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.
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.
Energy Efficient Spectrum Sensing for State Estimation over A Wireless Channel
Cao, Xianghui; Zhou, Xiangwei; Cheng, Yu
2014-01-01
The performance of remote estimation over wireless channel is strongly affected by sensor data losses due to interference. Although the impact of interference can be alleviated by performing spectrum sensing and then transmitting only when the channel is clear, the introduction of spectrum sensing also incurs extra energy expenditure. In this paper, we investigate the problem of energy efficient spectrum sensing for state estimation of a general linear dynamic system, and formulate an optimiz...
Directory of Open Access Journals (Sweden)
A. Akbulut
2012-04-01
Full Text Available In this study, Particle Swarm Optimization is applied for the estimation of the channel state transition probabilities. Unlike most other studies, where the channel state transition probabilities are assumed to be known and/or constant, in this study, these values are realistically considered to be time-varying parameters, which are unknown to the secondary users of the cognitive radio systems. The results of this study demonstrate the following: without any a priori information about the channel characteristics, even in a very transient environment, it is quite possible to achieve reasonable estimates of channel state transition probabilities with a practical and simple implementation.
Institute of Scientific and Technical Information of China (English)
Ding Wenrui; Fei Li; Gao Qiang; Liu Shuo
2013-01-01
In this paper,we consider an amplify-and-forward (AF) cooperative communication system when the channel state information (CSI) used in relay selection differs from that during data transmission,i.e.,the CSI used in relay selection is outdated.The selected relay may not be actually the best for data transmission and the outage performance of the cooperative system will deteriorate.To improve its performance,we propose a relay selection strategy based on maximum a posteriori (MAP) estimation,where relay is selected based on predicted signal-to-noise ratio (SNR).To reduce the computation complexity,we approximate the a posteriori probability density of SNR and obtain a closed-form predicted SNR,and a relay selection strategy based on the approximate MAP estimation (RS-AMAP) is proposed.The simulation results show that this approximation leads to trivial performance loss from the perspective of outage probability.Compared with relay selection strategies given in the literature,the outage probability is reduced largely through RS-AMAP for medium-to-large transmitting powers and medium-to-high channel correlation coefficients.
Caire, Giuseppe; Kobayashi, Mari; Ravindran, Niranjay
2007-01-01
We consider a MIMO fading broadcast channel and compute achievable ergodic rates when channel state information is acquired at the receivers via downlink training and explicit channel feedback is performed to provide transmitter channel state information (CSIT). Both ``analog'' and quantized (digital) channel feedback are analyzed, and digital feedback is shown to be potentially superior when the feedback channel uses per channel coefficient is larger than 1. Also, we show that by proper design of the digital feedback link, errors in the feedback have a relatively minor effect even if simple uncoded modulation is used on the feedback channel. We extend our analysis to the case of fading MIMO Multiaccess Channel (MIMO-MAC) in the feedback link, as well as to the case of a time-varying channel and feedback delay. We show that by exploiting the MIMO-MAC nature of the uplink channel, a fully scalable system with both downlink multiplexing gain and feedback redundancy proportional to the number of base station ant...
Xu, Yong; Lu, Renquan; Shi, Peng; Li, Hongyi; Xie, Shengli
2016-12-15
This paper considers finite-time distributed state estimation for discrete-time nonlinear systems over sensor networks. The Round-Robin protocol is introduced to overcome the channel capacity constraint among sensor nodes, and the multiplicative noise is employed to model the channel fading. In order to improve the performance of the estimator under the situation, where the transmission resources are limited, fading channels with different stochastic properties are used in each round by allocating the resources. Sufficient conditions of the average stochastic finite-time boundedness and the average stochastic finite-time stability for the estimation error system are derived on the basis of the periodic system analysis method and Lyapunov approach, respectively. According to the linear matrix inequality approach, the estimator gains are designed. Finally, the effectiveness of the developed results are illustrated by a numerical example.
