs) is considered as a candidate technology for fifth-generation (5G) communications, VLC is free of electromagnetic interference and it can simplify the integration of VLC into heterogeneous wireless networks. Due to the data rates of VLC system limited by the low pumping efficiency, small output power and narrow modulation bandwidth, visible laser light communication (VLLC) system with laser diode (LD) has paid more attention. In addition, orthogonal frequency division multiplexing/offset quadrature amplitude modulation (OFDM/OQAM) is currently attracting attention in optical communications. Due to the non-requirement of cyclic prefix (CP) and time-frequency domain well-localized pulse shapes, it can achieve high spectral efficiency. Moreover, OFDM/OQAM has lower out-of-band power leakage so that it increases the system robustness against inter-carrier interference (ICI) and frequency offset. In this paper, a Discrete Fourier Transform (DFT)-based channel estimation scheme combined with the interference approximation method (IAM) is proposed and experimentally demonstrated for VLLC OFDM/OQAM system. The performance of VLLC OFDM/OQAM system with and without DFT-based channel estimation is investigated. Moreover, the proposed DFT-based channel estimation scheme and the intra-symbol frequency-domain averaging (ISFA)-based method are also compared for the VLLC OFDM/OQAM system. The experimental results show that, the performance of EVM using the DFT-based channel estimation scheme is improved about 3dB compared with the conventional IAM method. In addition, the DFT-based channel estimation scheme can resist the channel noise effectively than that of the ISFA-based method.
Radaydeh, Redha Mahmoud
2012-10-19
Overlaid cellular technology has been considered as a promising candidate to enhance the capacity and extend the coverage of cellular networks, particularly indoors. The deployment of small cells (e.g. femtocells and/or picocells) in an overlaid setup is expected to reduce the operational power and to function satisfactorily with the existing cellular architecture. Among the possible deployments of small-cell access points is to manage many of them to serve specific spatial locations, while reusing the available spectrum universally. This contribution considers the aforementioned scenario with the objective to serve as many active users as possible when the available downlink spectrum is overloaded. The case study is motivated by the importance of realizing universal resource sharing in overlaid networks, while reducing the load of distributing available resources, satisfying downlink multi-channel assignment, controlling the aggregate level of interference, and maintaining desired design/operation requirements. These objectives need to be achieved in distributed manner in each spatial space with as low processing load as possible when the feedback links are capacity-limited, multiple small-cell access points can be shared, and data exchange between access points can not be coordinated. This contribution is summarized as follows. An adaptive downlink multi-channel assignment scheme when multiple co-channel and shared small-cell access points are allocated to serve active users is proposed. It is assumed that the deployed access points employ isotropic antenna arrays of arbitrary sizes, operate using the open-access strategy, and transmit on shared physical channels simultaneously. Moreover, each active user can be served by a single transmit channel per each access point at a time, and can sense the concurrent interference level associated with each transmit antenna channel non-coherently. The proposed scheme aims to identify a suitable subset of transmit channels
Optimal Design of the Adaptive Normalized Matched Filter Detector using Regularized Tyler Estimators
Kammoun, Abla; Couillet, Romain; Pascal, Frederic; Alouini, Mohamed-Slim
2017-01-01
This article addresses improvements on the design of the adaptive normalized matched filter (ANMF) for radar detection. It is well-acknowledged that the estimation of the noise-clutter covariance matrix is a fundamental step in adaptive radar detection. In this paper, we consider regularized estimation methods which force by construction the eigenvalues of the covariance estimates to be greater than a positive regularization parameter ρ. This makes them more suitable for high dimensional problems with a limited number of secondary data samples than traditional sample covariance estimates. The motivation behind this work is to understand the effect and properly set the value of ρthat improves estimate conditioning while maintaining a low estimation bias. More specifically, we consider the design of the ANMF detector for two kinds of regularized estimators, namely the regularized sample covariance matrix (RSCM), the regularized Tyler estimator (RTE). The rationale behind this choice is that the RTE is efficient in mitigating the degradation caused by the presence of impulsive noises while inducing little loss when the noise is Gaussian. Based on asymptotic results brought by recent tools from random matrix theory, we propose a design for the regularization parameter that maximizes the asymptotic detection probability under constant asymptotic false alarm rates. Provided Simulations support the efficiency of the proposed method, illustrating its gain over conventional settings of the regularization parameter.
Optimal Design of the Adaptive Normalized Matched Filter Detector using Regularized Tyler Estimators
Kammoun, Abla
2017-10-25
This article addresses improvements on the design of the adaptive normalized matched filter (ANMF) for radar detection. It is well-acknowledged that the estimation of the noise-clutter covariance matrix is a fundamental step in adaptive radar detection. In this paper, we consider regularized estimation methods which force by construction the eigenvalues of the covariance estimates to be greater than a positive regularization parameter ρ. This makes them more suitable for high dimensional problems with a limited number of secondary data samples than traditional sample covariance estimates. The motivation behind this work is to understand the effect and properly set the value of ρthat improves estimate conditioning while maintaining a low estimation bias. More specifically, we consider the design of the ANMF detector for two kinds of regularized estimators, namely the regularized sample covariance matrix (RSCM), the regularized Tyler estimator (RTE). The rationale behind this choice is that the RTE is efficient in mitigating the degradation caused by the presence of impulsive noises while inducing little loss when the noise is Gaussian. Based on asymptotic results brought by recent tools from random matrix theory, we propose a design for the regularization parameter that maximizes the asymptotic detection probability under constant asymptotic false alarm rates. Provided Simulations support the efficiency of the proposed method, illustrating its gain over conventional settings of the regularization parameter.
A speed estimation unit for induction motors based on adaptive linear combiner
International Nuclear Information System (INIS)
Marei, Mostafa I.; Shaaban, Mostafa F.; El-Sattar, Ahmed A.
2009-01-01
This paper presents a new induction motor speed estimation technique, which can estimate the rotor resistance as well, from the measured voltage and current signals. Moreover, the paper utilizes a novel adaptive linear combiner (ADALINE) structure for speed and rotor resistance estimations. This structure can deal with the multi-output systems and it is called MO-ADALINE. The model of the induction motor is arranged in a linear form, in the stationary reference frame, to cope with the proposed speed estimator. There are many advantages of the proposed unit such as wide speed range capability, immunity against harmonics of measured waveforms, and precise estimation of the speed and the rotor resistance at different dynamic changes. Different types of induction motor drive systems are used to evaluate the dynamic performance and to examine the accuracy of the proposed unit for speed and rotor resistance estimation.
Directory of Open Access Journals (Sweden)
Simoens Frederik
2006-01-01
Full Text Available This paper concerns channel tracking in a multiantenna context for correlated flat-fading channels obeying a Gauss-Markov model. It is known that data-aided tracking of fast-fading channels requires a lot of pilot symbols in order to achieve sufficient accuracy, and hence decreases the spectral efficiency. To overcome this problem, we design a code-aided estimation scheme which exploits information from both the pilot symbols and the unknown coded data symbols. The algorithm is derived based on a factor graph representation of the system and application of the sum-product algorithm. The sum-product algorithm reveals how soft information from the decoder should be exploited for the purpose of estimation and how the information bits can be detected. Simulation results illustrate the effectiveness of our approach.
Error estimation for goal-oriented spatial adaptivity for the SN equations on triangular meshes
International Nuclear Information System (INIS)
Lathouwers, D.
2011-01-01
In this paper we investigate different error estimation procedures for use within a goal oriented adaptive algorithm for the S N equations on unstructured meshes. The method is based on a dual-weighted residual approach where an appropriate adjoint problem is formulated and solved in order to obtain the importance of residual errors in the forward problem on the specific goal of interest. The forward residuals and the adjoint function are combined to obtain both economical finite element meshes tailored to the solution of the target functional as well as providing error estimates. Various approximations made to make the calculation of the adjoint angular flux more economically attractive are evaluated by comparing the performance of the resulting adaptive algorithm and the quality of the error estimators when applied to two shielding-type test problems. (author)
History-based Adaptive Modulation for a Downlink Multicast Channel in OFDMA systems
DEFF Research Database (Denmark)
Wang, Haibo; Schwefel, Hans-Peter; Toftegaard, Thomas Skjødeberg
2008-01-01
In this paper we investigated the adaptive modulation strategies for Multicast service in orthogonal frequency division multiple access systems. We defined a Reward function as the performance optimization target and developed adaptive modulation strategies to maximize this Reward function....... The proposed optimization algorithm varied the instantaneous BER constraint of each mobile Multicast receiver according to its individual cumulated BER, which resulted in a significant Reward gain....
Channel Compensation for Speaker Recognition using MAP Adapted PLDA and Denoising DNNs
2016-06-21
05 Jabra Cellphone Earwrap Mic 06 Motorola Cellphone Earbud 07 Olympus Pearlcorder 08 Radio Shack Computer Desktop Mic Table 1: Mixer 1 and 2...EER and min DCF vs λ for 2cov map adapt PLDA the MAP adapted PLDA model using a λ of 0.5. The remain- ing rows demonstrate the impact of the feature...degrading perfor- mance on conversational telephone speech. To assess the per- formance impact of the denoising DNN on telephony data we evaluated the
Autonomous transmission power adaptation for multi-radio multi-channel wireless mesh networks
CSIR Research Space (South Africa)
Olwal, TO
2009-09-01
Full Text Available Multi-Radio Multi-Channel (MRMC) systems are key to power control problems in WMNs. Previous studies have emphasized through- put maximization in such systems as the main design challenge and transmission power control treated as a secondary issue...
Autonomous transmission power adaptation for multi-radio multi-channel wireless mesh networks
CSIR Research Space (South Africa)
Olwal, TO
2008-09-01
Full Text Available Multi-Radio Multi-Channel (MRMC) systems are key to power control problems in WMNs. Previous studies have emphasized throughput maximization in such systems as the main design challenge and transmission power control treated as a secondary issue...
An adaptive state of charge estimation approach for lithium-ion series-connected battery system
Peng, Simin; Zhu, Xuelai; Xing, Yinjiao; Shi, Hongbing; Cai, Xu; Pecht, Michael
2018-07-01
Due to the incorrect or unknown noise statistics of a battery system and its cell-to-cell variations, state of charge (SOC) estimation of a lithium-ion series-connected battery system is usually inaccurate or even divergent using model-based methods, such as extended Kalman filter (EKF) and unscented Kalman filter (UKF). To resolve this problem, an adaptive unscented Kalman filter (AUKF) based on a noise statistics estimator and a model parameter regulator is developed to accurately estimate the SOC of a series-connected battery system. An equivalent circuit model is first built based on the model parameter regulator that illustrates the influence of cell-to-cell variation on the battery system. A noise statistics estimator is then used to attain adaptively the estimated noise statistics for the AUKF when its prior noise statistics are not accurate or exactly Gaussian. The accuracy and effectiveness of the SOC estimation method is validated by comparing the developed AUKF and UKF when model and measurement statistics noises are inaccurate, respectively. Compared with the UKF and EKF, the developed method shows the highest SOC estimation accuracy.
A Robust Adaptive Unscented Kalman Filter for Nonlinear Estimation with Uncertain Noise Covariance.
Zheng, Binqi; Fu, Pengcheng; Li, Baoqing; Yuan, Xiaobing
2018-03-07
The Unscented Kalman filter (UKF) may suffer from performance degradation and even divergence while mismatch between the noise distribution assumed as a priori by users and the actual ones in a real nonlinear system. To resolve this problem, this paper proposes a robust adaptive UKF (RAUKF) to improve the accuracy and robustness of state estimation with uncertain noise covariance. More specifically, at each timestep, a standard UKF will be implemented first to obtain the state estimations using the new acquired measurement data. Then an online fault-detection mechanism is adopted to judge if it is necessary to update current noise covariance. If necessary, innovation-based method and residual-based method are used to calculate the estimations of current noise covariance of process and measurement, respectively. By utilizing a weighting factor, the filter will combine the last noise covariance matrices with the estimations as the new noise covariance matrices. Finally, the state estimations will be corrected according to the new noise covariance matrices and previous state estimations. Compared with the standard UKF and other adaptive UKF algorithms, RAUKF converges faster to the actual noise covariance and thus achieves a better performance in terms of robustness, accuracy, and computation for nonlinear estimation with uncertain noise covariance, which is demonstrated by the simulation results.
Errors in the estimation method for the rejection of vibrations in adaptive optics systems
Kania, Dariusz
2017-06-01
In recent years the problem of the mechanical vibrations impact in adaptive optics (AO) systems has been renewed. These signals are damped sinusoidal signals and have deleterious effect on the system. One of software solutions to reject the vibrations is an adaptive method called AVC (Adaptive Vibration Cancellation) where the procedure has three steps: estimation of perturbation parameters, estimation of the frequency response of the plant, update the reference signal to reject/minimalize the vibration. In the first step a very important problem is the estimation method. A very accurate and fast (below 10 ms) estimation method of these three parameters has been presented in several publications in recent years. The method is based on using the spectrum interpolation and MSD time windows and it can be used to estimate multifrequency signals. In this paper the estimation method is used in the AVC method to increase the system performance. There are several parameters that affect the accuracy of obtained results, e.g. CiR - number of signal periods in a measurement window, N - number of samples in the FFT procedure, H - time window order, SNR, b - number of ADC bits, γ - damping ratio of the tested signal. Systematic errors increase when N, CiR, H decrease and when γ increases. The value for systematic error is approximately 10^-10 Hz/Hz for N = 2048 and CiR = 0.1. This paper presents equations that can used to estimate maximum systematic errors for given values of H, CiR and N before the start of the estimation process.
The Joint Adaptive Kalman Filter (JAKF) for Vehicle Motion State Estimation.
Gao, Siwei; Liu, Yanheng; Wang, Jian; Deng, Weiwen; Oh, Heekuck
2016-07-16
This paper proposes a multi-sensory Joint Adaptive Kalman Filter (JAKF) through extending innovation-based adaptive estimation (IAE) to estimate the motion state of the moving vehicles ahead. JAKF views Lidar and Radar data as the source of the local filters, which aims to adaptively adjust the measurement noise variance-covariance (V-C) matrix 'R' and the system noise V-C matrix 'Q'. Then, the global filter uses R to calculate the information allocation factor 'β' for data fusion. Finally, the global filter completes optimal data fusion and feeds back to the local filters to improve the measurement accuracy of the local filters. Extensive simulation and experimental results show that the JAKF has better adaptive ability and fault tolerance. JAKF enables one to bridge the gap of the accuracy difference of various sensors to improve the integral filtering effectivity. If any sensor breaks down, the filtered results of JAKF still can maintain a stable convergence rate. Moreover, the JAKF outperforms the conventional Kalman filter (CKF) and the innovation-based adaptive Kalman filter (IAKF) with respect to the accuracy of displacement, velocity, and acceleration, respectively.
Channel modelling for free-space optical inter-HAP links using adaptive ARQ transmission
Parthasarathy, S.; Giggenbach, D.; Kirstädter, A.
2014-10-01
Free-space optical (FSO) communication systems have seen significant developments in recent years due to growing need for very high data rates and tap-proof communication. The operation of an FSO link is suited to diverse variety of applications such as satellites, High Altitude Platforms (HAPs), Unmanned Aerial Vehicles (UAVs), aircrafts, ground stations and other areas involving both civil and military situations. FSO communication systems face challenges due to different effects of the atmospheric channel. FSO channel primarily suffers from scintillation effects due to Index of Refraction Turbulence (IRT). In addition, acquisition and pointing becomes more difficult because of the high directivity of the transmitted beam: Miss-pointing of the transmitted beam and tracking errors at the receiver generate additional fading of the optical signal. High Altitude Platforms (HAPs) are quasi-stationary vehicles operating in the stratosphere. The slowly varying but precisely determined time-of-flight of the Inter-HAP channel adds to its characteristics. To propose a suitable ARQ scheme, proper theoretical understanding of the optical atmospheric propagation and modeling of a specific scenario FSO channel is required. In this paper, a bi-directional symmetrical Inter-HAP link has been selected and modeled. The Inter-HAP channel model is then investigated via simulations in terms of optical scintillation induced by IRT and in presence of pointing error. The performance characteristic of the model is then quantified in terms of fading statistics from which the Packet Error Probability (PEP) is calculated. Based on the PEP characteristics, we propose suitable ARQ schemes.
Directory of Open Access Journals (Sweden)
Masoumeh Soflaei
2014-01-01
Full Text Available One of the most important problems of reliable communications in shallow water channels is intersymbol interference (ISI which is due to scattering from surface and reflecting from bottom. Using adaptive equalizers in receiver is one of the best suggested ways for overcoming this problem. In this paper, we apply the family of selective regressor affine projection algorithms (SR-APA and the family of selective partial update APA (SPU-APA which have low computational complexity that is one of the important factors that influences adaptive equalizer performance. We apply experimental data from Strait of Hormuz for examining the efficiency of the proposed methods over shallow water channel. We observe that the values of the steady-state mean square error (MSE of SR-APA and SPU-APA decrease by 5.8 (dB and 5.5 (dB, respectively, in comparison with least mean square (LMS algorithm. Also the families of SPU-APA and SR-APA have better convergence speed than LMS type algorithm.
Wang, Xinrui; Fitts, Robert H
2017-08-01
Regular exercise training is known to affect the action potential duration (APD) and improve heart function, but involvement of β-adrenergic receptor (β-AR) subtypes and/or the ATP-sensitive K + (K ATP ) channel is unknown. To address this, female and male Sprague-Dawley rats were randomly assigned to voluntary wheel-running or control groups; they were anesthetized after 6-8 wk of training, and myocytes were isolated. Exercise training significantly increased APD of apex and base myocytes at 1 Hz and decreased APD at 10 Hz. Ca 2+ transient durations reflected the changes in APD, while Ca 2+ transient amplitudes were unaffected by wheel running. The nonselective β-AR agonist isoproterenol shortened the myocyte APD, an effect reduced by wheel running. The isoproterenol-induced shortening of APD was largely reversed by the selective β 1 -AR blocker atenolol, but not the β 2 -AR blocker ICI 118,551, providing evidence that wheel running reduced the sensitivity of the β 1 -AR. At 10 Hz, the K ATP channel inhibitor glibenclamide prolonged the myocyte APD more in exercise-trained than control rats, implicating a role for this channel in the exercise-induced APD shortening at 10 Hz. A novel finding of this work was the dual importance of altered β 1 -AR responsiveness and K ATP channel function in the training-induced regulation of APD. Of physiological importance to the beating heart, the reduced response to adrenergic agonists would enhance cardiac contractility at resting rates, where sympathetic drive is low, by prolonging APD and Ca 2+ influx; during exercise, an increase in K ATP channel activity would shorten APD and, thus, protect the heart against Ca 2+ overload or inadequate filling. NEW & NOTEWORTHY Our data demonstrated that regular exercise prolonged the action potential and Ca 2+ transient durations in myocytes isolated from apex and base regions at 1-Hz and shortened both at 10-Hz stimulation. Novel findings were that wheel running shifted the
Yambe, Kiyoyuki; Saito, Hidetoshi
2017-12-01
When the working gas of an atmospheric-pressure non-equilibrium (cold) plasma flows into free space, the diameter of the resulting flow channel changes continuously. The shape of the channel is observed through the light emitted by the working gas of the atmospheric-pressure plasma. When the plasma jet forms a conical shape, the diameter of the cylindrical shape, which approximates the conical shape, defines the diameter of the flow channel. When the working gas flows into the atmosphere from the inside of a quartz tube, the gas mixes with air. The molar ratio of the working gas and air is estimated from the corresponding volume ratio through the relationship between the diameter of the cylindrical plasma channel and the inner diameter of the quartz tube. The Reynolds number is calculated from the kinematic viscosity of the mixed gas and the molar ratio. The gas flow rates for the upper limit of laminar flow and the lower limit of turbulent flow are determined by the corresponding Reynolds numbers estimated from the molar ratio. It is confirmed that the plasma jet length and the internal plasma length associated with strong light emission increase with the increasing gas flow rate until the rate for the upper limit of laminar flow and the lower limit of turbulent flow, respectively. Thus, we are able to explain the increasing trend in the plasma lengths with the diameter of the flow channel and the molar ratio by using the cylindrical approximation.
Adaptive estimation for control of uncertain nonlinear systems with applications to target tracking
Madyastha, Venkatesh Kattigari
2005-08-01
Design of nonlinear observers has received considerable attention since the early development of methods for linear state estimation. The most popular approach is the extended Kalman filter (EKF), that goes through significant degradation in the presence of nonlinearities, particularly if unmodeled dynamics are coupled to the process and the measurement. For uncertain nonlinear systems, adaptive observers have been introduced to estimate the unknown state variables where no priori information about the unknown parameters is available. While establishing global results, these approaches are applicable only to systems transformable to output feedback form. Over the recent years, neural network (NN) based identification and estimation schemes have been proposed that relax the assumptions on the system at the price of sacrificing on the global nature of the results. However, most of the NN based adaptive observer approaches in the literature require knowledge of the full dimension of the system, therefore may not be suitable for systems with unmodeled dynamics. We first propose a novel approach to nonlinear state estimation from the perspective of augmenting a linear time invariant observer with an adaptive element. The class of nonlinear systems treated here are finite but of otherwise unknown dimension. The objective is to improve the performance of the linear observer when applied to a nonlinear system. The approach relies on the ability of the NNs to approximate the unknown dynamics from finite time histories of available measurements. Next we investigate nonlinear state estimation from the perspective of adaptively augmenting an existing time varying observer, such as an EKF. EKFs find their applications mostly in target tracking problems. The proposed approaches are robust to unmodeled dynamics, including unmodeled disturbances. Lastly, we consider the problem of adaptive estimation in the presence of feedback control for a class of uncertain nonlinear systems
LDPC code decoding adapted to the precoded partial response magnetic recording channels
International Nuclear Information System (INIS)
Lee, Jun; Kim, Kyuyong; Lee, Jaejin; Yang, Gijoo
2004-01-01
We propose a signal processing technique using LDPC (low-density parity-check) code instead of PRML (partial response maximum likelihood) system for the longitudinal magnetic recording channel. The scheme is designed by the precoder admitting level detection at the receiver-end and modifying the likelihood function for LDPC code decoding. The scheme can be collaborated with other decoder for turbo-like systems. The proposed algorithm can contribute to improve the performance of the conventional turbo-like systems
LDPC code decoding adapted to the precoded partial response magnetic recording channels
Energy Technology Data Exchange (ETDEWEB)
Lee, Jun E-mail: leejun28@sait.samsung.co.kr; Kim, Kyuyong; Lee, Jaejin; Yang, Gijoo
2004-05-01
We propose a signal processing technique using LDPC (low-density parity-check) code instead of PRML (partial response maximum likelihood) system for the longitudinal magnetic recording channel. The scheme is designed by the precoder admitting level detection at the receiver-end and modifying the likelihood function for LDPC code decoding. The scheme can be collaborated with other decoder for turbo-like systems. The proposed algorithm can contribute to improve the performance of the conventional turbo-like systems.
Channel Estimation on the (EW RLS Algorithm Model of MIMO OFDM in Wireless Communication
Directory of Open Access Journals (Sweden)
Sarnin Suzi Seroja
2016-01-01
(correspond to different mobility speeds and Monte Carlo simulations are performed and the MSE and BER performance versus SNR are obtained by averaging over 10000 channel realization. For comparisons, the BER performance is also presented for perfectly known channel at the receiver. In all the simulations, perfect synchronization between the transmitter and the receiver is assumed.
International Nuclear Information System (INIS)
Zhao Huidong; Hei Yong; Qiao Shushan; Ye Tianchun
2012-01-01
An optimized channel estimation algorithm based on a time-spread structure in OFDM low-voltage power line communication (PLC) systems is proposed to achieve a lower bit error rate (BER). This paper optimizes the best maximum multi-path delay of the linear minimum mean square error (LMMSE) algorithm in time-domain spread OFDM systems. Simulation results indicate that the BER of the improved method is lower than that of conventional LMMSE algorithm, especially when the signal-to-noise ratio (SNR) is lower than 0 dB. Both the LMMSE algorithm and the proposed algorithm are implemented and fabricated in CSMC 0.18 μm technology. This paper analyzes and compares the hardware complexity and performance of the two algorithms. Measurements indicate that the proposed channel estimator has better performance than the conventional estimator.
A Robust Parametric Technique for Multipath Channel Estimation in the Uplink of a DS-CDMA System
Directory of Open Access Journals (Sweden)
2006-01-01
Full Text Available The problem of estimating the multipath channel parameters of a new user entering the uplink of an asynchronous direct sequence-code division multiple access (DS-CDMA system is addressed. The problem is described via a least squares (LS cost function with a rich structure. This cost function, which is nonlinear with respect to the time delays and linear with respect to the gains of the multipath channel, is proved to be approximately decoupled in terms of the path delays. Due to this structure, an iterative procedure of 1D searches is adequate for time delays estimation. The resulting method is computationally efficient, does not require any specific pilot signal, and performs well for a small number of training symbols. Simulation results show that the proposed technique offers a better estimation accuracy compared to existing related methods, and is robust to multiple access interference.
New model and field data on estimates of Antarctic Bottom Water flow through the deep Vema Channel
Frey, D. I.; Fomin, V. V.; Diansky, N. A.; Morozov, E. G.; Neiman, V. G.
2017-05-01
We used a numerical model of the ocean circulation with a high spatial resolution to obtain estimates of the kinematic characteristics of Antarctic Bottom Water flow through the abyssal Vema Channel in the southwestern part of the Atlantic Ocean. The results of simulations correspond to the data of direct velocity measurements made at several locations in the channel. The high horizontal and vertical resolution of the model in the bottom layer allowed us to study in detail the hydrodynamics of this flow over its entire length.
Reliable channel-adapted error correction: Bacon-Shor code recovery from amplitude damping
Á. Piedrafita (Álvaro); J.M. Renes (Joseph)
2017-01-01
textabstractWe construct two simple error correction schemes adapted to amplitude damping noise for Bacon-Shor codes and investigate their prospects for fault-tolerant implementation. Both consist solely of Clifford gates and require far fewer qubits, relative to the standard method, to achieve
Adaptive Hybrid Control of Vehicle Semiactive Suspension Based on Road Profile Estimation
Directory of Open Access Journals (Sweden)
Yechen Qin
2015-01-01
Full Text Available A new road estimation based suspension hybrid control strategy is proposed. Its aim is to adaptively change control gains to improve both ride comfort and road handling with the constraint of rattle space. To achieve this, analytical expressions for ride comfort, road handling, and rattle space with respect to road input are derived based on the hybrid control, and the problem is transformed into a MOOP (Multiobjective Optimization Problem and has been solved by NSGA-II (Nondominated Sorting Genetic Algorithm-II. A new road estimation and classification method, which is based on ANFIS (Adaptive Neurofuzzy Inference System and wavelet transforms, is then presented as a means of detecting the road profile level, and a Kalman filter is designed for observing unknown states. The results of simulations conducted with random road excitation show that the efficiency of the proposed control strategy compares favourably to that of a passive system.
International Nuclear Information System (INIS)
Wang Baosheng; Wang Dongqing; Zhang Jianmin; Jiang Jing
2012-01-01
In order to estimate the functional failure probability of passive systems, an innovative adaptive importance sampling methodology is presented. In the proposed methodology, information of variables is extracted with some pre-sampling of points in the failure region. An important sampling density is then constructed from the sample distribution in the failure region. Taking the AP1000 passive residual heat removal system as an example, the uncertainties related to the model of a passive system and the numerical values of its input parameters are considered in this paper. And then the probability of functional failure is estimated with the combination of the response surface method and adaptive importance sampling method. The numerical results demonstrate the high computed efficiency and excellent computed accuracy of the methodology compared with traditional probability analysis methods. (authors)
Language Adaptation for Extending Post-Editing Estimates for Closely Related Languages
Directory of Open Access Journals (Sweden)
Rios Miguel
2016-10-01
Full Text Available This paper presents an open-source toolkit for predicting human post-editing efforts for closely related languages. At the moment, training resources for the Quality Estimation task are available for very few language directions and domains. Available resources can be expanded on the assumption that MT errors and the amount of post-editing required to correct them are comparable across related languages, even if the feature frequencies differ. In this paper we report a toolkit for achieving language adaptation, which is based on learning new feature representation using transfer learning methods. In particular, we report performance of a method based on Self-Taught Learning which adapts the English-Spanish pair to produce Quality Estimation models for translation from English into Portuguese, Italian and other Romance languages using the publicly available Autodesk dataset.
A self-adaptive genetic algorithm to estimate JA model parameters considering minor loops
Energy Technology Data Exchange (ETDEWEB)
Lu, Hai-liang; Wen, Xi-shan; Lan, Lei; An, Yun-zhu; Li, Xiao-ping
2015-01-15
A self-adaptive genetic algorithm for estimating Jiles–Atherton (JA) magnetic hysteresis model parameters is presented. The fitness function is established based on the distances between equidistant key points of normalized hysteresis loops. Linearity function and logarithm function are both adopted to code the five parameters of JA model. Roulette wheel selection is used and the selection pressure is adjusted adaptively by deducting a proportional which depends on current generation common value. The Crossover operator is established by combining arithmetic crossover and multipoint crossover. Nonuniform mutation is improved by adjusting the mutation ratio adaptively. The algorithm is used to estimate the parameters of one kind of silicon-steel sheet’s hysteresis loops, and the results are in good agreement with published data. - Highlights: • We present a method to find JA parameters for both major and minor loops. • Fitness function is based on distances between key points of normalized loops. • The selection pressure is adjusted adaptively based on generations.
A self-adaptive genetic algorithm to estimate JA model parameters considering minor loops
International Nuclear Information System (INIS)
Lu, Hai-liang; Wen, Xi-shan; Lan, Lei; An, Yun-zhu; Li, Xiao-ping
2015-01-01
A self-adaptive genetic algorithm for estimating Jiles–Atherton (JA) magnetic hysteresis model parameters is presented. The fitness function is established based on the distances between equidistant key points of normalized hysteresis loops. Linearity function and logarithm function are both adopted to code the five parameters of JA model. Roulette wheel selection is used and the selection pressure is adjusted adaptively by deducting a proportional which depends on current generation common value. The Crossover operator is established by combining arithmetic crossover and multipoint crossover. Nonuniform mutation is improved by adjusting the mutation ratio adaptively. The algorithm is used to estimate the parameters of one kind of silicon-steel sheet’s hysteresis loops, and the results are in good agreement with published data. - Highlights: • We present a method to find JA parameters for both major and minor loops. • Fitness function is based on distances between key points of normalized loops. • The selection pressure is adjusted adaptively based on generations
Speed Estimation of Induction Motor Using Model Reference Adaptive System with Kalman Filter
Directory of Open Access Journals (Sweden)
Pavel Brandstetter
2013-01-01
Full Text Available The paper deals with a speed estimation of the induction motor using observer with Model Reference Adaptive System and Kalman Filter. For simulation, Hardware in Loop Simulation method is used. The first part of the paper includes the mathematical description of the observer for the speed estimation of the induction motor. The second part describes Kalman filter. The third part describes Hardware in Loop Simulation method and its realization using multifunction card MF 624. In the last section of the paper, simulation results are shown for different changes of the induction motor speed which confirm high dynamic properties of the induction motor drive with sensorless control.
Adaptive feedforward of estimated ripple improves the closed loop system performance significantly
International Nuclear Information System (INIS)
Kwon, S.; Regan, A.; Wang, Y.M.; Rohlev, A.S.
1998-01-01
The Low Energy Demonstration Accelerator (LEDA) being constructed at Los Alamos National Laboratory will serve as the prototype for the low energy section of Acceleration Production of Tritium (APT) accelerator. This paper addresses the problem of LLRF control system for LEDA. The authors propose an estimator of the ripple and its time derivative and a control law which is based on PID control and adaptive feedforward of estimated ripple. The control law reduces the effect of the deterministic cathode ripple that is due to high voltage power supply and achieves tracking of desired set points
Pose Estimation and Adaptive Robot Behaviour for Human-Robot Interaction
DEFF Research Database (Denmark)
Svenstrup, Mikael; Hansen, Søren Tranberg; Andersen, Hans Jørgen
2009-01-01
Abstract—This paper introduces a new method to determine a person’s pose based on laser range measurements. Such estimates are typically a prerequisite for any human-aware robot navigation, which is the basis for effective and timeextended interaction between a mobile robot and a human. The robot......’s pose. The resulting pose estimates are used to identify humans who wish to be approached and interacted with. The interaction motion of the robot is based on adaptive potential functions centered around the person that respect the persons social spaces. The method is tested in experiments...
A review of some a posteriori error estimates for adaptive finite element methods
Czech Academy of Sciences Publication Activity Database
Segeth, Karel
2010-01-01
Roč. 80, č. 8 (2010), s. 1589-1600 ISSN 0378-4754. [European Seminar on Coupled Problems. Jetřichovice, 08.06.2008-13.06.2008] R&D Projects: GA AV ČR(CZ) IAA100190803 Institutional research plan: CEZ:AV0Z10190503 Keywords : hp-adaptive finite element method * a posteriori error estimators * computational error estimates Subject RIV: BA - General Mathematics Impact factor: 0.812, year: 2010 http://www.sciencedirect.com/science/article/pii/S0378475408004230
Bazile , Alban; Hachem , Elie; Larroya-Huguet , Juan-Carlos; Mesri , Youssef
2018-01-01
International audience; In this work, we present a new a posteriori error estimator based on the Variational Multiscale method for anisotropic adaptive fluid mechanics problems. The general idea is to combine the large scale error based on the solved part of the solution with the sub-mesh scale error based on the unresolved part of the solution. We compute the latter with two different methods: one using the stabilizing parameters and the other using bubble functions. We propose two different...
State of Charge Estimation of Lithium-Ion Batteries Using an Adaptive Cubature Kalman Filter
Directory of Open Access Journals (Sweden)
Bizhong Xia
2015-06-01
Full Text Available Accurate state of charge (SOC estimation is of great significance for a lithium-ion battery to ensure its safe operation and to prevent it from over-charging or over-discharging. However, it is difficult to get an accurate value of SOC since it is an inner sate of a battery cell, which cannot be directly measured. This paper presents an Adaptive Cubature Kalman filter (ACKF-based SOC estimation algorithm for lithium-ion batteries in electric vehicles. Firstly, the lithium-ion battery is modeled using the second-order resistor-capacitor (RC equivalent circuit and parameters of the battery model are determined by the forgetting factor least-squares method. Then, the Adaptive Cubature Kalman filter for battery SOC estimation is introduced and the estimated process is presented. Finally, two typical driving cycles, including the Dynamic Stress Test (DST and New European Driving Cycle (NEDC are applied to evaluate the performance of the proposed method by comparing with the traditional extended Kalman filter (EKF and cubature Kalman filter (CKF algorithms. Experimental results show that the ACKF algorithm has better performance in terms of SOC estimation accuracy, convergence to different initial SOC errors and robustness against voltage measurement noise as compared with the traditional EKF and CKF algorithms.
Polynomial Phase Estimation Based on Adaptive Short-Time Fourier Transform.
Jing, Fulong; Zhang, Chunjie; Si, Weijian; Wang, Yu; Jiao, Shuhong
2018-02-13
Polynomial phase signals (PPSs) have numerous applications in many fields including radar, sonar, geophysics, and radio communication systems. Therefore, estimation of PPS coefficients is very important. In this paper, a novel approach for PPS parameters estimation based on adaptive short-time Fourier transform (ASTFT), called the PPS-ASTFT estimator, is proposed. Using the PPS-ASTFT estimator, both one-dimensional and multi-dimensional searches and error propagation problems, which widely exist in PPSs field, are avoided. In the proposed algorithm, the instantaneous frequency (IF) is estimated by S-transform (ST), which can preserve information on signal phase and provide a variable resolution similar to the wavelet transform (WT). The width of the ASTFT analysis window is equal to the local stationary length, which is measured by the instantaneous frequency gradient (IFG). The IFG is calculated by the principal component analysis (PCA), which is robust to the noise. Moreover, to improve estimation accuracy, a refinement strategy is presented to estimate signal parameters. Since the PPS-ASTFT avoids parameter search, the proposed algorithm can be computed in a reasonable amount of time. The estimation performance, computational cost, and implementation of the PPS-ASTFT are also analyzed. The conducted numerical simulations support our theoretical results and demonstrate an excellent statistical performance of the proposed algorithm.
Channel estimation for space-time trellis coded-OFDM systems based on nonoverlapping pilot structure
CSIR Research Space (South Africa)
Sokoya, O
2008-09-01
Full Text Available . Through the analysis, two extreme conditions that produce the largest minimum determinant for a STTC-OFDM over multiple-tap channels were pointed out. The analysis show that the performance of the STTC-OFDM under various channel condition is based on...: 1) the minimum determinant tap delay of the channel and 2) the memory order of the STTC. New STTC-OFDM schemes were later designed in [2] taking into account some of the designed criteria shown in [1]. The STTC-OFDM schemes are capable...
Lubey, D.; Scheeres, D.
Tracking objects in Earth orbit is fraught with complications. This is due to the large population of orbiting spacecraft and debris that continues to grow, passive (i.e. no direct communication) and data-sparse observations, and the presence of maneuvers and dynamics mismodeling. Accurate orbit determination in this environment requires an algorithm to capture both a system's state and its state dynamics in order to account for mismodelings. Previous studies by the authors yielded an algorithm called the Optimal Control Based Estimator (OCBE) - an algorithm that simultaneously estimates a system's state and optimal control policies that represent dynamic mismodeling in the system for an arbitrary orbit-observer setup. The stochastic properties of these estimated controls are then used to determine the presence of mismodelings (maneuver detection), as well as characterize and reconstruct the mismodelings. The purpose of this paper is to develop the OCBE into an accurate real-time orbit tracking and maneuver detection algorithm by automating the algorithm and removing its linear assumptions. This results in a nonlinear adaptive estimator. In its original form the OCBE had a parameter called the assumed dynamic uncertainty, which is selected by the user with each new measurement to reflect the level of dynamic mismodeling in the system. This human-in-the-loop approach precludes real-time application to orbit tracking problems due to their complexity. This paper focuses on the Adaptive OCBE, a version of the estimator where the assumed dynamic uncertainty is chosen automatically with each new measurement using maneuver detection results to ensure that state uncertainties are properly adjusted to account for all dynamic mismodelings. The paper also focuses on a nonlinear implementation of the estimator. Originally, the OCBE was derived from a nonlinear cost function then linearized about a nominal trajectory, which is assumed to be ballistic (i.e. the nominal optimal
International Nuclear Information System (INIS)
Ye, Min; Guo, Hui; Cao, Binggang
2017-01-01
Highlights: • Propose an improved adaptive particle swarm filter method. • The SoC estimation method for the battery based on the adaptive particle swarm filter is presented. • The algorithm is validated by the case study of different aged extent batteries. • The effectiveness and applicability of the algorithm are validated by the LiPB batteries. - Abstract: Obtaining accurate parameters, state of charge (SoC) and capacity of a lithium-ion battery is crucial for a battery management system, and establishing a battery model online is complex. In addition, the errors and perturbations of the battery model dramatically increase throughout the battery lifetime, making it more challenging to model the battery online. To overcome these difficulties, this paper provides three contributions: (1) To improve the robustness of the adaptive particle filter algorithm, an error analysis method is added to the traditional adaptive particle swarm algorithm. (2) An online adaptive SoC estimator based on the improved adaptive particle filter is presented; this estimator can eliminate the estimation error due to battery degradation and initial SoC errors. (3) The effectiveness of the proposed method is verified using various initial states of lithium nickel manganese cobalt oxide (NMC) cells and lithium-ion polymer (LiPB) batteries. The experimental analysis shows that the maximum errors are less than 1% for both the voltage and SoC estimations and that the convergence time of the SoC estimation decreased to 120 s.