Using unsteady-state water level data to estimate channel roughness and discharge hydrograph
Aricò, Costanza; Nasello, Carmelo; Tucciarelli, Tullio
2009-08-01
A novel methodology for simultaneous discharge and channel roughness estimation is developed and applied to data sets available at three experimental sites. The methodology is based on the synchronous measurement of water level data in two river sections far some kilometers from each other, as well as on the use of a diffusive flow routing solver and does not require any direct velocity measurement. The methodology is first analyzed for the simplest case of a channel with a large slope, where the kinematic assumption holds. A sensitivity and a model error analysis are carried out in this hypothesis in order to show the stability of the results with respect to the error in the input parameters in the case of homogeneous roughness and to analyze the effect of unknown roughness heterogeneity on the estimated discharges. The methodology is then extended to the more general case of channels with mild slope and validated using field data previously collected in three Italian rivers: the Arno (in Tuscany), the Tiber (in Latium) and the Vallo di Diana, a small tributary of the Tanagro river (in Southern Italy). The performance of the proposed algorithm has been investigated according to three performance criteria estimating the quality of the match between the measured and the computed stage and discharge hydrographs. Results of the field tests can be considered good, despite the uncertainties of the field data and of the measured values.
Institute of Scientific and Technical Information of China (English)
LAI Rui-xun; FANG Hong-wei; HE Guo-jian; YU Xin; YANG Ming; WANG Ming
2013-01-01
In this paper,both state variables and parameters of one-dimensional open channel model are estimated using a framework of the Ensemble Kalman Filter (EnKF).Compared with observation,the predicted accuracy of water level and discharge are improved while the parameters of the model are identified simultaneously.With the principles of the EnKF,a state-space description of the Saint-Venant equation is constructed by perturbing the measurements with Gaussian error distribution.At the same time,the roughness,one of the key parameters in one-dimensional open channel,is also considered as a state variable to identify its value dynamically.The updated state variables and the parameters are then used as the initial values of the next time step to continue the assimilation process.The usefulness and the capability of the dual EnKF are demonstrated in the lower Yellow River during the water-sediment regulation in 2009.In the optimization process,the errors between the prediction and the observation are analyzed,and the rationale of inverse roughness is discussed.It is believed that (1) the flexible approach of the dual EnKF can improve the accuracy of predicting water level and discharge,(2) it provides a probabilistic way to identify the model error which is feasible to implement but hard to handle in other filter systems,and (3) it is practicable for river engineering and management.
Channel estimation in TDD mode
Institute of Scientific and Technical Information of China (English)
ZHANG Yi; GU Jian; YANG Da-cheng
2006-01-01
An efficient solution is proposed in this article for the channel estimation in time division duplex (TDD) mode wireless communication systems. In the proposed solution, the characteristics of fading channels in TDD mode systems are fully exploited to estimate the path delay of the fading channel.The corresponding amplitude is estimated using the minimum mean square error (MMSE) criterion. As a result, it is shown that the proposed novel solution is more accurate and efficient than the traditional solution, and the improvement is beneficial to the performance of Joint Detection.
Multiuser MIMO Channel Estimation
Directory of Open Access Journals (Sweden)
G.Indumathi
2016-05-01
Full Text Available In this paper, three beamforming design are considered for multi user MIMO system. First, transmit beamformers are fixed and the receive (RX beamformers are calculated. Transmit beamformer (TX-BFis projectedas a null space of appropriate channels. It reduces the interference for each user. Then the receiver beamformer is determined which maximize the SNR. This beamforming design provides less computation time. The second case is joint TX and RX beamformer for SNR maximization. In this transmitter and receiver beamformer are calculated using extended alternating optimization (EAO algorithm. The third one is joint transmitter and receiver beamforming for SNR and SINR maximization using EAO algorithm. This algorithm provides better error performance and sum rate performance. All the design cases are simulated by using standard multipath channel model. Our simulation results illustrate that compared to the least square design and zero forcing design, the joint TX and RX beamforming design using EAO algorithm provides faster beamforming and improved error performance and sum rate.
BLIND CHANNEL ESTIMATION IN DELAY DIVERSITY FOR FREQUENCY SELECTIVE CHANNELS
Institute of Scientific and Technical Information of China (English)
Zhao Zheng; Jia Ying; Yin Qinye
2003-01-01
Delay diversity is an effective transmit diversity technique to combat adverse ef-fects of fading. Thus far, previous work in delay diversity assumed that perfect estimates ofcurrent channel fading conditions are available at the receiver and training symbols are requiredto estimate the channel from the transmitter to the receiver. However, increasing the number ofthe antennas increases the required training interval and reduces the available time within whichdata may be transmitted. Learning the channel coefficients becomes increasingly difficult for thefrequency selective channels. In this paper, with the subspace method and the delay character ofdelay diversity, a channel estimation method is proposed, which does not use training symbols. Itaddresses the transmit diversity for a frequency selective channel from a single carrier perspectivein the form of a simple equivalent fiat fading model. Monte Carlo simulations give the perfor-mance of channel estimation and the performance comparison of our channel-estimation-baseddetector with decision feedback equalization, which uses the perfect channel information.
Coalson, Rob D; Cheng, Mary Hongying
2011-09-01
Analytical estimation of state-to-state rate constants is carried out for a recently developed discrete state model of chloride ion motion in a CLC chloride channel (Coalson and Cheng, J. Phys. Chem. B 2010, 114, 1424). In the original presentation of this model, the same rate constants were evaluated via three-dimensional Brownian dynamics simulations. The underlying dynamical theory is an appropriate single- or multiparticle three-dimensional Smoluchowski equation. Taking advantage of approximate geometric symmetries (based on the details of the model channel geometry), well-known formulas for state-to-state transition rates are appealed to herein and adapted as necessary to the problem at hand. Rates of ionic influx from a bulk electrolyte reservoir to the nearest binding site within the channel pore are particularly challenging to compute analytically because they reflect multi-ion interactions (as opposed to single-ion dynamics). A simple empirical correction factor is added to the single-ion rate constant formula in this case to account for the saturation of influx rate constants with increasing bulk Cl(-) concentration. Overall, the agreement between all analytically estimated rate constants is within a factor of 2 of those computed via three-dimensional Brownian dynamics simulations, and often better than this. Current-concentration curves obtained using rate constants derived from these two different computational approaches agree to within 25%.
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.
Semi-blind Channel Estimator for OFDM-STC
Institute of Scientific and Technical Information of China (English)
WU Yun; LUO Han-wen; SONG Wen-tao; HUANG Jian-guo
2007-01-01
Channel state information of OFDM-STC system is required for maximum likelihood decoding. A subspace-based semi-blind method was proposed for estimating the channels of OFDM-STC systems. The channels are first estimated blindly up to an ambiguity parameter utilizing the nature structure of STC, irrespective of the underlying signal constellations. Furthermore, a method was proposed to resolve the ambiguity by using a few pilot symbols. The simulation results show the proposed semi-blind estimator can achieve higher spectral efficiency and provide improved estimation performance compared to the non-blind estimator.
OFDM System Channel Estimation with Hidden Pilot
Institute of Scientific and Technical Information of China (English)
YANG Feng; LIN Cheng-yu; ZHANG Wen-jun
2007-01-01
Channel estimation using pilot is common used in OFDM system. The pilot is usually time division multiplexed with the informative sequence. One of the main drawbacks is bandwidth losing. In this paper, a new method was proposed to perform channel estimation in OFDM system. The pilot is arithmetically added to the output of OFDM modulator. Receiver uses the hidden pilot to get an accurate estimation of the channel. Then pilot is removed after channel estimation. The Cramer-Rao lower bound for this method was deprived. The performance of the algorithm is then shown. Compared with traditional methods, the proposed algorithm increases the bandwidth efficiency dramatically.