Kratochvíla, Jiří; Jiřík, Radovan; Bartoš, Michal; Standara, Michal; Starčuk, Zenon; Taxt, Torfinn
2016-03-01
One of the main challenges in quantitative dynamic contrast-enhanced (DCE) MRI is estimation of the arterial input function (AIF). Usually, the signal from a single artery (ignoring contrast dispersion, partial volume effects and flow artifacts) or a population average of such signals (also ignoring variability between patients) is used. Multi-channel blind deconvolution is an alternative approach avoiding most of these problems. The AIF is estimated directly from the measured tracer concentration curves in several tissues. This contribution extends the published methods of multi-channel blind deconvolution by applying a more realistic model of the impulse residue function, the distributed capillary adiabatic tissue homogeneity model (DCATH). In addition, an alternative AIF model is used and several AIF-scaling methods are tested. The proposed method is evaluated on synthetic data with respect to the number of tissue regions and to the signal-to-noise ratio. Evaluation on clinical data (renal cell carcinoma patients before and after the beginning of the treatment) gave consistent results. An initial evaluation on clinical data indicates more reliable and less noise sensitive perfusion parameter estimates. Blind multi-channel deconvolution using the DCATH model might be a method of choice for AIF estimation in a clinical setup. © 2015 Wiley Periodicals, Inc.
Vera-Sánchez, Juan Antonio; Ruiz-Morales, Carmen; González-López, Antonio
2018-03-01
To provide a multi-stage model to calculate uncertainty in radiochromic film dosimetry with Monte-Carlo techniques. This new approach is applied to single-channel and multichannel algorithms. Two lots of Gafchromic EBT3 are exposed in two different Varian linacs. They are read with an EPSON V800 flatbed scanner. The Monte-Carlo techniques in uncertainty analysis provide a numerical representation of the probability density functions of the output magnitudes. From this numerical representation, traditional parameters of uncertainty analysis as the standard deviations and bias are calculated. Moreover, these numerical representations are used to investigate the shape of the probability density functions of the output magnitudes. Also, another calibration film is read in four EPSON scanners (two V800 and two 10000XL) and the uncertainty analysis is carried out with the four images. The dose estimates of single-channel and multichannel algorithms show a Gaussian behavior and low bias. The multichannel algorithms lead to less uncertainty in the final dose estimates when the EPSON V800 is employed as reading device. In the case of the EPSON 10000XL, the single-channel algorithms provide less uncertainty in the dose estimates for doses higher than four Gy. A multi-stage model has been presented. With the aid of this model and the use of the Monte-Carlo techniques, the uncertainty of dose estimates for single-channel and multichannel algorithms are estimated. The application of the model together with Monte-Carlo techniques leads to a complete characterization of the uncertainties in radiochromic film dosimetry. Copyright © 2018 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.
International Nuclear Information System (INIS)
Yasin, M; Akhtar, Pervez; Pathan, Amir Hassan
2013-01-01
In this paper, we analyze the performance of adaptive blind algorithms – i.e. Kaiser Constant Modulus Algorithm (KCMA), Hamming CMA (HAMCMA) – with CMA in a wireless cellular communication system using digital modulation technique. These blind algorithms are used in digital signal processor of adaptive antenna to make it smart and change weights of the antenna array system dynamically. The simulation results revealed that KCMA and HAMCMA provide minimum mean square error (MSE) with 1.247 dB and 1.077 dB antenna gain enhancement, 75% reduction in bit error rate (BER) respectively over that of CMA. Therefore, KCMA and HAMCMA algorithms give a cost effective solution for a communication system
Khan, Fahd Ahmed; Chen, Yunfei; Alouini, Mohamed-Slim
2012-01-01
history in the receivers. The decision history is also incorporated in the existing Euclidean metric to improve its performance. Simulation results show that, for 16-quadrature-amplitude-modulation in a Rayleigh fading channel, a performance gain of up
Energy-efficient power allocation of two-hop cooperative systems with imperfect channel estimation
Amin, Osama; Bedeer, Ebrahim; Ahmed, Mohamed H.; Dobre, Octavia A.; Alouini, Mohamed-Slim
2015-01-01
an accurate EE metric for cooperative two-hop systems that use the amplify-and-forward relaying scheme. Different from the existing research that assumes the availability of perfect channel state information (CSI) at the communication cooperative nodes, we
Efficient optimal joint channel estimation and data detection for massive MIMO systems
Alshamary, Haider Ali Jasim; Xu, Weiyu
2016-01-01
show that the expected complexity of our algorithm grows polynomially in the channel coherence time. Simulation results demonstrate significant performance gains of our algorithm compared with suboptimal non-coherent detection algorithms. To the best
Adaptive OFDM Radar Waveform Design for Improved Micro-Doppler Estimation
Energy Technology Data Exchange (ETDEWEB)
Sen, Satyabrata [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Center for Engineering Science Advanced Research, Computer Science and Mathematics Division
2014-07-01
Here we analyze the performance of a wideband orthogonal frequency division multiplexing (OFDM) signal in estimating the micro-Doppler frequency of a rotating target having multiple scattering centers. The use of a frequency-diverse OFDM signal enables us to independently analyze the micro-Doppler characteristics with respect to a set of orthogonal subcarrier frequencies. We characterize the accuracy of micro-Doppler frequency estimation by computing the Cramer-Rao bound (CRB) on the angular-velocity estimate of the target. Additionally, to improve the accuracy of the estimation procedure, we formulate and solve an optimization problem by minimizing the CRB on the angular-velocity estimate with respect to the OFDM spectral coefficients. We present several numerical examples to demonstrate the CRB variations with respect to the signal-to-noise ratios, number of temporal samples, and number of OFDM subcarriers. We also analysed numerically the improvement in estimation accuracy due to the adaptive waveform design. A grid-based maximum likelihood estimation technique is applied to evaluate the corresponding mean-squared error performance.
Channel Simulation in Quantum Metrology
Directory of Open Access Journals (Sweden)
Laurenza Riccardo
2018-04-01
Full Text Available In this review we discuss how channel simulation can be used to simplify the most general protocols of quantum parameter estimation, where unlimited entanglement and adaptive joint operations may be employed. Whenever the unknown parameter encoded in a quantum channel is completely transferred in an environmental program state simulating the channel, the optimal adaptive estimation cannot beat the standard quantum limit. In this setting, we elucidate the crucial role of quantum teleportation as a primitive operation which allows one to completely reduce adaptive protocols over suitable teleportation-covariant channels and derive matching upper and lower bounds for parameter estimation. For these channels,wemay express the quantum Cramér Rao bound directly in terms of their Choi matrices. Our review considers both discrete- and continuous-variable systems, also presenting some new results for bosonic Gaussian channels using an alternative sub-optimal simulation. It is an open problem to design simulations for quantum channels that achieve the Heisenberg limit.
Rajaona, Harizo; Septier, François; Armand, Patrick; Delignon, Yves; Olry, Christophe; Albergel, Armand; Moussafir, Jacques
2015-12-01
In the eventuality of an accidental or intentional atmospheric release, the reconstruction of the source term using measurements from a set of sensors is an important and challenging inverse problem. A rapid and accurate estimation of the source allows faster and more efficient action for first-response teams, in addition to providing better damage assessment. This paper presents a Bayesian probabilistic approach to estimate the location and the temporal emission profile of a pointwise source. The release rate is evaluated analytically by using a Gaussian assumption on its prior distribution, and is enhanced with a positivity constraint to improve the estimation. The source location is obtained by the means of an advanced iterative Monte-Carlo technique called Adaptive Multiple Importance Sampling (AMIS), which uses a recycling process at each iteration to accelerate its convergence. The proposed methodology is tested using synthetic and real concentration data in the framework of the Fusion Field Trials 2007 (FFT-07) experiment. The quality of the obtained results is comparable to those coming from the Markov Chain Monte Carlo (MCMC) algorithm, a popular Bayesian method used for source estimation. Moreover, the adaptive processing of the AMIS provides a better sampling efficiency by reusing all the generated samples.
Adaptive order search and tangent-weighted trade-off for motion estimation in H.264
Directory of Open Access Journals (Sweden)
Srinivas Bachu
2018-04-01
Full Text Available Motion estimation and compensation play a major role in video compression to reduce the temporal redundancies of the input videos. A variety of block search patterns have been developed for matching the blocks with reduced computational complexity, without affecting the visual quality. In this paper, block motion estimation is achieved through integrating the square as well as the hexagonal search patterns with adaptive order. The proposed algorithm is called, AOSH (Adaptive Order Square Hexagonal Search algorithm, and it finds the best matching block with a reduced number of search points. The searching function is formulated as a trade-off criterion here. Hence, the tangent-weighted function is newly developed to evaluate the matching point. The proposed AOSH search algorithm and the tangent-weighted trade-off criterion are effectively applied to the block estimation process to enhance the visual quality and the compression performance. The proposed method is validated using three videos namely, football, garden and tennis. The quantitative performance of the proposed method and the existing methods is analysed using the Structural SImilarity Index (SSIM and the Peak Signal to Noise Ratio (PSNR. The results prove that the proposed method offers good visual quality than the existing methods. Keywords: Block motion estimation, Square search, Hexagon search, H.264, Video coding
Yi, J.; Choi, C.
2014-12-01
Rainfall observation and forecasting using remote sensing such as RADAR(Radio Detection and Ranging) and satellite images are widely used to delineate the increased damage by rapid weather changeslike regional storm and flash flood. The flood runoff was calculated by using adaptive neuro-fuzzy inference system, the data driven models and MAPLE(McGill Algorithm for Precipitation Nowcasting by Lagrangian Extrapolation) forecasted precipitation data as the input variables.The result of flood estimation method using neuro-fuzzy technique and RADAR forecasted precipitation data was evaluated by comparing it with the actual data.The Adaptive Neuro Fuzzy method was applied to the Chungju Reservoir basin in Korea. The six rainfall events during the flood seasons in 2010 and 2011 were used for the input data.The reservoir inflow estimation results were comparedaccording to the rainfall data used for training, checking and testing data in the model setup process. The results of the 15 models with the combination of the input variables were compared and analyzed. Using the relatively larger clustering radius and the biggest flood ever happened for training data showed the better flood estimation in this study.The model using the MAPLE forecasted precipitation data showed better result for inflow estimation in the Chungju Reservoir.
International Nuclear Information System (INIS)
Yashiki, Taturou; Yagawa, Genki; Okuda, Hiroshi
1995-01-01
The adaptive finite element method based on an 'a posteriori error estimation' is known to be a powerful technique for analyzing the engineering practical problems, since it excludes the instinctive aspect of the mesh subdivision and gives high accuracy with relatively low computational cost. In the adaptive procedure, both the error estimation and the mesh generation according to the error estimator are essential. In this paper, the adaptive procedure is realized by the automatic mesh generation based on the control of node density distribution, which is decided according to the error estimator. The global percentage error, CPU time, the degrees of freedom and the accuracy of the solution of the adaptive procedure are compared with those of the conventional method using regular meshes. Such numerical examples as the driven cavity flows of various Reynolds numbers and the flows around a cylinder have shown the very high performance of the proposed adaptive procedure. (author)
Park, Kihong
2013-04-01
In this paper, we consider resource allocation method in the visible light communication. It is challenging to achieve high data rate due to the limited bandwidth of the optical sources. In order to increase the spectral efficiency, we design a suitable multiple-input multiple-output (MIMO) system utilizing spatial multiplexing based on singular value decomposition and adaptive modulation. More specifically, after explaining why the conventional allocation method in radio frequency MIMO channels cannot be applied directly to the optical intensity channels, we theoretically derive a power allocation method for an arbitrary number of transmit and receive antennas for optical wireless MIMO systems. Based on three key constraints: the nonnegativity of the intensity-modulated signal, the aggregate optical power budget, and the bit error rate requirement, we propose a novel method to allocate the optical power, the offset value, and the modulation size. Based on some selected simulation results, we show that our proposed allocation method gives a better spectral efficiency at the expense of an increased computational complexity in comparison to a simple method that allocates the optical power equally among all the data streams. © 2013 IEEE.
Park, Kihong; Ko, Youngchai; Alouini, Mohamed-Slim
2013-01-01
In this paper, we consider resource allocation method in the visible light communication. It is challenging to achieve high data rate due to the limited bandwidth of the optical sources. In order to increase the spectral efficiency, we design a suitable multiple-input multiple-output (MIMO) system utilizing spatial multiplexing based on singular value decomposition and adaptive modulation. More specifically, after explaining why the conventional allocation method in radio frequency MIMO channels cannot be applied directly to the optical intensity channels, we theoretically derive a power allocation method for an arbitrary number of transmit and receive antennas for optical wireless MIMO systems. Based on three key constraints: the nonnegativity of the intensity-modulated signal, the aggregate optical power budget, and the bit error rate requirement, we propose a novel method to allocate the optical power, the offset value, and the modulation size. Based on some selected simulation results, we show that our proposed allocation method gives a better spectral efficiency at the expense of an increased computational complexity in comparison to a simple method that allocates the optical power equally among all the data streams. © 2013 IEEE.
Aniba, Ghassane
2011-04-01
This paper presents an optimal adaptive modulation (AM) algorithm designed using a cross-layer approach which combines truncated automatic repeat request (ARQ) protocol and packet combining. Transmissions are performed over multiple-input multiple-output (MIMO) Nakagami fading channels, and retransmitted packets are not necessarily modulated using the same modulation format as in the initial transmission. Compared to traditional approach, cross-layer design based on the coupling across the physical and link layers, has proven to yield better performance in wireless communications. However, there is a lack for the performance analysis and evaluation of such design when the ARQ protocol is used in conjunction with packet combining. Indeed, previous works addressed the link layer performance of AM with truncated ARQ but without packet combining. In addition, previously proposed AM algorithms are not optimal and can provide poor performance when packet combining is implemented. Herein, we first show that the packet loss rate (PLR) resulting from the combining of packets modulated with different constellations can be well approximated by an exponential function. This model is then used in the design of an optimal AM algorithm for systems employing packet combining, truncated ARQ and MIMO antenna configurations, considering transmission over Nakagami fading channels. Numerical results are provided for operation with or without packet combining, and show the enhanced performance and efficiency of the proposed algorithm in comparison with existing ones. © 2011 IEEE.
Estimation of Stator winding faults in induction motors using an adaptive observer scheme
DEFF Research Database (Denmark)
Kallesøe, C. S.; Vadstrup, P.; Rasmussen, Henrik
2004-01-01
This paper addresses the subject of inter-turn short circuit estimation in the stator of an induction motor. In the paper an adaptive observer scheme is proposed. The proposed observer is capable of simultaneously estimating the speed of the motor, the amount turns involved in the short circuit...... and an expression of the current in the short circuit. Moreover the states of the motor are estimated, meaning that the magnetizing currents are made available even though a fault has happened in the motor. To be able to develop this observer, a model particular suitable for the chosen observer design, is also...... derived. The efficiency of the proposed observer is demonstrated by tests performed on a test setup with a customized designed induction motor. With this motor it is possible to simulate inter-turn short circuit faults....
Estimation of Stator Winding Faults in Induction Motors using an Adaptive Observer Scheme
DEFF Research Database (Denmark)
Kallesøe, C. S.; Vadstrup, P.; Rasmussen, Henrik
2004-01-01
This paper addresses the subject of inter-turn short circuit estimation in the stator of an induction motor. In the paper an adaptive observer scheme is proposed. The proposed observer is capable of simultaneously estimating the speed of the motor, the amount turns involved in the short circuit...... and an expression of the current in the short circuit. Moreover the states of the motor are estimated, meaning that the magnetizing currents are made available even though a fault has happened in the motor. To be able to develop this observer, a model particular suitable for the chosen observer design, is also...... derived. The efficiency of the proposed observer is demonstrated by tests performed on a test setup with a customized designed induction motor. With this motor it is possible to simulate inter-turn short circuit faults....
An Adaptive Estimation Scheme for Open-Circuit Voltage of Power Lithium-Ion Battery
Directory of Open Access Journals (Sweden)
Yun Zhang
2013-01-01
Full Text Available Open-circuit voltage (OCV is one of the most important parameters in determining state of charge (SoC of power battery. The direct measurement of it is costly and time consuming. This paper describes an adaptive scheme that can be used to derive OCV of the power battery. The scheme only uses the measurable input (terminal current and the measurable output (terminal voltage signals of the battery system and is simple enough to enable online implement. Firstly an equivalent circuit model is employed to describe the polarization characteristic and the dynamic behavior of the lithium-ion battery; the state-space representation of the electrical performance for the battery is obtained based on the equivalent circuit model. Then the implementation procedure of the adaptive scheme is given; also the asymptotic convergence of the observer error and the boundedness of all the parameter estimates are proven. Finally, experiments are carried out, and the effectiveness of the adaptive estimation scheme is validated by the experimental results.
Use of artificial neural network in estimating channel power distribution of a 220 MWe PHWR
International Nuclear Information System (INIS)
Dubey, B.P.; Chandra, A.K.; Govindarajan, G.; Jagannathan, V.; Kataria, S.K.
1998-01-01
Knowledge of the distribution of power in all the 306 channels of a Pressurised Heavy Water Reactor (PHWR) as a result of the movement of one or more of the four regulating rods is important from the operation and maintenance point view of the reactor. Conventional computer codes available for this purpose take several minutes to calculate the channel power distribution on PC-AT/486. An Artificial Neural network (ANN), based on the RPROP algorithm has been developed and employed in predicting channel power distribution of a 220 MWe Indian PHWR as a result of a perturbation caused by the movement of one or more of the four regulating rods of the reactor. The ANN based system produces the result of an analysis much faster than that produced by a conventional computer code usually employed for this application. The ANN based system is rugged, accurate and fast, and therefore, has potential to be used in real-time applications. (author)
Semantic Edge Based Disparity Estimation Using Adaptive Dynamic Programming for Binocular Sensors.
Zhu, Dongchen; Li, Jiamao; Wang, Xianshun; Peng, Jingquan; Shi, Wenjun; Zhang, Xiaolin
2018-04-03
Disparity calculation is crucial for binocular sensor ranging. The disparity estimation based on edges is an important branch in the research of sparse stereo matching and plays an important role in visual navigation. In this paper, we propose a robust sparse stereo matching method based on the semantic edges. Some simple matching costs are used first, and then a novel adaptive dynamic programming algorithm is proposed to obtain optimal solutions. This algorithm makes use of the disparity or semantic consistency constraint between the stereo images to adaptively search parameters, which can improve the robustness of our method. The proposed method is compared quantitatively and qualitatively with the traditional dynamic programming method, some dense stereo matching methods, and the advanced edge-based method respectively. Experiments show that our method can provide superior performance on the above comparison.
Modulation transfer function estimation of optical lens system by adaptive neuro-fuzzy methodology
Petković, Dalibor; Shamshirband, Shahaboddin; Pavlović, Nenad T.; Anuar, Nor Badrul; Kiah, Miss Laiha Mat
2014-07-01
The quantitative assessment of image quality is an important consideration in any type of imaging system. The modulation transfer function (MTF) is a graphical description of the sharpness and contrast of an imaging system or of its individual components. The MTF is also known and spatial frequency response. The MTF curve has different meanings according to the corresponding frequency. The MTF of an optical system specifies the contrast transmitted by the system as a function of image size, and is determined by the inherent optical properties of the system. In this study, the adaptive neuro-fuzzy (ANFIS) estimator is designed and adapted to estimate MTF value of the actual optical system. Neural network in ANFIS adjusts parameters of membership function in the fuzzy logic of the fuzzy inference system. The back propagation learning algorithm is used for training this network. This intelligent estimator is implemented using Matlab/Simulink and the performances are investigated. The simulation results presented in this paper show the effectiveness of the developed method.
Directory of Open Access Journals (Sweden)
Hongjian Wang
2014-01-01
Full Text Available We present a support vector regression-based adaptive divided difference filter (SVRADDF algorithm for improving the low state estimation accuracy of nonlinear systems, which are typically affected by large initial estimation errors and imprecise prior knowledge of process and measurement noises. The derivative-free SVRADDF algorithm is significantly simpler to compute than other methods and is implemented using only functional evaluations. The SVRADDF algorithm involves the use of the theoretical and actual covariance of the innovation sequence. Support vector regression (SVR is employed to generate the adaptive factor to tune the noise covariance at each sampling instant when the measurement update step executes, which improves the algorithm’s robustness. The performance of the proposed algorithm is evaluated by estimating states for (i an underwater nonmaneuvering target bearing-only tracking system and (ii maneuvering target bearing-only tracking in an air-traffic control system. The simulation results show that the proposed SVRADDF algorithm exhibits better performance when compared with a traditional DDF algorithm.
Wei, Zhongbao; Meng, Shujuan; Tseng, King Jet; Lim, Tuti Mariana; Soong, Boon Hee; Skyllas-Kazacos, Maria
2017-03-01
An accurate battery model is the prerequisite for reliable state estimate of vanadium redox battery (VRB). As the battery model parameters are time varying with operating condition variation and battery aging, the common methods where model parameters are empirical or prescribed offline lacks accuracy and robustness. To address this issue, this paper proposes to use an online adaptive battery model to reproduce the VRB dynamics accurately. The model parameters are online identified with both the recursive least squares (RLS) and the extended Kalman filter (EKF). Performance comparison shows that the RLS is superior with respect to the modeling accuracy, convergence property, and computational complexity. Based on the online identified battery model, an adaptive peak power estimator which incorporates the constraints of voltage limit, SOC limit and design limit of current is proposed to fully exploit the potential of the VRB. Experiments are conducted on a lab-scale VRB system and the proposed peak power estimator is verified with a specifically designed "two-step verification" method. It is shown that different constraints dominate the allowable peak power at different stages of cycling. The influence of prediction time horizon selection on the peak power is also analyzed.
Shen, Yi
2013-05-01
A subject's sensitivity to a stimulus variation can be studied by estimating the psychometric function. Generally speaking, three parameters of the psychometric function are of interest: the performance threshold, the slope of the function, and the rate at which attention lapses occur. In the present study, three psychophysical procedures were used to estimate the three-parameter psychometric function for an auditory gap detection task. These were an up-down staircase (up-down) procedure, an entropy-based Bayesian (entropy) procedure, and an updated maximum-likelihood (UML) procedure. Data collected from four young, normal-hearing listeners showed that while all three procedures provided similar estimates of the threshold parameter, the up-down procedure performed slightly better in estimating the slope and lapse rate for 200 trials of data collection. When the lapse rate was increased by mixing in random responses for the three adaptive procedures, the larger lapse rate was especially detrimental to the efficiency of the up-down procedure, and the UML procedure provided better estimates of the threshold and slope than did the other two procedures.
Directory of Open Access Journals (Sweden)
V. Jayaraj
2010-08-01
Full Text Available A Non-linear adaptive decision based algorithm with robust motion estimation technique is proposed for removal of impulse noise, Gaussian noise and mixed noise (impulse and Gaussian with edge and fine detail preservation in images and videos. The algorithm includes detection of corrupted pixels and the estimation of values for replacing the corrupted pixels. The main advantage of the proposed algorithm is that an appropriate filter is used for replacing the corrupted pixel based on the estimation of the noise variance present in the filtering window. This leads to reduced blurring and better fine detail preservation even at the high mixed noise density. It performs both spatial and temporal filtering for removal of the noises in the filter window of the videos. The Improved Cross Diamond Search Motion Estimation technique uses Least Median Square as a cost function, which shows improved performance than other motion estimation techniques with existing cost functions. The results show that the proposed algorithm outperforms the other algorithms in the visual point of view and in Peak Signal to Noise Ratio, Mean Square Error and Image Enhancement Factor.
An adaptive ARX model to estimate the RUL of aluminum plates based on its crack growth
Barraza-Barraza, Diana; Tercero-Gómez, Víctor G.; Beruvides, Mario G.; Limón-Robles, Jorge
2017-01-01
A wide variety of Condition-Based Maintenance (CBM) techniques deal with the problem of predicting the time for an asset fault. Most statistical approaches rely on historical failure data that might not be available in several practical situations. To address this issue, practitioners might require the use of self-starting approaches that consider only the available knowledge about the current degradation process and the asset operating context to update the prognostic model. Some authors use Autoregressive (AR) models for this purpose that are adequate when the asset operating context is constant, however, if it is variable, the accuracy of the models can be affected. In this paper, three autoregressive models with exogenous variables (ARX) were constructed, and their capability to estimate the remaining useful life (RUL) of a process was evaluated following the case of the aluminum crack growth problem. An existing stochastic model of aluminum crack growth was implemented and used to assess RUL estimation performance of the proposed ARX models through extensive Monte Carlo simulations. Point and interval estimations were made based only on individual history, behavior, operating conditions and failure thresholds. Both analytic and bootstrapping techniques were used in the estimation process. Finally, by including recursive parameter estimation and a forgetting factor, the ARX methodology adapts to changing operating conditions and maintain the focus on the current degradation level of an asset.
International Nuclear Information System (INIS)
Daldaban, Ferhat; Ustkoyuncu, Nurettin; Guney, Kerim
2006-01-01
A new method based on an adaptive neuro-fuzzy inference system (ANFIS) for estimating the phase inductance of switched reluctance motors (SRMs) is presented. The ANFIS has the advantages of expert knowledge of the fuzzy inference system and the learning capability of neural networks. A hybrid learning algorithm, which combines the least square method and the back propagation algorithm, is used to identify the parameters of the ANFIS. The rotor position and the phase current of the 6/4 pole SRM are used to predict the phase inductance. The phase inductance results predicted by the ANFIS are in excellent agreement with the results of the finite element method
Angular-contact ball-bearing internal load estimation algorithm using runtime adaptive relaxation
Medina, H.; Mutu, R.
2017-07-01
An algorithm to estimate internal loads for single-row angular contact ball bearings due to externally applied thrust loads and high-operating speeds is presented. A new runtime adaptive relaxation procedure and blending function is proposed which ensures algorithm stability whilst also reducing the number of iterations needed to reach convergence, leading to an average reduction in computation time in excess of approximately 80%. The model is validated based on a 218 angular contact bearing and shows excellent agreement compared to published results.
An Adaptive Nonlinear Aircraft Maneuvering Envelope Estimation Approach for Online Applications
Schuet, Stefan R.; Lombaerts, Thomas Jan; Acosta, Diana; Wheeler, Kevin; Kaneshige, John
2014-01-01
A nonlinear aircraft model is presented and used to develop an overall unified robust and adaptive approach to passive trim and maneuverability envelope estimation with uncertainty quantification. The concept of time scale separation makes this method suitable for the online characterization of altered safe maneuvering limitations after impairment. The results can be used to provide pilot feedback and/or be combined with flight planning, trajectory generation, and guidance algorithms to help maintain safe aircraft operations in both nominal and off-nominal scenarios.
Cavina-Pratesi, C; Kentridge, R W; Heywood, C A; Milner, A D
2010-10-01
Previous neuroimaging research suggests that although object shape is analyzed in the lateral occipital cortex, surface properties of objects, such as color and texture, are dealt with in more medial areas, close to the collateral sulcus (CoS). The present study sought to determine whether there is a single medial region concerned with surface properties in general or whether instead there are multiple foci independently extracting different surface properties. We used stimuli varying in their shape, texture, or color, and tested healthy participants and 2 object-agnosic patients, in both a discrimination task and a functional MR adaptation paradigm. We found a double dissociation between medial and lateral occipitotemporal cortices in processing surface (texture or color) versus geometric (shape) properties, respectively. In Experiment 2, we found that the medial occipitotemporal cortex houses separate foci for color (within anterior CoS and lingual gyrus) and texture (caudally within posterior CoS). In addition, we found that areas selective for shape, texture, and color individually were quite distinct from those that respond to all of these features together (shape and texture and color). These latter areas appear to correspond to those associated with the perception of complex stimuli such as faces and places.
Directory of Open Access Journals (Sweden)
Bahita Mohamed
2011-01-01
Full Text Available In this work, we introduce an adaptive neural network controller for a class of nonlinear systems. The approach uses two Radial Basis Functions, RBF networks. The first RBF network is used to approximate the ideal control law which cannot be implemented since the dynamics of the system are unknown. The second RBF network is used for on-line estimating the control gain which is a nonlinear and unknown function of the states. The updating laws for the combined estimator and controller are derived through Lyapunov analysis. Asymptotic stability is established with the tracking errors converging to a neighborhood of the origin. Finally, the proposed method is applied to control and stabilize the inverted pendulum system.
International Nuclear Information System (INIS)
Morio, Jerome
2011-01-01
Importance sampling (IS) is a useful simulation technique to estimate critical probability with a better accuracy than Monte Carlo methods. It consists in generating random weighted samples from an auxiliary distribution rather than the distribution of interest. The crucial part of this algorithm is the choice of an efficient auxiliary PDF that has to be able to simulate more rare random events. The optimisation of this auxiliary distribution is often in practice very difficult. In this article, we propose to approach the IS optimal auxiliary density with non-parametric adaptive importance sampling (NAIS). We apply this technique for the probability estimation of spatial launcher impact position since it has currently become a more and more important issue in the field of aeronautics.
Performance bounds on micro-Doppler estimation and adaptive waveform design using OFDM signals
Sen, Satyabrata; Barhen, Jacob; Glover, Charles W.
2014-05-01
We analyze the performance of a wideband orthogonal frequency division multiplexing (OFDM) signal in estimating the micro-Doppler frequency of a target having multiple rotating scatterers (e.g., rotor blades of a helicopter, propellers of a submarine). The presence of rotating scatterers introduces Doppler frequency modulation in the received signal by generating sidebands about the transmitted frequencies. This is called the micro-Doppler effects. The use of a frequency-diverse OFDM signal in this context enables us to independently analyze the micro-Doppler characteristics with respect to a set of orthogonal subcarrier frequencies. Therefore, to characterize the accuracy of micro-Doppler frequency estimation, we compute the Craḿer-Rao Bound (CRB) on the angular-velocity estimate of the target while considering the scatterer responses as deterministic but unknown nuisance parameters. Additionally, to improve the accuracy of the estimation procedure, we formulate and solve an optimization problem by minimizing the CRB on the angular-velocity estimate with respect to the transmitting OFDM spectral coefficients. We present several numerical examples to demonstrate the CRB variations at different values of the signal-to-noise ratio (SNR) and the number of OFDM subcarriers. The CRB values not only decrease with the increase in the SNR values, but also reduce as we increase the number of subcarriers implying the significance of frequency-diverse OFDM waveforms. The improvement in estimation accuracy due to the adaptive waveform design is also numerically analyzed. Interestingly, we find that the relative decrease in the CRBs on the angular-velocity estimate is more pronounced for larger number of OFDM subcarriers.
Performance Bounds on Micro-Doppler Estimation and Adaptive Waveform Design Using OFDM Signals
Energy Technology Data Exchange (ETDEWEB)
Sen, Satyabrata [ORNL; Barhen, Jacob [ORNL; Glover, Charles Wayne [ORNL
2014-01-01
We analyze the performance of a wideband orthogonal frequency division multiplexing (OFDM) signal in estimating the micro-Doppler frequency of a target having multiple rotating scatterers (e.g., rotor blades of a helicopter, propellers of a submarine). The presence of rotating scatterers introduces Doppler frequency modulation in the received signal by generating sidebands about the transmitted frequencies. This is called the micro-Doppler effects. The use of a frequency-diverse OFDM signal in this context enables us to independently analyze the micro-Doppler characteristics with respect to a set of orthogonal subcarrier frequencies. Therefore, to characterize the accuracy of micro-Doppler frequency estimation, we compute the Cram er-Rao Bound (CRB) on the angular-velocity estimate of the target while considering the scatterer responses as deterministic but unknown nuisance parameters. Additionally, to improve the accuracy of the estimation procedure, we formulate and solve an optimization problem by minimizing the CRB on the angular-velocity estimate with respect to the transmitting OFDM spectral coefficients. We present several numerical examples to demonstrate the CRB variations at different values of the signal-to-noise ratio (SNR) and the number of OFDM subcarriers. The CRB values not only decrease with the increase in the SNR values, but also reduce as we increase the number of subcarriers implying the significance of frequency-diverse OFDM waveforms. The improvement in estimation accuracy due to the adaptive waveform design is also numerically analyzed. Interestingly, we find that the relative decrease in the CRBs on the angular-velocity estimate is more pronounced for larger number of OFDM subcarriers.
Generation of realistic scene using illuminant estimation and mixed chromatic adaptation
Kim, Jae-Chul; Hong, Sang-Gi; Kim, Dong-Ho; Park, Jong-Hyun
2003-12-01
The algorithm of combining a real image with a virtual model was proposed to increase the reality of synthesized images. Currently, synthesizing a real image with a virtual model facilitated the surface reflection model and various geometric techniques. In the current methods, the characteristics of various illuminants in the real image are not sufficiently considered. In addition, despite the chromatic adaptation plays a vital role for accommodating different illuminants in the two media viewing conditions, it is not taken into account in the existing methods. Thus, it is hardly to get high-quality synthesized images. In this paper, we proposed the two-phase image synthesis algorithm. First, the surface reflectance of the maximum high-light region (MHR) was estimated using the three eigenvectors obtained from the principal component analysis (PCA) applied to the surface reflectances of 1269 Munsell samples. The combined spectral value, i.e., the product of surface reflectance and the spectral power distributions (SPDs) of an illuminant, of MHR was then estimated using the three eigenvectors obtained from PCA applied to the products of surface reflectances of Munsell 1269 samples and the SPDs of four CIE Standard Illuminants (A, C, D50, D65). By dividing the average combined spectral values of MHR by the average surface reflectances of MHR, we could estimate the illuminant of a real image. Second, the mixed chromatic adaptation (S-LMS) using an estimated and an external illuminants was applied to the virtual-model image. For evaluating the proposed algorithm, experiments with synthetic and real scenes were performed. It was shown that the proposed method was effective in synthesizing the real and the virtual scenes under various illuminants.
Aguirre, Erik; Lopez-Iturri, Peio; Azpilicueta, Leire; Astrain, José Javier; Villadangos, Jesús; Falcone, Francisco
2015-02-05
One of the main challenges in the implementation and design of context-aware scenarios is the adequate deployment strategy for Wireless Sensor Networks (WSNs), mainly due to the strong dependence of the radiofrequency physical layer with the surrounding media, which can lead to non-optimal network designs. In this work, radioplanning analysis for WSN deployment is proposed by employing a deterministic 3D ray launching technique in order to provide insight into complex wireless channel behavior in context-aware indoor scenarios. The proposed radioplanning procedure is validated with a testbed implemented with a Mobile Ad Hoc Network WSN following a chain configuration, enabling the analysis and assessment of a rich variety of parameters, such as received signal level, signal quality and estimation of power consumption. The adoption of deterministic radio channel techniques allows the design and further deployment of WSNs in heterogeneous wireless scenarios with optimized behavior in terms of coverage, capacity, quality of service and energy consumption.
Peterson, Harold; Koshak, William J.
2009-01-01
An algorithm has been developed to estimate the altitude distribution of one-meter lightning channel segments. The algorithm is required as part of a broader objective that involves improving the lightning NOx emission inventories of both regional air quality and global chemistry/climate models. The algorithm was tested and applied to VHF signals detected by the North Alabama Lightning Mapping Array (NALMA). The accuracy of the algorithm was characterized by comparing algorithm output to the plots of individual discharges whose lengths were computed by hand; VHF source amplitude thresholding and smoothing were applied to optimize results. Several thousands of lightning flashes within 120 km of the NALMA network centroid were gathered from all four seasons, and were analyzed by the algorithm. The mean, standard deviation, and median statistics were obtained for all the flashes, the ground flashes, and the cloud flashes. One-meter channel segment altitude distributions were also obtained for the different seasons.
International Nuclear Information System (INIS)
Taleyarkhan, R.; McFarlane, A.F.; Lahey, R.T. Jr.; Podowski, M.Z.
1988-01-01
The work described in this paper is focused on the development, verification and benchmarking of the NUFREQ-NPW code at Westinghouse, USA for best estimate prediction of multi-channel core stability margins in US BWRs. Various models incorporated into NUFREQ-NPW are systematically compared against the Westinghouse channel stability analysis code MAZDA, which the Mathematical Model was developed in an entirely different manner. The NUFREQ-NPW code is extensively benchmarked against experimental stability data with and without nuclear reactivity feedback. Detailed comparisons are next performed against nuclear-coupled core stability data. A physically based algorithm is developed to correct for the effect of flow development on subcooled boiling. Use of this algorithm (to be described in the full paper) captures the peak magnitude as well as the resonance frequency with good accuracy
Energy Technology Data Exchange (ETDEWEB)
Sheng, Zheng, E-mail: 19994035@sina.com [College of Meteorology and Oceanography, PLA University of Science and Technology, Nanjing 211101 (China); Wang, Jun; Zhou, Bihua [National Defense Key Laboratory on Lightning Protection and Electromagnetic Camouflage, PLA University of Science and Technology, Nanjing 210007 (China); Zhou, Shudao [College of Meteorology and Oceanography, PLA University of Science and Technology, Nanjing 211101 (China); Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing 210044 (China)
2014-03-15
This paper introduces a novel hybrid optimization algorithm to establish the parameters of chaotic systems. In order to deal with the weaknesses of the traditional cuckoo search algorithm, the proposed adaptive cuckoo search with simulated annealing algorithm is presented, which incorporates the adaptive parameters adjusting operation and the simulated annealing operation in the cuckoo search algorithm. Normally, the parameters of the cuckoo search algorithm are kept constant that may result in decreasing the efficiency of the algorithm. For the purpose of balancing and enhancing the accuracy and convergence rate of the cuckoo search algorithm, the adaptive operation is presented to tune the parameters properly. Besides, the local search capability of cuckoo search algorithm is relatively weak that may decrease the quality of optimization. So the simulated annealing operation is merged into the cuckoo search algorithm to enhance the local search ability and improve the accuracy and reliability of the results. The functionality of the proposed hybrid algorithm is investigated through the Lorenz chaotic system under the noiseless and noise condition, respectively. The numerical results demonstrate that the method can estimate parameters efficiently and accurately in the noiseless and noise condition. Finally, the results are compared with the traditional cuckoo search algorithm, genetic algorithm, and particle swarm optimization algorithm. Simulation results demonstrate the effectiveness and superior performance of the proposed algorithm.
A new adaptive control scheme based on the interacting multiple model (IMM) estimation
International Nuclear Information System (INIS)
Afshari, Hamed H.; Al-Ani, Dhafar; Habibi, Saeid
2016-01-01
In this paper, an Interacting multiple model (IMM) adaptive estimation approach is incorporated to design an optimal adaptive control law for stabilizing an Unmanned vehicle. Due to variations of the forward velocity of the Unmanned vehicle, its aerodynamic derivatives are constantly changing. In order to stabilize the unmanned vehicle and achieve the control objectives for in-flight conditions, one seeks for an adaptive control strategy that can adjust itself to varying flight conditions. In this context, a bank of linear models is used to describe the vehicle dynamics in different operating modes. Each operating mode represents a particular dynamic with a different forward velocity. These models are then used within an IMM filter containing a bank of Kalman filters (KF) in a parallel operating mechanism. To regulate and stabilize the vehicle, a Linear quadratic regulator (LQR) law is designed and implemented for each mode. The IMM structure determines the particular mode based on the stored models and in-flight input-output measurements. The LQR controller also provides a set of controllers; each corresponds to a particular flight mode and minimizes the tracking error. Finally, the ultimate control law is obtained as a weighted summation of all individual controllers whereas weights are obtained using mode probabilities of each operating mode.
International Nuclear Information System (INIS)
Sheng, Zheng; Wang, Jun; Zhou, Bihua; Zhou, Shudao
2014-01-01
This paper introduces a novel hybrid optimization algorithm to establish the parameters of chaotic systems. In order to deal with the weaknesses of the traditional cuckoo search algorithm, the proposed adaptive cuckoo search with simulated annealing algorithm is presented, which incorporates the adaptive parameters adjusting operation and the simulated annealing operation in the cuckoo search algorithm. Normally, the parameters of the cuckoo search algorithm are kept constant that may result in decreasing the efficiency of the algorithm. For the purpose of balancing and enhancing the accuracy and convergence rate of the cuckoo search algorithm, the adaptive operation is presented to tune the parameters properly. Besides, the local search capability of cuckoo search algorithm is relatively weak that may decrease the quality of optimization. So the simulated annealing operation is merged into the cuckoo search algorithm to enhance the local search ability and improve the accuracy and reliability of the results. The functionality of the proposed hybrid algorithm is investigated through the Lorenz chaotic system under the noiseless and noise condition, respectively. The numerical results demonstrate that the method can estimate parameters efficiently and accurately in the noiseless and noise condition. Finally, the results are compared with the traditional cuckoo search algorithm, genetic algorithm, and particle swarm optimization algorithm. Simulation results demonstrate the effectiveness and superior performance of the proposed algorithm
Directory of Open Access Journals (Sweden)
Dalei Song
2012-10-01
Full Text Available The adaptive extended set-membership filter (AESMF for nonlinear ellipsoidal estimation suffers a mismatch between real process noise and its set boundaries, which may result in unstable estimation. In this paper, a MIT method-based adaptive set-membership filter, for the optimization of the set boundaries of process noise, is developed and applied to the nonlinear joint estimation of both time-varying states and parameters. As a result of using the proposed MIT-AESMF, the estimation effectiveness and boundary accuracy of traditional AESMF are substantially improved. Simulation results have shown the efficiency and robustness of the proposed method.
Gummadi, V.; He, Y.; Beighley, E. R.
2007-12-01
Modeling fine scale spatial and temporal processes of the hydrologic cycle over continental to global extents is vital for assessing the potential impacts of climate and land use change on global water resources and related systems. Significant advancement in understanding and predicting the magnitude, trend, timing and partitioning of terrestrial water stores and fluxes requires the development of methodologies and knowledge for extracting representative hydraulic geometries from remote sensing data products and field data, suitable for estimating inundation characteristics and water storage changes which are limited for much of the globe. In this research, relationships between channel and floodplain widths and spatial drainage characteristics are developed for the Amazon Basin. Channel and floodplain widths were measured using SRTM data and LandSat TM/ETM imagery at 510 sites. The study sites were selected based on the Pfafstetter decomposition methodology which provides an irregular model grid based on repeatedly subdividing landscape units into nine subunits consisting of basins and interbasins. The selected sites encompass all possible combinations of Pfafstetter modeling units (ex., basins of interbasins, interbasins of basins, etc.). The 510 study sites are within the Amazon Basin with drainage areas ranging 10 to 5.4 million sq km and mean watershed ground slopes ranging from 0.4 and 30 percent. Preliminary results indicate that channel widths can be predicted using drainage area and mean watershed slope (R2 = 0.85). Floodplain widths can be predicted using channel width and the local slope (R2 = 0.70). Using the Purus watershed, a sub-basin to the Amazon (350,000 sq km), effects of channel and floodplain widths on simulated hydrographs are presented.
On the estimation of the worst-case implant-induced RF-heating in multi-channel MRI
Córcoles, Juan; Zastrow, Earl; Kuster, Niels
2017-06-01
The increasing use of multiple radiofrequency (RF) transmit channels in magnetic resonance imaging (MRI) systems makes it necessary to rigorously assess the risk of RF-induced heating. This risk is especially aggravated with inclusions of medical implants within the body. The worst-case RF-heating scenario is achieved when the local tissue deposition in the at-risk region (generally in the vicinity of the implant electrodes) reaches its maximum value while MRI exposure is compliant with predefined general specific absorption rate (SAR) limits or power requirements. This work first reviews the common approach to estimate the worst-case RF-induced heating in multi-channel MRI environment, based on the maximization of the ratio of two Hermitian forms by solving a generalized eigenvalue problem. It is then shown that the common approach is not rigorous and may lead to an underestimation of the worst-case RF-heating scenario when there is a large number of RF transmit channels and there exist multiple SAR or power constraints to be satisfied. Finally, this work derives a rigorous SAR-based formulation to estimate a preferable worst-case scenario, which is solved by casting a semidefinite programming relaxation of this original non-convex problem, whose solution closely approximates the true worst-case including all SAR constraints. Numerical results for 2, 4, 8, 16, and 32 RF channels in a 3T-MRI volume coil for a patient with a deep-brain stimulator under a head imaging exposure are provided as illustrative examples.
Directory of Open Access Journals (Sweden)
Dongming Li
2017-04-01
Full Text Available An adaptive optics (AO system provides real-time compensation for atmospheric turbulence. However, an AO image is usually of poor contrast because of the nature of the imaging process, meaning that the image contains information coming from both out-of-focus and in-focus planes of the object, which also brings about a loss in quality. In this paper, we present a robust multi-frame adaptive optics image restoration algorithm via maximum likelihood estimation. Our proposed algorithm uses a maximum likelihood method with image regularization as the basic principle, and constructs the joint log likelihood function for multi-frame AO images based on a Poisson distribution model. To begin with, a frame selection method based on image variance is applied to the observed multi-frame AO images to select images with better quality to improve the convergence of a blind deconvolution algorithm. Then, by combining the imaging conditions and the AO system properties, a point spread function estimation model is built. Finally, we develop our iterative solutions for AO image restoration addressing the joint deconvolution issue. We conduct a number of experiments to evaluate the performances of our proposed algorithm. Experimental results show that our algorithm produces accurate AO image restoration results and outperforms the current state-of-the-art blind deconvolution methods.
Directory of Open Access Journals (Sweden)
E. A. Feilat
2010-12-01
Full Text Available This paper demonstrates the assessment of the small-signal stability of a single-machine infinite- bus power system under widely varying loading conditions using the concept of synchronizing and damping torques coefficients. The coefficients are calculated from the time responses of the rotor angle, speed, and torque of the synchronous generator. Three adaptive computation algorithms including Kalman filtering, Adaline, and recursive least squares have been compared to estimate the synchronizing and damping torque coefficients. The steady-state performance of the three adaptive techniques is compared with the conventional static least squares technique by conducting computer simulations at different loading conditions. The algorithms are compared to each other in terms of speed of convergence and accuracy. The recursive least squares estimation offers several advantages including significant reduction in computing time and computational complexity. The tendency of an unsupplemented static exciter to degrade the system damping for medium and heavy loading is verified. Consequently, a power system stabilizer whose parameters are adjusted to compensate for variations in the system loading is designed using phase compensation method. The effectiveness of the stabilizer in enhancing the dynamic stability over wide range of operating conditions is verified through the calculation of the synchronizing and damping torque coefficients using recursive least square technique.
HIERARCHICAL ADAPTIVE ROOD PATTERN SEARCH FOR MOTION ESTIMATION AT VIDEO SEQUENCE ANALYSIS
Directory of Open Access Journals (Sweden)
V. T. Nguyen
2016-05-01
Full Text Available Subject of Research.The paper deals with the motion estimation algorithms for the analysis of video sequences in compression standards MPEG-4 Visual and H.264. Anew algorithm has been offered based on the analysis of the advantages and disadvantages of existing algorithms. Method. Thealgorithm is called hierarchical adaptive rood pattern search (Hierarchical ARPS, HARPS. This new algorithm includes the classic adaptive rood pattern search ARPS and hierarchical search MP (Hierarchical search or Mean pyramid. All motion estimation algorithms have been implemented using MATLAB package and tested with several video sequences. Main Results. The criteria for evaluating the algorithms were: speed, peak signal to noise ratio, mean square error and mean absolute deviation. The proposed method showed a much better performance at a comparable error and deviation. The peak signal to noise ratio in different video sequences shows better and worse results than characteristics of known algorithms so it requires further investigation. Practical Relevance. Application of this algorithm in MPEG-4 and H.264 codecs instead of the standard can significantly reduce compression time. This feature enables to recommend it in telecommunication systems for multimedia data storing, transmission and processing.
Adaptive control based on an on-line parameter estimation of an upper limb exoskeleton.
Riani, Akram; Madani, Tarek; Hadri, Abdelhafid El; Benallegue, Abdelaziz
2017-07-01
This paper presents an adaptive control strategy for an upper-limb exoskeleton based on an on-line dynamic parameter estimator. The objective is to improve the control performance of this system that plays a critical role in assisting patients for shoulder, elbow and wrist joint movements. In general, the dynamic parameters of the human limb are unknown and differ from a person to another, which degrade the performances of the exoskeleton-human control system. For this reason, the proposed control scheme contains a supplementary loop based on a new efficient on-line estimator of the dynamic parameters. Indeed, the latter is acting upon the parameter adaptation of the controller to ensure the performances of the system in the presence of parameter uncertainties and perturbations. The exoskeleton used in this work is presented and a physical model of the exoskeleton interacting with a 7 Degree of Freedom (DoF) upper limb model is generated using the SimMechanics library of MatLab/Simulink. To illustrate the effectiveness of the proposed approach, an example of passive rehabilitation movements is performed using multi-body dynamic simulation. The aims is to maneuver the exoskeleton that drive the upper limb to track desired trajectories in the case of the passive arm movements.
Estimation of hydraulic jump characteristics of channels with sudden diverging side walls via SVM.
Roushangar, Kiyoumars; Valizadeh, Reyhaneh; Ghasempour, Roghayeh
2017-10-01
Sudden diverging channels are one of the energy dissipaters which can dissipate most of the kinetic energy of the flow through a hydraulic jump. An accurate prediction of hydraulic jump characteristics is an important step in designing hydraulic structures. This paper focuses on the capability of the support vector machine (SVM) as a meta-model approach for predicting hydraulic jump characteristics in different sudden diverging stilling basins (i.e. basins with and without appurtenances). In this regard, different models were developed and tested using 1,018 experimental data. The obtained results proved the capability of the SVM technique in predicting hydraulic jump characteristics and it was found that the developed models for a channel with a central block performed more successfully than models for channels without appurtenances or with a negative step. The superior performance for the length of hydraulic jump was obtained for the model with parameters F 1 (Froude number) and (h 2- h 1 )/h 1 (h 1 and h 2 are sequent depth of upstream and downstream respectively). Concerning the relative energy dissipation and sequent depth ratio, the model with parameters F 1 and h 1 /B (B is expansion ratio) led to the best results. According to the outcome of sensitivity analysis, Froude number had the most significant effect on the modeling. Also comparison between SVM and empirical equations indicated the great performance of the SVM.
An adaptive neuro fuzzy model for estimating the reliability of component-based software systems
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Kirti Tyagi
2014-01-01
Full Text Available Although many algorithms and techniques have been developed for estimating the reliability of component-based software systems (CBSSs, much more research is needed. Accurate estimation of the reliability of a CBSS is difficult because it depends on two factors: component reliability and glue code reliability. Moreover, reliability is a real-world phenomenon with many associated real-time problems. Soft computing techniques can help to solve problems whose solutions are uncertain or unpredictable. A number of soft computing approaches for estimating CBSS reliability have been proposed. These techniques learn from the past and capture existing patterns in data. The two basic elements of soft computing are neural networks and fuzzy logic. In this paper, we propose a model for estimating CBSS reliability, known as an adaptive neuro fuzzy inference system (ANFIS, that is based on these two basic elements of soft computing, and we compare its performance with that of a plain FIS (fuzzy inference system for different data sets.
Adaptive Parameter Estimation of Person Recognition Model in a Stochastic Human Tracking Process
Nakanishi, W.; Fuse, T.; Ishikawa, T.
2015-05-01
This paper aims at an estimation of parameters of person recognition models using a sequential Bayesian filtering method. In many human tracking method, any parameters of models used for recognize the same person in successive frames are usually set in advance of human tracking process. In real situation these parameters may change according to situation of observation and difficulty level of human position prediction. Thus in this paper we formulate an adaptive parameter estimation using general state space model. Firstly we explain the way to formulate human tracking in general state space model with their components. Then referring to previous researches, we use Bhattacharyya coefficient to formulate observation model of general state space model, which is corresponding to person recognition model. The observation model in this paper is a function of Bhattacharyya coefficient with one unknown parameter. At last we sequentially estimate this parameter in real dataset with some settings. Results showed that sequential parameter estimation was succeeded and were consistent with observation situations such as occlusions.
Owens, A. R.; Kópházi, J.; Welch, J. A.; Eaton, M. D.
2017-04-01
In this paper a hanging-node, discontinuous Galerkin, isogeometric discretisation of the multigroup, discrete ordinates (SN) equations is presented in which each energy group has its own mesh. The equations are discretised using Non-Uniform Rational B-Splines (NURBS), which allows the coarsest mesh to exactly represent the geometry for a wide range of engineering problems of interest; this would not be the case using straight-sided finite elements. Information is transferred between meshes via the construction of a supermesh. This is a non-trivial task for two arbitrary meshes, but is significantly simplified here by deriving every mesh from a common coarsest initial mesh. In order to take full advantage of this flexible discretisation, goal-based error estimators are derived for the multigroup, discrete ordinates equations with both fixed (extraneous) and fission sources, and these estimators are used to drive an adaptive mesh refinement (AMR) procedure. The method is applied to a variety of test cases for both fixed and fission source problems. The error estimators are found to be extremely accurate for linear NURBS discretisations, with degraded performance for quadratic discretisations owing to a reduction in relative accuracy of the "exact" adjoint solution required to calculate the estimators. Nevertheless, the method seems to produce optimal meshes in the AMR process for both linear and quadratic discretisations, and is ≈×100 more accurate than uniform refinement for the same amount of computational effort for a 67 group deep penetration shielding problem.
Directory of Open Access Journals (Sweden)
Linhui Zhao
2017-12-01
Full Text Available State of charge (SOC is an important evaluation index for lithium-ion batteries (LIBs in electric vehicles (EVs. This paper proposes a nonlinear observer with a new adaptive gain structure for SOC estimation based on a second-order RC model. It is able to dynamically adjust the gains and obtain a better balance between convergence speed and estimation accuracy with less computational time. A sufficient condition is derived to guarantee the uniform asymptotic stability of the observer, and its robustness with respect to disturbances and uncertainties is analyzed with the help of input-to-state stability (ISS theory. A selection guide of the observer gains in practical application is presented. The estimation accuracy and convergence rate of the observer are evaluated and compared with those of extended Kalman filter (EKF based on multi-temperature datasets from two different types of LIB cells. The robustness against different disturbances and uncertainties that may appear in a real vehicle is validated and discussed in detail. The experimental results show that the proposed observer is capable of achieving better performance with less computational time in comparison to EKF for different types of LIB cells under various working conditions. The observer is also capable of estimating SOC accurately for real life conditions according to the validation results of datasets from a battery management system (BMS in an EV battery pack. Furthermore, the observer is simple enough, and is suitable for implementation on embedded hardware for LIB cells of EVs.
Removing damped sinusoidal vibrations in adaptive optics systems using a DFT-based estimation method
Kania, Dariusz
2017-06-01
The problem of a vibrations rejection in adaptive optics systems is still present in publications. These undesirable signals emerge because of shaking the system structure, the tracking process, etc., and they usually are damped sinusoidal signals. There are some mechanical solutions to reduce the signals but they are not very effective. One of software solutions are very popular adaptive methods. An AVC (Adaptive Vibration Cancellation) method has been presented and developed in recent years. The method is based on the estimation of three vibrations parameters and values of frequency, amplitude and phase are essential to produce and adjust a proper signal to reduce or eliminate vibrations signals. This paper presents a fast (below 10 ms) and accurate estimation method of frequency, amplitude and phase of a multifrequency signal that can be used in the AVC method to increase the AO system performance. The method accuracy depends on several parameters: CiR - number of signal periods in a measurement window, N - number of samples in the FFT procedure, H - time window order, SNR, THD, b - number of A/D converter bits in a real time system, γ - the damping ratio of the tested signal, φ - the phase of the tested signal. Systematic errors increase when N, CiR, H decrease and when γ increases. The value of systematic error for γ = 0.1%, CiR = 1.1 and N = 32 is approximately 10^-4 Hz/Hz. This paper focuses on systematic errors of and effect of the signal phase and values of γ on the results.
Estimation of Efficiency of the Cooling Channel of the Nozzle Blade of Gas-Turbine Engines
Vikulin, A. V.; Yaroslavtsev, N. L.; Zemlyanaya, V. A.
2018-02-01
The main direction of improvement of gas-turbine plants (GTP) and gas-turbine engines (GTE) is increasing the gas temperature at the turbine inlet. For the solution of this problem, promising systems of intensification of heat exchange in cooled turbine blades are developed. With this purpose, studies of the efficiency of the cooling channel of the nozzle blade in the basic modification and of the channel after constructive measures for improvement of the cooling system by the method of calorimetry in a liquid-metal thermostat were conducted. The combined system of heat-exchange intensification with the complicated scheme of branched channels is developed; it consists of a vortex matrix and three rows of inclined intermittent trip strips. The maximum value of hydraulic resistance ξ is observed at the first row of the trip strips, which is connected with the effect of dynamic impact of airflow on the channel walls, its turbulence, and rotation by 117° at the inlet to the channels formed by the trip strips. These factors explain the high value of hydraulic resistance equal to 3.7-3.4 for the first row of the trip strips. The obtained effect was also confirmed by the results of thermal tests, i.e., the unevenness of heat transfer on the back and on the trough of the blade is observed at the first row of the trip strips, which amounts 8-12%. This unevenness has a fading character; at the second row of the trip strips, it amounts to 3-7%, and it is almost absent at the third row. At the area of vortex matrix, the intensity of heat exchange on the blade back is higher as compared to the trough, which is explained by the different height of the matrix ribs on its opposite sides. The design changes in the nozzle blade of basic modification made it possible to increase the intensity of heat exchange by 20-50% in the area of the vortex matrix and by 15-30% on the section of inclined intermittent trip strips. As a result of research, new criteria dependences for the
Petersen, Øyvind Wiig
2014-01-01
Force identification in structural dynamics is an inverse problem concerned with finding loads from measured structural response. The main objective of this thesis is to perform and study state (displacement and velocity) and force estimation by Kalman filtering. Theory on optimal control and state-space models are presented, adapted to linear structural dynamics. Accommodation for measurement noise and model inaccuracies are attained by stochastic-deterministic coupling. Explicit requirem...
Sheng, Li; Wang, Zidong; Tian, Engang; Alsaadi, Fuad E
2016-12-01
This paper deals with the H ∞ state estimation problem for a class of discrete-time neural networks with stochastic delays subject to state- and disturbance-dependent noises (also called (x,v)-dependent noises) and fading channels. The time-varying stochastic delay takes values on certain intervals with known probability distributions. The system measurement is transmitted through fading channels described by the Rice fading model. The aim of the addressed problem is to design a state estimator such that the estimation performance is guaranteed in the mean-square sense against admissible stochastic time-delays, stochastic noises as well as stochastic fading signals. By employing the stochastic analysis approach combined with the Kronecker product, several delay-distribution-dependent conditions are derived to ensure that the error dynamics of the neuron states is stochastically stable with prescribed H ∞ performance. Finally, a numerical example is provided to illustrate the effectiveness of the obtained results. Copyright © 2016 Elsevier Ltd. All rights reserved.
Ergeneci, Mert; Gokcesu, Kaan; Ertan, Erhan; Kosmas, Panagiotis
2018-02-01
Wearable technology has gained increasing popularity in the applications of healthcare, sports science, and biomedical engineering in recent years. Because of its convenient nature, the wearable technology is particularly useful in the acquisition of the physiological signals. Specifically, the (surface electromyography) sEMG systems, which measure the muscle activation potentials, greatly benefit from this technology in both clinical and industrial applications. However, the current wearable sEMG systems have several drawbacks including inefficient noise cancellation, insufficient measurement quality, and difficult integration to customized applications. Additionally, none of these sEMG data acquisition systems can detect sEMG signals (i.e., contractions), which provides a valuable environment for further studies such as human machine interaction, gesture recognition, and fatigue tracking. To this end, we introduce an embedded, eight channel, noise canceling, wireless, wearable sEMG data acquisition system with adaptive muscle contraction detection. Our design consists of two stages, which are the sEMG sensors and the multichannel data acquisition unit. For the first stage, we propose a low cost, dry, and active sEMG sensor that captures the muscle activation potentials, a data acquisition unit that evaluates these captured multichannel sEMG signals and transmits them to a user interface. In the data acquisition unit, the sEMG signals are processed through embedded, adaptive methods in order to reject the power line noise and detect the muscle contractions. Through extensive experiments, we demonstrate that our sEMG sensor outperforms a widely used commercially available product and our data acquisition system achieves 4.583 dB SNR gain with accuracy in the detection of the contractions.
Fast simulation of transport and adaptive permeability estimation in porous media
Energy Technology Data Exchange (ETDEWEB)
Berre, Inga
2005-07-01
The focus of the thesis is twofold: Both fast simulation of transport in porous media and adaptive estimation of permeability are considered. A short introduction that motivates the work on these topics is given in Chapter 1. In Chapter 2, the governing equations for one- and two-phase flow in porous media are presented. Overall numerical solution strategies for the two-phase flow model are also discussed briefly. The concepts of streamlines and time-of-flight are introduced in Chapter 3. Methods for computing streamlines and time-of-flight are also presented in this chapter. Subsequently, in Chapters 4 and 5, the focus is on simulation of transport in a time-of-flight perspective. In Chapter 4, transport of fluids along streamlines is considered. Chapter 5 introduces a different viewpoint based on the evolution of isocontours of the fluid saturation. While the first chapters focus on the forward problem, which consists in solving a mathematical model given the reservoir parameters, Chapters 6, 7 and 8 are devoted to the inverse problem of permeability estimation. An introduction to the problem of identifying spatial variability in reservoir permeability by inversion of dynamic production data is given in Chapter 6. In Chapter 7, adaptive multiscale strategies for permeability estimation are discussed. Subsequently, Chapter 8 presents a level-set approach for improving piecewise constant permeability representations. Finally, Chapter 9 summarizes the results obtained in the thesis; in addition, the chapter gives some recommendations and suggests directions for future work. Part II In Part II, the following papers are included in the order they were completed: Paper A: A Streamline Front Tracking Method for Two- and Three-Phase Flow Including Capillary Forces. I. Berre, H. K. Dahle, K. H. Karlsen, and H. F. Nordhaug. In Fluid flow and transport in porous media: mathematical and numerical treatment (South Hadley, MA, 2001), volume 295 of Contemp. Math., pages 49
International Nuclear Information System (INIS)
Sun, Fengchun; Hu, Xiaosong; Zou, Yuan; Li, Siguang
2011-01-01
An accurate battery State of Charge estimation is of great significance for battery electric vehicles and hybrid electric vehicles. This paper presents an adaptive unscented Kalman filtering method to estimate State of Charge of a lithium-ion battery for battery electric vehicles. The adaptive adjustment of the noise covariances in the State of Charge estimation process is implemented by an idea of covariance matching in the unscented Kalman filter context. Experimental results indicate that the adaptive unscented Kalman filter-based algorithm has a good performance in estimating the battery State of Charge. A comparison with the adaptive extended Kalman filter, extended Kalman filter, and unscented Kalman filter-based algorithms shows that the proposed State of Charge estimation method has a better accuracy. -- Highlights: → Adaptive unscented Kalman filtering is proposed to estimate State of Charge of a lithium-ion battery for electric vehicles. → The proposed method has a good performance in estimating the battery State of Charge. → A comparison with three other Kalman filtering algorithms shows that the proposed method has a better accuracy.
SU-G-BRA-09: Estimation of Motion Tracking Uncertainty for Real-Time Adaptive Imaging
Energy Technology Data Exchange (ETDEWEB)
Yan, H [Capital Medical University, Beijing, Beijing (China); Chen, Z [Yale New Haven Hospital, New Haven, CT (United States); Nath, R; Liu, W [Yale University School of Medicine, New Haven, CT (United States)
2016-06-15
Purpose: kV fluoroscopic imaging combined with MV treatment beam imaging has been investigated for intrafractional motion monitoring and correction. It is, however, subject to additional kV imaging dose to normal tissue. To balance tracking accuracy and imaging dose, we previously proposed an adaptive imaging strategy to dynamically decide future imaging type and moments based on motion tracking uncertainty. kV imaging may be used continuously for maximal accuracy or only when the position uncertainty (probability of out of threshold) is high if a preset imaging dose limit is considered. In this work, we propose more accurate methods to estimate tracking uncertainty through analyzing acquired data in real-time. Methods: We simulated motion tracking process based on a previously developed imaging framework (MV + initial seconds of kV imaging) using real-time breathing data from 42 patients. Motion tracking errors for each time point were collected together with the time point’s corresponding features, such as tumor motion speed and 2D tracking error of previous time points, etc. We tested three methods for error uncertainty estimation based on the features: conditional probability distribution, logistic regression modeling, and support vector machine (SVM) classification to detect errors exceeding a threshold. Results: For conditional probability distribution, polynomial regressions on three features (previous tracking error, prediction quality, and cosine of the angle between the trajectory and the treatment beam) showed strong correlation with the variation (uncertainty) of the mean 3D tracking error and its standard deviation: R-square = 0.94 and 0.90, respectively. The logistic regression and SVM classification successfully identified about 95% of tracking errors exceeding 2.5mm threshold. Conclusion: The proposed methods can reliably estimate the motion tracking uncertainty in real-time, which can be used to guide adaptive additional imaging to confirm the
SU-G-BRA-09: Estimation of Motion Tracking Uncertainty for Real-Time Adaptive Imaging
International Nuclear Information System (INIS)
Yan, H; Chen, Z; Nath, R; Liu, W
2016-01-01
Purpose: kV fluoroscopic imaging combined with MV treatment beam imaging has been investigated for intrafractional motion monitoring and correction. It is, however, subject to additional kV imaging dose to normal tissue. To balance tracking accuracy and imaging dose, we previously proposed an adaptive imaging strategy to dynamically decide future imaging type and moments based on motion tracking uncertainty. kV imaging may be used continuously for maximal accuracy or only when the position uncertainty (probability of out of threshold) is high if a preset imaging dose limit is considered. In this work, we propose more accurate methods to estimate tracking uncertainty through analyzing acquired data in real-time. Methods: We simulated motion tracking process based on a previously developed imaging framework (MV + initial seconds of kV imaging) using real-time breathing data from 42 patients. Motion tracking errors for each time point were collected together with the time point’s corresponding features, such as tumor motion speed and 2D tracking error of previous time points, etc. We tested three methods for error uncertainty estimation based on the features: conditional probability distribution, logistic regression modeling, and support vector machine (SVM) classification to detect errors exceeding a threshold. Results: For conditional probability distribution, polynomial regressions on three features (previous tracking error, prediction quality, and cosine of the angle between the trajectory and the treatment beam) showed strong correlation with the variation (uncertainty) of the mean 3D tracking error and its standard deviation: R-square = 0.94 and 0.90, respectively. The logistic regression and SVM classification successfully identified about 95% of tracking errors exceeding 2.5mm threshold. Conclusion: The proposed methods can reliably estimate the motion tracking uncertainty in real-time, which can be used to guide adaptive additional imaging to confirm the
Channel Estimation and Information Symbol Detection for DS-UWB Communication Systems
Directory of Open Access Journals (Sweden)
Wei Wang
2014-01-01
estimation, the one-step predictor of information symbol is used and the estimation error is also considered as a multiplicative noise. The solutions to the above two problems are obtained by solving a couple of Riccati equations together with two Lyapunov equations.
Multiple estimation channel decoupling and optimization method based on inverse system
Wu, Peng; Mu, Rongjun; Zhang, Xin; Deng, Yanpeng
2018-03-01
This paper addressed the intelligent autonomous navigation request of intelligent deformation missile, based on the intelligent deformation missile dynamics and kinematics modeling, navigation subsystem solution method and error modeling, and then focuses on the corresponding data fusion and decision fusion technology, decouples the sensitive channel of the filter input through the inverse system of design dynamics to reduce the influence of sudden change of the measurement information on the filter input. Then carrying out a series of simulation experiments, which verified the feasibility of the inverse system decoupling algorithm effectiveness.
Hu, Chia-Chang; Lin, Hsuan-Yu; Chen, Yu-Fan; Wen, Jyh-Horng
2006-12-01
An adaptive minimum mean-square error (MMSE) array receiver based on the fuzzy-logic recursive least-squares (RLS) algorithm is developed for asynchronous DS-CDMA interference suppression in the presence of frequency-selective multipath fading. This receiver employs a fuzzy-logic control mechanism to perform the nonlinear mapping of the squared error and squared error variation, denoted by ([InlineEquation not available: see fulltext.],[InlineEquation not available: see fulltext.]), into a forgetting factor[InlineEquation not available: see fulltext.]. For the real-time applicability, a computationally efficient version of the proposed receiver is derived based on the least-mean-square (LMS) algorithm using the fuzzy-inference-controlled step-size[InlineEquation not available: see fulltext.]. This receiver is capable of providing both fast convergence/tracking capability as well as small steady-state misadjustment as compared with conventional LMS- and RLS-based MMSE DS-CDMA receivers. Simulations show that the fuzzy-logic LMS and RLS algorithms outperform, respectively, other variable step-size LMS (VSS-LMS) and variable forgetting factor RLS (VFF-RLS) algorithms at least 3 dB and 1.5 dB in bit-error-rate (BER) for multipath fading channels.
Directory of Open Access Journals (Sweden)
Chen Yu-Fan
2006-01-01
Full Text Available An adaptive minimum mean-square error (MMSE array receiver based on the fuzzy-logic recursive least-squares (RLS algorithm is developed for asynchronous DS-CDMA interference suppression in the presence of frequency-selective multipath fading. This receiver employs a fuzzy-logic control mechanism to perform the nonlinear mapping of the squared error and squared error variation, denoted by ( , , into a forgetting factor . For the real-time applicability, a computationally efficient version of the proposed receiver is derived based on the least-mean-square (LMS algorithm using the fuzzy-inference-controlled step-size . This receiver is capable of providing both fast convergence/tracking capability as well as small steady-state misadjustment as compared with conventional LMS- and RLS-based MMSE DS-CDMA receivers. Simulations show that the fuzzy-logic LMS and RLS algorithms outperform, respectively, other variable step-size LMS (VSS-LMS and variable forgetting factor RLS (VFF-RLS algorithms at least 3 dB and 1.5 dB in bit-error-rate (BER for multipath fading channels.
Broom, Donald M
2006-01-01
The term adaptation is used in biology in three different ways. It may refer to changes which occur at the cell and organ level, or at the individual level, or at the level of gene action and evolutionary processes. Adaptation by cells, especially nerve cells helps in: communication within the body, the distinguishing of stimuli, the avoidance of overload and the conservation of energy. The time course and complexity of these mechanisms varies. Adaptive characters of organisms, including adaptive behaviours, increase fitness so this adaptation is evolutionary. The major part of this paper concerns adaptation by individuals and its relationships to welfare. In complex animals, feed forward control is widely used. Individuals predict problems and adapt by acting before the environmental effect is substantial. Much of adaptation involves brain control and animals have a set of needs, located in the brain and acting largely via motivational mechanisms, to regulate life. Needs may be for resources but are also for actions and stimuli which are part of the mechanism which has evolved to obtain the resources. Hence pigs do not just need food but need to be able to carry out actions like rooting in earth or manipulating materials which are part of foraging behaviour. The welfare of an individual is its state as regards its attempts to cope with its environment. This state includes various adaptive mechanisms including feelings and those which cope with disease. The part of welfare which is concerned with coping with pathology is health. Disease, which implies some significant effect of pathology, always results in poor welfare. Welfare varies over a range from very good, when adaptation is effective and there are feelings of pleasure or contentment, to very poor. A key point concerning the concept of individual adaptation in relation to welfare is that welfare may be good or poor while adaptation is occurring. Some adaptation is very easy and energetically cheap and
Enzymatic Synthesis of Ampicillin: Nonlinear Modeling, Kinetics Estimation, and Adaptive Control
Directory of Open Access Journals (Sweden)
Monica Roman
2012-01-01
Full Text Available Nowadays, the use of advanced control strategies in biotechnology is quite low. A main reason is the lack of quality of the data, and the fact that more sophisticated control strategies must be based on a model of the dynamics of bioprocesses. The nonlinearity of the bioprocesses and the absence of cheap and reliable instrumentation require an enhanced modeling effort and identification strategies for the kinetics. The present work approaches modeling and control strategies for the enzymatic synthesis of ampicillin that is carried out inside a fed-batch bioreactor. First, a nonlinear dynamical model of this bioprocess is obtained by using a novel modeling procedure for biotechnology: the bond graph methodology. Second, a high gain observer is designed for the estimation of the imprecisely known kinetics of the synthesis process. Third, by combining an exact linearizing control law with the on-line estimation kinetics algorithm, a nonlinear adaptive control law is designed. The case study discussed shows that a nonlinear feedback control strategy applied to the ampicillin synthesis bioprocess can cope with disturbances, noisy measurements, and parametric uncertainties. Numerical simulations performed with MATLAB environment are included in order to test the behavior and the performances of the proposed estimation and control strategies.
Adaptive Model Predictive Vibration Control of a Cantilever Beam with Real-Time Parameter Estimation
Directory of Open Access Journals (Sweden)
Gergely Takács
2014-01-01
Full Text Available This paper presents an adaptive-predictive vibration control system using extended Kalman filtering for the joint estimation of system states and model parameters. A fixed-free cantilever beam equipped with piezoceramic actuators serves as a test platform to validate the proposed control strategy. Deflection readings taken at the end of the beam have been used to reconstruct the position and velocity information for a second-order state-space model. In addition to the states, the dynamic system has been augmented by the unknown model parameters: stiffness, damping constant, and a voltage/force conversion constant, characterizing the actuating effect of the piezoceramic transducers. The states and parameters of this augmented system have been estimated in real time, using the hybrid extended Kalman filter. The estimated model parameters have been applied to define the continuous state-space model of the vibrating system, which in turn is discretized for the predictive controller. The model predictive control algorithm generates state predictions and dual-mode quadratic cost prediction matrices based on the updated discrete state-space models. The resulting cost function is then minimized using quadratic programming to find the sequence of optimal but constrained control inputs. The proposed active vibration control system is implemented and evaluated experimentally to investigate the viability of the control method.
Improved remote gaze estimation using corneal reflection-adaptive geometric transforms
Ma, Chunfei; Baek, Seung-Jin; Choi, Kang-A.; Ko, Sung-Jea
2014-05-01
Recently, the remote gaze estimation (RGE) technique has been widely applied to consumer devices as a more natural interface. In general, the conventional RGE method estimates a user's point of gaze using a geometric transform, which represents the relationship between several infrared (IR) light sources and their corresponding corneal reflections (CRs) in the eye image. Among various methods, the homography normalization (HN) method achieves state-of-the-art performance. However, the geometric transform of the HN method requiring four CRs is infeasible for the case when fewer than four CRs are available. To solve this problem, this paper proposes a new RGE method based on three alternative geometric transforms, which are adaptive to the number of CRs. Unlike the HN method, the proposed method not only can operate with two or three CRs, but can also provide superior accuracy. To further enhance the performance, an effective error correction method is also proposed. By combining the introduced transforms with the error-correction method, the proposed method not only provides high accuracy and robustness for gaze estimation, but also allows for a more flexible system setup with a different number of IR light sources. Experimental results demonstrate the effectiveness of the proposed method.
Directory of Open Access Journals (Sweden)
Bingfei Fan
2017-05-01
Full Text Available Magnetic and inertial sensors have been widely used to estimate the orientation of human segments due to their low cost, compact size and light weight. However, the accuracy of the estimated orientation is easily affected by external factors, especially when the sensor is used in an environment with magnetic disturbances. In this paper, we propose an adaptive method to improve the accuracy of orientation estimations in the presence of magnetic disturbances. The method is based on existing gradient descent algorithms, and it is performed prior to sensor fusion algorithms. The proposed method includes stationary state detection and magnetic disturbance severity determination. The stationary state detection makes this method immune to magnetic disturbances in stationary state, while the magnetic disturbance severity determination helps to determine the credibility of magnetometer data under dynamic conditions, so as to mitigate the negative effect of the magnetic disturbances. The proposed method was validated through experiments performed on a customized three-axis instrumented gimbal with known orientations. The error of the proposed method and the original gradient descent algorithms were calculated and compared. Experimental results demonstrate that in stationary state, the proposed method is completely immune to magnetic disturbances, and in dynamic conditions, the error caused by magnetic disturbance is reduced by 51.2% compared with original MIMU gradient descent algorithm.
Adaptive transmit selection with interference suppression
Radaydeh, Redha Mahmoud Mesleh
2010-01-01
This paper studies the performance of adaptive transmit channel selection in multipath fading channels. The adaptive selection algorithms are configured for single-antenna bandwidth-efficient or power-efficient transmission with as low transmit channel estimations as possible. Due to the fact that the number of active co-channel interfering signals and their corresponding powers experience random behavior, the adaptation to channels conditions, assuming uniform buffer and traffic loading, is proposed to be jointly based on the transmit channels instantaneous signal-to-noise ratios (SNRs) and signal-to- interference-plus- noise ratios (SINRs). Two interference cancelation algorithms, which are the dominant cancelation and the less complex arbitrary cancelation, are considered, for which the receive antenna array is assumed to have small angular spread. Analytical formulation for some performance measures in addition to several processing complexity and numerical comparisons between various adaptation schemes are presented. ©2010 IEEE.
Kim, Sooyeon; Moses, Tim; Yoo, Hanwook Henry
2015-01-01
The purpose of this inquiry was to investigate the effectiveness of item response theory (IRT) proficiency estimators in terms of estimation bias and error under multistage testing (MST). We chose a 2-stage MST design in which 1 adaptation to the examinees' ability levels takes place. It includes 4 modules (1 at Stage 1, 3 at Stage 2) and 3 paths…
Directory of Open Access Journals (Sweden)
Colin Morningstar
2017-11-01
Full Text Available An implementation of estimating the two-to-two K-matrix from finite-volume energies based on the Lüscher formalism and involving a Hermitian matrix known as the “box matrix” is described. The method includes higher partial waves and multiple decay channels. Two fitting procedures for estimating the K-matrix parameters, which properly incorporate all statistical covariances, are discussed. Formulas and software for handling total spins up to S=2 and orbital angular momenta up to L=6 are obtained for total momenta in several directions. First tests involving ρ-meson decay to two pions include the L=3 and L=5 partial waves, and the contributions from these higher waves are found to be negligible in the elastic energy range.
International Development Research Centre (IDRC) Digital Library (Canada)
building skills, knowledge or networks on adaptation, ... the African partners leading the AfricaAdapt network, together with the UK-based Institute of Development Studies; and ... UNCCD Secretariat, Regional Coordination Unit for Africa, Tunis, Tunisia .... 26 Rural–urban Cooperation on Water Management in the Context of.
Achieving Optimal Quantum Acceleration of Frequency Estimation Using Adaptive Coherent Control.
Naghiloo, M; Jordan, A N; Murch, K W
2017-11-03
Precision measurements of frequency are critical to accurate time keeping and are fundamentally limited by quantum measurement uncertainties. While for time-independent quantum Hamiltonians the uncertainty of any parameter scales at best as 1/T, where T is the duration of the experiment, recent theoretical works have predicted that explicitly time-dependent Hamiltonians can yield a 1/T^{2} scaling of the uncertainty for an oscillation frequency. This quantum acceleration in precision requires coherent control, which is generally adaptive. We experimentally realize this quantum improvement in frequency sensitivity with superconducting circuits, using a single transmon qubit. With optimal control pulses, the theoretically ideal frequency precision scaling is reached for times shorter than the decoherence time. This result demonstrates a fundamental quantum advantage for frequency estimation.
A Rate-Adaptive MAC Protocol Based on TCP throughput for Ad Hoc Networks in Fading Channels
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Shoko Uchida
2008-10-01
Full Text Available Wireless technology is becoming a leading option for future Internet access. Transmission Control Protocol (TCP is one of the protocols designed on the basis of the transmission characteristics in wired networks. It is known that the TCP performance deteriorates drastically under a wireless communication environment. On the other hand, many wireless networking standards such as IEEE 802.11a, 802.11b, and 802.11g have multirate capability. Therefore, adaptive rate control methods have been proposed for ad hoc networks. However, almost methods require the modification of the request to send (RTS and clear to send (CTS packets. Therefore, the conventional methods are not compatible with the standardized system. In this paper, we propose adaptive rate control mechanisms for ad hoc networks. Our mechanisms are based on the RTS/CTS mechanisms. However, no modifications to the RTS and CTS packets are required in the proposed method. Therefore, our proposed method can attempt to satisfy the conventional IEEE 802.11 standards. Moreover, an adequate transmission rate is selected based on an estimated TCP throughput performance. From simulation results, it is observed that the proposed method can improve the throughput performance without any modification of packet structures.
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Marco Lombardo
Full Text Available PURPOSE: To investigate the influence of various technical factors on the variation of cone packing density estimates in adaptive optics flood illuminated retinal images. METHODS: Adaptive optics images of the photoreceptor mosaic were obtained in fifteen healthy subjects. The cone density and Voronoi diagrams were assessed in sampling windows of 320×320 µm, 160×160 µm and 64×64 µm at 1.5 degree temporal and superior eccentricity from the preferred locus of fixation (PRL. The technical factors that have been analyzed included the sampling window size, the corrected retinal magnification factor (RMFcorr, the conversion from radial to linear distance from the PRL, the displacement between the PRL and foveal center and the manual checking of cone identification algorithm. Bland-Altman analysis was used to assess the agreement between cone density estimated within the different sampling window conditions. RESULTS: The cone density declined with decreasing sampling area and data between areas of different size showed low agreement. A high agreement was found between sampling areas of the same size when comparing density calculated with or without using individual RMFcorr. The agreement between cone density measured at radial and linear distances from the PRL and between data referred to the PRL or the foveal center was moderate. The percentage of Voronoi tiles with hexagonal packing arrangement was comparable between sampling areas of different size. The boundary effect, presence of any retinal vessels, and the manual selection of cones missed by the automated identification algorithm were identified as the factors influencing variation of cone packing arrangements in Voronoi diagrams. CONCLUSIONS: The sampling window size is the main technical factor that influences variation of cone density. Clear identification of each cone in the image and the use of a large buffer zone are necessary to minimize factors influencing variation of Voronoi
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Max Berniker
2011-10-01
Full Text Available Recent studies suggest that motor adaptation is the result of multiple, perhaps linear processes each with distinct time scales. While these models are consistent with some motor phenomena, they can neither explain the relatively fast re-adaptation after a long washout period, nor savings on a subsequent day. Here we examined if these effects can be explained if we assume that the CNS stores and retrieves movement parameters based on their possible relevance. We formalize this idea with a model that infers not only the sources of potential motor errors, but also their relevance to the current motor circumstances. In our model adaptation is the process of re-estimating parameters that represent the body and the world. The likelihood of a world parameter being relevant is then based on the mismatch between an observed movement and that predicted when not compensating for the estimated world disturbance. As such, adapting to large motor errors in a laboratory setting should alert subjects that disturbances are being imposed on them, even after motor performance has returned to baseline. Estimates of this external disturbance should be relevant both now and in future laboratory settings. Estimated properties of our bodies on the other hand should always be relevant. Our model demonstrates savings, interference, spontaneous rebound and differences between adaptation to sudden and gradual disturbances. We suggest that many issues concerning savings and interference can be understood when adaptation is conditioned on the relevance of parameters.
Distributed Channel Estimation and Pilot Contamination Analysis for Massive MIMO-OFDM Systems
Zaib, Alam; Masood, Mudassir; Ali, Anum; Xu, Weiyu; Al-Naffouri, Tareq Y.
2016-01-01
of reserved pilot tones, we propose a data-aided estimation technique that relies on finding a set of most reliable data carriers. Furthermore, we use stochastic geometry to quantify the pilot contamination, and in turn use this information to analyze
Directory of Open Access Journals (Sweden)
Dansereau Richard M
2007-01-01
Full Text Available We present a new technique for separating two speech signals from a single recording. The proposed method bridges the gap between underdetermined blind source separation techniques and those techniques that model the human auditory system, that is, computational auditory scene analysis (CASA. For this purpose, we decompose the speech signal into the excitation signal and the vocal-tract-related filter and then estimate the components from the mixed speech using a hybrid model. We first express the probability density function (PDF of the mixed speech's log spectral vectors in terms of the PDFs of the underlying speech signal's vocal-tract-related filters. Then, the mean vectors of PDFs of the vocal-tract-related filters are obtained using a maximum likelihood estimator given the mixed signal. Finally, the estimated vocal-tract-related filters along with the extracted fundamental frequencies are used to reconstruct estimates of the individual speech signals. The proposed technique effectively adds vocal-tract-related filter characteristics as a new cue to CASA models using a new grouping technique based on an underdetermined blind source separation. We compare our model with both an underdetermined blind source separation and a CASA method. The experimental results show that our model outperforms both techniques in terms of SNR improvement and the percentage of crosstalk suppression.
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Mohammad H. Radfar
2006-11-01
Full Text Available We present a new technique for separating two speech signals from a single recording. The proposed method bridges the gap between underdetermined blind source separation techniques and those techniques that model the human auditory system, that is, computational auditory scene analysis (CASA. For this purpose, we decompose the speech signal into the excitation signal and the vocal-tract-related filter and then estimate the components from the mixed speech using a hybrid model. We first express the probability density function (PDF of the mixed speech's log spectral vectors in terms of the PDFs of the underlying speech signal's vocal-tract-related filters. Then, the mean vectors of PDFs of the vocal-tract-related filters are obtained using a maximum likelihood estimator given the mixed signal. Finally, the estimated vocal-tract-related filters along with the extracted fundamental frequencies are used to reconstruct estimates of the individual speech signals. The proposed technique effectively adds vocal-tract-related filter characteristics as a new cue to CASA models using a new grouping technique based on an underdetermined blind source separation. We compare our model with both an underdetermined blind source separation and a CASA method. The experimental results show that our model outperforms both techniques in terms of SNR improvement and the percentage of crosstalk suppression.
Asymptotic behavior of Bayes estimators for hidden Markov models with application to ion channels
de Gunst, M.C.M.; Shcherbakova, O.V.
2008-01-01
In this paper we study the asymptotic behavior of Bayes estimators for hidden Markov models as the number of observations goes to infinity. The theorem that we prove is similar to the Bernstein-von Mises theorem on the asymptotic behavior of the posterior distribution for the case of independent
Understanding peer effects : on the nature, estimation and channels of peer effects
Feld, J.F.; Zölitz, U.N.
2016-01-01
This paper estimates peer effects in a university context where students are randomly assigned to sections. While students benefit from better peers on average, lowachieving students are harmed by high-achieving peers. Analyzing students’ course evaluations suggests that peer effects are driven by
Understanding peer effects - On the nature, estimation and channels of peer effects
Feld, J.F.; Zölitz, U.N.
2016-01-01
This paper estimates peer effects in a university context where students are randomly assigned to sections. While students benefit from better peers on average, low-achieving students are harmed by high-achieving peers. Analyzing students’ course evaluations suggests that peer effects are driven by
Directory of Open Access Journals (Sweden)
Hossein Riahi Modvar
2008-09-01
Full Text Available Longitudinal dispersion coefficient in rivers and natural streams is usually estimated by simple inaccurate empirical relations because of the complexity of the phenomenon. In this study, the adaptive neuro-fuzzy inference system (ANFIS is used to develop a new flexible tool for predicting the longitudinal dispersion coefficient. The system has the ability to understand and realize the phenomenon without the need for mathematical governing equations.. The training and testing of this new model are accomplished using a set of available published filed data. Several statistical and graphical criteria are used to check the accuracy of the model. The dispersion coefficient values predicted by the ANFIS model compares satisfactorily with the measured data. The predicted values are also compared with those predicted by existing empirical equations reported in the literature to find that the ANFIS model with R2=0.99 and RMSE=15.18 in training stage and R2=0.91 and RMSE=187.8 in testing stage is superior in predicting the dispersion coefficient to the most accurate empirical equation with R2=0.48 and RMSE=295.7. The proposed methodology is a new approach to estimating dispersion coefficient in streams and can be combined with mathematical models of pollutant transfer or real-time updating of these models.
Estimate of Hurricane Wind Speed from AMSR-E Low-Frequency Channel Brightness Temperature Data
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Lei Zhang
2018-01-01
Full Text Available Two new parameters (W6H and W6V were defined that represent brightness temperature increments for different low-frequency channels due to ocean wind. We developed a new wind speed retrieval model inside hurricanes based on W6H and W6V using brightness temperature data from AMSR-E. The AMSR-E observations of 12 category 3–5 hurricanes from 2003 to 2011 and corresponding data from the H*wind analysis system were used to develop and validate the AMSR-E wind speed retrieval model. The results show that the mean bias and the overall root-mean-square (RMS difference of the AMSR-E retrieved wind speeds with respect to H*wind (HRD Real-time Hurricane Wind Analysis System analysis data were −0.01 m/s and 2.66 m/s, respectively. One case study showed that W6H and W6V were less sensitive to rain than the observed AMSR-E C-band and X-band brightness temperature data. The AMSR-E retrieval model was further validated by comparing the retrieved wind speeds against stepped-frequency microwave radiometer (SFMR measurements. The comparison showed an RMS difference of 3.41 m/s and a mean bias of 0.49 m/s.
Estimating Total Fusion Cross Sections by Using a Coupled-Channel Method
Energy Technology Data Exchange (ETDEWEB)
Choi, Ki-Seok; Cheoun, Myung-Ki [Soongsil University, Seoul (Korea, Republic of); Kim, K. S. [Korea Aerospace University, Koyang (Korea, Republic of); Kim, T. H.; So, W. Y. [Kangwon National University at Dogye, Samcheok (Korea, Republic of)
2017-01-15
We calculate the total fusion cross sections for the {sup 6}He + {sup 209}Bi, {sup 6}Li + {sup 209}Bi,{sup 9}Be + {sup 208}Pb, {sup 10}Be + {sup 209}Bi, and {sup 11}Li + {sup 208}Pb systems by using a coupled-channel (CC) method and compare the results with the experimental data. In the CC approach for the total fusion cross sections, we exploit a globally determined Wood-Saxon potential with Aky¨uz-Winther parameters and couplings of the ground state to the low-lying excited states in the projectile and the target nuclei. The total fusion cross sections obtained with the CC are compared with those obtained without the CC couplings. The latter approach is tantamount to a one-dimensional barrier penetration model. Finally, our approach is applied to understand new data for the {sup 11}Li+{sup 208}Pb system. Possible ambiguities inherent in those approaches are discussed in detail for further applications to the fusion system of halo and/or neutron-rich nuclei.
Yang, Yanfu; Xiang, Qian; Zhang, Qun; Zhou, Zhongqing; Jiang, Wen; He, Qianwen; Yao, Yong
2017-09-01
We propose a joint estimation scheme for fast, accurate, and robust frequency offset (FO) estimation along with phase estimation based on modified adaptive Kalman filter (MAKF). The scheme consists of three key modules: extend Kalman filter (EKF), lock detector, and FO cycle slip recovery. The EKF module estimates time-varying phase induced by both FO and laser phase noise. The lock detector module makes decision between acquisition mode and tracking mode and consequently sets the EKF tuning parameter in an adaptive manner. The third module can detect possible cycle slip in the case of large FO and make proper correction. Based on the simulation and experimental results, the proposed MAKF has shown excellent estimation performance featuring high accuracy, fast convergence, as well as the capability of cycle slip recovery.
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Z. Lari
2012-07-01
Full Text Available Over the past few years, LiDAR systems have been established as a leading technology for the acquisition of high density point clouds over physical surfaces. These point clouds will be processed for the extraction of geo-spatial information. Local point density is one of the most important properties of the point cloud that highly affects the performance of data processing techniques and the quality of extracted information from these data. Therefore, it is necessary to define a standard methodology for the estimation of local point density indices to be considered for the precise processing of LiDAR data. Current definitions of local point density indices, which only consider the 2D neighbourhood of individual points, are not appropriate for 3D LiDAR data and cannot be applied for laser scans from different platforms. In order to resolve the drawbacks of these methods, this paper proposes several approaches for the estimation of the local point density index which take the 3D relationship among the points and the physical properties of the surfaces they belong to into account. In the simplest approach, an approximate value of the local point density for each point is defined while considering the 3D relationship among the points. In the other approaches, the local point density is estimated by considering the 3D neighbourhood of the point in question and the physical properties of the surface which encloses this point. The physical properties of the surfaces enclosing the LiDAR points are assessed through eigen-value analysis of the 3D neighbourhood of individual points and adaptive cylinder methods. This paper will discuss these approaches and highlight their impact on various LiDAR data processing activities (i.e., neighbourhood definition, region growing, segmentation, boundary detection, and classification. Experimental results from airborne and terrestrial LiDAR data verify the efficacy of considering local point density variation for
International Nuclear Information System (INIS)
Merat, S.
2008-01-01
Expanding wireless communication network reception inside reactor buildings (RB) and service wings (SW) has always been a technical challenge for operations service team. This is driven by the volume of metal equipment inside the Reactor Buildings (RB) that blocks and somehow shields the signal throughout the link. In this study, to improve wireless reception inside the Reactor Building (RB), an experimental model using indoor localization mesh based on IEEE 802.15 is developed to implement a wireless sensor network. This experimental model estimates the distance between different nodes by measuring the RSSI (Received Signal Strength Indicator). Then by using triangulation and RSSI measurement, the validity of the estimation techniques is verified to simulate the physical environmental obstacles, which block the signal transmission. (author)
Energy Technology Data Exchange (ETDEWEB)
Merat, S. [Wardrop Engineering Inc., Toronto, Ontario (Canada)
2008-07-01
Expanding wireless communication network reception inside reactor buildings (RB) and service wings (SW) has always been a technical challenge for operations service team. This is driven by the volume of metal equipment inside the Reactor Buildings (RB) that blocks and somehow shields the signal throughout the link. In this study, to improve wireless reception inside the Reactor Building (RB), an experimental model using indoor localization mesh based on IEEE 802.15 is developed to implement a wireless sensor network. This experimental model estimates the distance between different nodes by measuring the RSSI (Received Signal Strength Indicator). Then by using triangulation and RSSI measurement, the validity of the estimation techniques is verified to simulate the physical environmental obstacles, which block the signal transmission. (author)
Directory of Open Access Journals (Sweden)
H.Z. Igamberdiyev
2014-07-01
Full Text Available Dynamic systems condition estimation regularization algorithms in the conditions of signals and hindrances statistical characteristics aprioristic uncertainty are offered. Regular iterative algorithms of strengthening matrix factor elements of the Kalman filter, allowing to adapt the filter to changing hindrance-alarm conditions are developed. Steady adaptive estimation algorithms of a condition vector in the aprioristic uncertainty conditions of covariance matrixes of object noise and the measurements hindrances providing a certain roughness of filtration process in relation to changing statistical characteristics of signals information parameters are offered. Offered practical realization results of the dynamic systems condition estimation algorithms are given at the adaptive management systems synthesis problems solution by technological processes of granulation drying of an ammophos pulp and receiving ammonia.
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S. Mohan Krishna
2016-09-01
Full Text Available This paper presents a real-time simulation study of Model Reference Adaptive System based rotor speed estimator with parallel stator resistance adaptation mechanism for speed sensorless induction motor drive. Both, the traditional Proportional Integral and Fuzzy logic based control mechanisms are utilised for stator resistance adaptation, while, the rotor speed is estimated parallely by means of Proportional Integral based mechanism. The estimator's response to dynamic changes in Load perturbation and doubling of the nominal value of the actual stator resistance of the motor is observed. The superiority of the fuzzy based stator resistance adaptation in the Model Reference Adaptive System estimator is proved through results validated in real-time. The purpose of employing a fairly new real-time platform is to reduce the test and prototype time. The model is initially built using Matlab/Simulink blocksets and the results are validated in real time using RT-Lab. The RT-lab blocksets are integrated into the Simulink model and then executed in real-time using the OP-4500 target developed by Opal-RT. The real-time simulation results are observed in the workstation.
Bargatze, L. F.
2015-12-01
Active Data Archive Product Tracking (ADAPT) is a collection of software routines that permits one to generate XML metadata files to describe and register data products in support of the NASA Heliophysics Virtual Observatory VxO effort. ADAPT is also a philosophy. The ADAPT concept is to use any and all available metadata associated with scientific data to produce XML metadata descriptions in a consistent, uniform, and organized fashion to provide blanket access to the full complement of data stored on a targeted data server. In this poster, we present an application of ADAPT to describe all of the data products that are stored by using the Common Data File (CDF) format served out by the CDAWEB and SPDF data servers hosted at the NASA Goddard Space Flight Center. These data servers are the primary repositories for NASA Heliophysics data. For this purpose, the ADAPT routines have been used to generate data resource descriptions by using an XML schema named Space Physics Archive, Search, and Extract (SPASE). SPASE is the designated standard for documenting Heliophysics data products, as adopted by the Heliophysics Data and Model Consortium. The set of SPASE XML resource descriptions produced by ADAPT includes high-level descriptions of numerical data products, display data products, or catalogs and also includes low-level "Granule" descriptions. A SPASE Granule is effectively a universal access metadata resource; a Granule associates an individual data file (e.g. a CDF file) with a "parent" high-level data resource description, assigns a resource identifier to the file, and lists the corresponding assess URL(s). The CDAWEB and SPDF file systems were queried to provide the input required by the ADAPT software to create an initial set of SPASE metadata resource descriptions. Then, the CDAWEB and SPDF data repositories were queried subsequently on a nightly basis and the CDF file lists were checked for any changes such as the occurrence of new, modified, or deleted
Balas, Mark J.; Thapa Magar, Kaman S.; Frost, Susan A.
2013-01-01
A theory called Adaptive Disturbance Tracking Control (ADTC) is introduced and used to track the Tip Speed Ratio (TSR) of 5 MW Horizontal Axis Wind Turbine (HAWT). Since ADTC theory requires wind speed information, a wind disturbance generator model is combined with lower order plant model to estimate the wind speed as well as partial states of the wind turbine. In this paper, we present a proof of stability and convergence of ADTC theory with lower order estimator and show that the state feedback can be adaptive.
Global error estimation based on the tolerance proportionality for some adaptive Runge-Kutta codes
Calvo, M.; González-Pinto, S.; Montijano, J. I.
2008-09-01
Modern codes for the numerical solution of Initial Value Problems (IVPs) in ODEs are based in adaptive methods that, for a user supplied tolerance [delta], attempt to advance the integration selecting the size of each step so that some measure of the local error is [similar, equals][delta]. Although this policy does not ensure that the global errors are under the prescribed tolerance, after the early studies of Stetter [Considerations concerning a theory for ODE-solvers, in: R. Burlisch, R.D. Grigorieff, J. Schröder (Eds.), Numerical Treatment of Differential Equations, Proceedings of Oberwolfach, 1976, Lecture Notes in Mathematics, vol. 631, Springer, Berlin, 1978, pp. 188-200; Tolerance proportionality in ODE codes, in: R. März (Ed.), Proceedings of the Second Conference on Numerical Treatment of Ordinary Differential Equations, Humbold University, Berlin, 1980, pp. 109-123] and the extensions of Higham [Global error versus tolerance for explicit Runge-Kutta methods, IMA J. Numer. Anal. 11 (1991) 457-480; The tolerance proportionality of adaptive ODE solvers, J. Comput. Appl. Math. 45 (1993) 227-236; The reliability of standard local error control algorithms for initial value ordinary differential equations, in: Proceedings: The Quality of Numerical Software: Assessment and Enhancement, IFIP Series, Springer, Berlin, 1997], it has been proved that in many existing explicit Runge-Kutta codes the global errors behave asymptotically as some rational power of [delta]. This step-size policy, for a given IVP, determines at each grid point tn a new step-size hn+1=h(tn;[delta]) so that h(t;[delta]) is a continuous function of t. In this paper a study of the tolerance proportionality property under a discontinuous step-size policy that does not allow to change the size of the step if the step-size ratio between two consecutive steps is close to unity is carried out. This theory is applied to obtain global error estimations in a few problems that have been solved with
Directory of Open Access Journals (Sweden)
Erik Aguirre
2015-02-01
Full Text Available One of the main challenges in the implementation and design of context-aware scenarios is the adequate deployment strategy for Wireless Sensor Networks (WSNs, mainly due to the strong dependence of the radiofrequency physical layer with the surrounding media, which can lead to non-optimal network designs. In this work, radioplanning analysis for WSN deployment is proposed by employing a deterministic 3D ray launching technique in order to provide insight into complex wireless channel behavior in context-aware indoor scenarios. The proposed radioplanning procedure is validated with a testbed implemented with a Mobile Ad Hoc Network WSN following a chain configuration, enabling the analysis and assessment of a rich variety of parameters, such as received signal level, signal quality and estimation of power consumption. The adoption of deterministic radio channel techniques allows the design and further deployment of WSNs in heterogeneous wireless scenarios with optimized behavior in terms of coverage, capacity, quality of service and energy consumption.
Offset-Free Model Predictive Control of Open Water Channel Based on Moving Horizon Estimation
Ekin Aydin, Boran; Rutten, Martine
2016-04-01
Model predictive control (MPC) is a powerful control option which is increasingly used by operational water managers for managing water systems. The explicit consideration of constraints and multi-objective management are important features of MPC. However, due to the water loss in open water systems by seepage, leakage and evaporation a mismatch between the model and the real system will be created. These mismatch affects the performance of MPC and creates an offset from the reference set point of the water level. We present model predictive control based on moving horizon estimation (MHE-MPC) to achieve offset free control of water level for open water canals. MHE-MPC uses the past predictions of the model and the past measurements of the system to estimate unknown disturbances and the offset in the controlled water level is systematically removed. We numerically tested MHE-MPC on an accurate hydro-dynamic model of the laboratory canal UPC-PAC located in Barcelona. In addition, we also used well known disturbance modeling offset free control scheme for the same test case. Simulation experiments on a single canal reach show that MHE-MPC outperforms disturbance modeling offset free control scheme.
Estimation of Outage Capacity for Free Space Optical Links Over I-K and K Turbulent Channels
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D. Marinos
2011-06-01
Full Text Available The free space optical communication systems are attracting great research and commercial interest due to their capability of transferring data, over short distances, with high rate and security, low cost demands and without licensing fees. However, their performance depends strongly on the atmospheric conditions in the link’s area. In this work, we investigate the influence of the turbulence on the outage capacity of such a system for weak to strong turbulence channels modeled by the I-K and the K-distribution and we derive closed-form expressions for its estimation. Finally, using these expressions we present numerical results for various link cases with different turbulence conditions.
Reservoir characterisation by a binary level set method and adaptive multiscale estimation
Energy Technology Data Exchange (ETDEWEB)
Nielsen, Lars Kristian
2006-01-15
The main focus of this work is on estimation of the absolute permeability as a solution of an inverse problem. We have both considered a single-phase and a two-phase flow model. Two novel approaches have been introduced and tested numerical for solving the inverse problems. The first approach is a multi scale zonation technique which is treated in Paper A. The purpose of the work in this paper is to find a coarse scale solution based on production data from wells. In the suggested approach, the robustness of an already developed method, the adaptive multi scale estimation (AME), has been improved by utilising information from several candidate solutions generated by a stochastic optimizer. The new approach also suggests a way of combining a stochastic and a gradient search method, which in general is a problematic issue. The second approach is a piecewise constant level set approach and is applied in Paper B, C, D and E. Paper B considers the stationary single-phase problem, while Paper C, D and E use a two-phase flow model. In the two-phase flow problem we have utilised information from both production data in wells and spatially distributed data gathered from seismic surveys. Due to the higher content of information provided by the spatially distributed data, we search solutions on a slightly finer scale than one typically does with only production data included. The applied level set method is suitable for reconstruction of fields with a supposed known facies-type of solution. That is, the solution should be close to piecewise constant. This information is utilised through a strong restriction of the number of constant levels in the estimate. On the other hand, the flexibility in the geometries of the zones is much larger for this method than in a typical zonation approach, for example the multi scale approach applied in Paper A. In all these papers, the numerical studies are done on synthetic data sets. An advantage of synthetic data studies is that the true
Adaptive multiscale MCMC algorithm for uncertainty quantification in seismic parameter estimation
Tan, Xiaosi
2014-08-05
Formulating an inverse problem in a Bayesian framework has several major advantages (Sen and Stoffa, 1996). It allows finding multiple solutions subject to flexible a priori information and performing uncertainty quantification in the inverse problem. In this paper, we consider Bayesian inversion for the parameter estimation in seismic wave propagation. The Bayes\\' theorem allows writing the posterior distribution via the likelihood function and the prior distribution where the latter represents our prior knowledge about physical properties. One of the popular algorithms for sampling this posterior distribution is Markov chain Monte Carlo (MCMC), which involves making proposals and calculating their acceptance probabilities. However, for large-scale problems, MCMC is prohibitevely expensive as it requires many forward runs. In this paper, we propose a multilevel MCMC algorithm that employs multilevel forward simulations. Multilevel forward simulations are derived using Generalized Multiscale Finite Element Methods that we have proposed earlier (Efendiev et al., 2013a; Chung et al., 2013). Our overall Bayesian inversion approach provides a substantial speed-up both in the process of the sampling via preconditioning using approximate posteriors and the computation of the forward problems for different proposals by using the adaptive nature of multiscale methods. These aspects of the method are discussed n the paper. This paper is motivated by earlier work of M. Sen and his collaborators (Hong and Sen, 2007; Hong, 2008) who proposed the development of efficient MCMC techniques for seismic applications. In the paper, we present some preliminary numerical results.
Im, Subin; Min, Soonhong
2013-04-01
Exploratory factor analyses of the Kirton Adaption-Innovation Inventory (KAI), which serves to measure individual cognitive styles, generally indicate three factors: sufficiency of originality, efficiency, and rule/group conformity. In contrast, a 2005 study by Im and Hu using confirmatory factor analysis supported a four-factor structure, dividing the sufficiency of originality dimension into two subdimensions, idea generation and preference for change. This study extends Im and Hu's (2005) study of a derived version of the KAI by providing additional evidence of the four-factor structure. Specifically, the authors test the robustness of the parameter estimates to the violation of normality assumptions in the sample using bootstrap methods. A bias-corrected confidence interval bootstrapping procedure conducted among a sample of 356 participants--members of the Arkansas Household Research Panel, with middle SES and average age of 55.6 yr. (SD = 13.9)--showed that the four-factor model with two subdimensions of sufficiency of originality fits the data significantly better than the three-factor model in non-normality conditions.
Fetterly, Kenneth A; Favazza, Christopher P
2016-08-07
Channelized Hotelling model observer (CHO) methods were developed to assess performance of an x-ray angiography system. The analytical methods included correction for known bias error due to finite sampling. Detectability indices ([Formula: see text]) corresponding to disk-shaped objects with diameters in the range 0.5-4 mm were calculated. Application of the CHO for variable detector target dose (DTD) in the range 6-240 nGy frame(-1) resulted in [Formula: see text] estimates which were as much as 2.9× greater than expected of a quantum limited system. Over-estimation of [Formula: see text] was presumed to be a result of bias error due to temporally variable non-stationary noise. Statistical theory which allows for independent contributions of 'signal' from a test object (o) and temporally variable non-stationary noise (ns) was developed. The theory demonstrates that the biased [Formula: see text] is the sum of the detectability indices associated with the test object [Formula: see text] and non-stationary noise ([Formula: see text]). Given the nature of the imaging system and the experimental methods, [Formula: see text] cannot be directly determined independent of [Formula: see text]. However, methods to estimate [Formula: see text] independent of [Formula: see text] were developed. In accordance with the theory, [Formula: see text] was subtracted from experimental estimates of [Formula: see text], providing an unbiased estimate of [Formula: see text]. Estimates of [Formula: see text] exhibited trends consistent with expectations of an angiography system that is quantum limited for high DTD and compromised by detector electronic readout noise for low DTD conditions. Results suggest that these methods provide [Formula: see text] estimates which are accurate and precise for [Formula: see text]. Further, results demonstrated that the source of bias was detector electronic readout noise. In summary, this work presents theory and methods to test for the
Li, Zheng; Zhang, Hai; Zhou, Qifan; Che, Huan
2017-09-05
The main objective of the introduced study is to design an adaptive Inertial Navigation System/Global Navigation Satellite System (INS/GNSS) tightly-coupled integration system that can provide more reliable navigation solutions by making full use of an adaptive Kalman filter (AKF) and satellite selection algorithm. To achieve this goal, we develop a novel redundant measurement noise covariance estimation (RMNCE) theorem, which adaptively estimates measurement noise properties by analyzing the difference sequences of system measurements. The proposed RMNCE approach is then applied to design both a modified weighted satellite selection algorithm and a type of adaptive unscented Kalman filter (UKF) to improve the performance of the tightly-coupled integration system. In addition, an adaptive measurement noise covariance expanding algorithm is developed to mitigate outliers when facing heavy multipath and other harsh situations. Both semi-physical simulation and field experiments were conducted to evaluate the performance of the proposed architecture and were compared with state-of-the-art algorithms. The results validate that the RMNCE provides a significant improvement in the measurement noise covariance estimation and the proposed architecture can improve the accuracy and reliability of the INS/GNSS tightly-coupled systems. The proposed architecture can effectively limit positioning errors under conditions of poor GNSS measurement quality and outperforms all the compared schemes.
Hofmann, K.M.; Gavrilla, D.M.
2009-01-01
We present a system for the estimation of unconstrained 3D human upper body movement from multiple cameras. Its main novelty lies in the integration of three components: single frame pose recovery, temporal integration and model adaptation. Single frame pose recovery consists of a hypothesis
Fuady, Ahmad; Houweling, Tanja A; Mansyur, Muchtaruddin; Richardus, Jan H
2018-01-01
Indonesia is the second-highest country for tuberculosis (TB) incidence worldwide. Hence, it urgently requires improvements and innovations beyond the strategies that are currently being implemented throughout the country. One fundamental step in monitoring its progress is by preparing a validated tool to measure total patient costs and catastrophic total costs. The World Health Organization (WHO) recommends using a version of the generic questionnaire that has been adapted to the local cultural context in order to interpret findings correctly. This study is aimed to adapt the Tool to Estimate Patient Costs questionnaire into the Indonesian context, which measures total costs and catastrophic total costs for tuberculosis-affected households. the tool was adapted using best-practice guidelines. On the basis of a pre-test performed in a previous study (referred to as Phase 1 Study), we refined the adaptation process by comparing it with the generic tool introduced by the WHO. We also held an expert committee review and performed pre-testing by interviewing 30 TB patients. After pre-testing, the tool was provided with complete explanation sheets for finalization. seventy-two major changes were made during the adaptation process including changing the answer choices to match the Indonesian context, refining the flow of questions, deleting questions, changing some words and restoring original questions that had been changed in Phase 1 Study. Participants indicated that most questions were clear and easy to understand. To address recall difficulties by the participants, we made some adaptations to obtain data that might be missing, such as tracking data to medical records, developing a proxy of costs and guiding interviewers to ask for a specific value when participants were uncertain about the estimated market value of property they had sold. the adapted Tool to Estimate Patient Costs in Bahasa Indonesia is comprehensive and ready for use in future studies on TB
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Yong Tian
2014-12-01
Full Text Available State of charge (SOC estimation is essential to battery management systems in electric vehicles (EVs to ensure the safe operations of batteries and providing drivers with the remaining range of the EVs. A number of estimation algorithms have been developed to get an accurate SOC value because the SOC cannot be directly measured with sensors and is closely related to various factors, such as ambient temperature, current rate and battery aging. In this paper, two model-based adaptive algorithms, including the adaptive unscented Kalman filter (AUKF and adaptive slide mode observer (ASMO are applied and compared in terms of convergence behavior, tracking accuracy, computational cost and estimation robustness against parameter uncertainties of the battery model in SOC estimation. Two typical driving cycles, including the Dynamic Stress Test (DST and New European Driving Cycle (NEDC are applied to evaluate the performance of the two algorithms. Comparison results show that the AUKF has merits in convergence ability and tracking accuracy with an accurate battery model, while the ASMO has lower computational cost and better estimation robustness against parameter uncertainties of the battery model.
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Yuan Zou
2010-09-01
Full Text Available In order to safely and efficiently use the power as well as to extend the lifetime of the traction battery pack, accurate estimation of State of Charge (SoC is very important and necessary. This paper presents an adaptive observer-based technique for estimating SoC of a lithium-ion battery pack used in an electric vehicle (EV. The RC equivalent circuit model in ADVISOR is applied to simulate the lithium-ion battery pack. The parameters of the battery model as a function of SoC, are identified and optimized using the numerically nonlinear least squares algorithm, based on an experimental data set. By means of the optimized model, an adaptive Luenberger observer is built to estimate online the SoC of the lithium-ion battery pack. The observer gain is adaptively adjusted using a stochastic gradient approach so as to reduce the error between the estimated battery output voltage and the filtered battery terminal voltage measurement. Validation results show that the proposed technique can accurately estimate SoC of the lithium-ion battery pack without a heavy computational load.
Jakeman, J. D.; Wildey, T.
2015-01-01
In this paper we present an algorithm for adaptive sparse grid approximations of quantities of interest computed from discretized partial differential equations. We use adjoint-based a posteriori error estimates of the physical discretization error and the interpolation error in the sparse grid to enhance the sparse grid approximation and to drive adaptivity of the sparse grid. Utilizing these error estimates provides significantly more accurate functional values for random samples of the sparse grid approximation. We also demonstrate that alternative refinement strategies based upon a posteriori error estimates can lead to further increases in accuracy in the approximation over traditional hierarchical surplus based strategies. Throughout this paper we also provide and test a framework for balancing the physical discretization error with the stochastic interpolation error of the enhanced sparse grid approximation.
International Nuclear Information System (INIS)
Jakeman, J.D.; Wildey, T.
2015-01-01
In this paper we present an algorithm for adaptive sparse grid approximations of quantities of interest computed from discretized partial differential equations. We use adjoint-based a posteriori error estimates of the physical discretization error and the interpolation error in the sparse grid to enhance the sparse grid approximation and to drive adaptivity of the sparse grid. Utilizing these error estimates provides significantly more accurate functional values for random samples of the sparse grid approximation. We also demonstrate that alternative refinement strategies based upon a posteriori error estimates can lead to further increases in accuracy in the approximation over traditional hierarchical surplus based strategies. Throughout this paper we also provide and test a framework for balancing the physical discretization error with the stochastic interpolation error of the enhanced sparse grid approximation
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Sara Bardestani
2017-09-01
Full Text Available Triangular channels have different applications in many water and wastewater engineering problems. For this purpose investigating hydraulic characteristics of flow in these sections has great importance. Researchers have presented different prediction methods for the velocity contours in prismatic sections. Most proposed methods are not able to consider the effect of walls roughness, the roughness distribution and secondary flows. However, due to complexity and nonlinearity of velocity contours in open channel flow, there is no simple relationship that can be fully able to exactly draw the velocity contours. In this paper an efficient approach for modeling velocity contours in triangular open channels with non-uniform roughness distributions by Adaptive Neuro-Fuzzy Inference System (ANFIS has been suggested. For training and testing model, the experimental data including 1703 data in triangular channels with geometric symmetry and non-uniform roughness distributions have been used. Comparing experimental results with predicted values by model indicates that ANFIS model is capable to be used in simulation of local velocity and determining velocity contours and the independent evaluation showed that the calculated values of discharge and depth-averaged velocity from model information are precisely in conformity with experimental values.
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Eyad K Almaita
2017-03-01
Keywords: Energy efficiency, Power quality, Radial basis function, neural networks, adaptive, harmonic. Article History: Received Dec 15, 2016; Received in revised form Feb 2nd 2017; Accepted 13rd 2017; Available online How to Cite This Article: Almaita, E.K and Shawawreh J.Al (2017 Improving Stability and Convergence for Adaptive Radial Basis Function Neural Networks Algorithm (On-Line Harmonics Estimation Application. International Journal of Renewable Energy Develeopment, 6(1, 9-17. http://dx.doi.org/10.14710/ijred.6.1.9-17
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Chidentree Treesatayapun
2015-06-01
Full Text Available An adaptive control scheme based on data-driven controller (DDC is proposed in this article. Unlike several DDC techniques, the proposed controller is constructed by an adaptive fuzzy rule emulated network (FREN which is able to include human knowledge based on controlled plant's input–output signals within the format of IF-THEN rules. Regarding to this advantage, an on-line estimation of pseudo partial derivative (PPD and resetting algorithms, which are commonly used by DDC, can be omitted here. Furthermore, a novel adaptive algorithm is introduced to minimize for both tracking error and control effort with stability analysis for the closed-loop system. The experimental system with brushed DC-motor current control is constructed to validate the performance of the proposed control scheme. Comparative results with conventional DDC and radial basis function (RBF controllers demonstrate that the proposed controller can provide the less tracking error and minimize the control effort.
Climate Change and Risk Management: Challenges for Insurance, Adaptation, and Loss Estimation
Kousky, Carolyn; Cooke, Roger
2009-01-01
Adapting to climate change will not only require responding to the physical effects of global warming, but will also require adapting the way we conceptualize, measure, and manage risks. Climate change is creating new risks, altering the risks we already face, and also, importantly, impacting the interdependencies between these risks. In this paper we focus on three particular phenomena of climate related risks that will require a change in our thinking about risk management: global micro-cor...