CHANNEL ESTIMATION FOR ITERATIVE DECODING OVER FADING CHANNELS
Institute of Scientific and Technical Information of China (English)
K. H. Sayhood; Wu Lenan
2002-01-01
A method of coherent detection and channel estimation for punctured convolutional coded binary Quadrature Amplitude Modulation (QAM) signals transmitted over a frequency-flat Rayleigh fading channels used for a digital radio broadcasting transmission is presented. Some known symbols are inserted in the encoded data stream to enhance the channel estimation process.The pilot symbols are used to replace the existing parity symbols so no bandwidth expansion is required. An iterative algorithm that uses decoding information as well as the information contained in the known symbols is used to improve the channel parameter estimate. The scheme complexity grows exponentially with the channel estimation filter length. The performance of the system is compared for a normalized fading rate with both perfect coherent detection (corresponding to a perfect knowledge of the fading process and noise variance) and differential detection of Differential Amplitude Phase Shift Keying (DAPSK). The tradeoff between simplicity of implementation and bit-error-rate performance of different techniques is also compared.
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.
Parameter estimation in channel network flow simulation
Institute of Scientific and Technical Information of China (English)
Han Longxi
2008-01-01
Simulations of water flow in channel networks require estimated values of roughness for all the individual channel segments that make up a network. When the number of individual channel segments is large, the parameter calibration workload is substantial and a high level of uncertainty in estimated roughness cannot be avoided. In this study, all the individual channel segments are graded according to the factors determining the value of roughness. It is assumed that channel segments with the same grade have the same value of roughness. Based on observed hydrological data, an optimal model for roughness estimation is built. The procedure of solving the optimal problem using the optimal model is described. In a test of its efficacy, this estimation method was applied successfully in the simulation of tidal water flow in a large complicated channel network in the lower reach of the Yangtze River in China.
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.
Channel Capacity Estimation using Free Probability Theory
Ryan, Øyvind
2007-01-01
In many channel measurement applications, one needs to estimate some characteristics of the channels based on a limited set of measurements. This is mainly due to the highly time varying characteristics of the channel. In this contribution, it will be shown how free probability can be used for channel capacity estimation in MIMO systems. Free probability has already been applied in various application fields such as digital communications, nuclear physics and mathematical finance, and has been shown to be an invaluable tool for describing the asymptotic behaviour of many systems when the dimensions of the system get large (i.e. the number of antennas). In particular, introducing the notion of free deconvolution, we provide hereafter an asymptotically (in the number of antennas) unbiased capacity estimator (w.r.t. the number of observations) for MIMO channels impaired with noise. Another unbiased estimator (for any number of observations) is also constructed by slightly modifying the free probability based est...
Methods for Estimating Capacities of Gaussian Quantum Channels
Pilyavets, Oleg V; Mancini, Stefano
2009-01-01
We present a perturbative approach to the problem of estimating capacities of Gaussian quantum channels. It relies on the expansion of the von Neumann entropy of Gaussian states as a function of the symplectic eigenvalues of the quadratures covariance matrices. We apply this method to the classical capacity of a lossy bosonic channel for both the memory and memoryless cases.
Spatial DCT-Based Channel Estimation in Multi-Antenna Multi-Cell Interference Channels
Alodeh, Maha; Chatzinotas, Symeon; Ottersten, Bjorn
2015-03-01
This work addresses channel estimation in multiple antenna multicell interference-limited networks. Channel state information (CSI) acquisition is vital for interference mitigation. Wireless networks often suffer from multicell interference, which can be mitigated by deploying beamforming to spatially direct the transmissions. The accuracy of the estimated CSI plays an important role in designing accurate beamformers that can control the amount of interference created from simultaneous spatial transmissions to mobile users. Therefore, a new technique based on the structure of the spatial covariance matrix and the discrete cosine transform (DCT) is proposed to enhance channel estimation in the presence of interference. Bayesian estimation and Least Squares estimation frameworks are introduced by utilizing the DCT to separate the overlapping spatial paths that create the interference. The spatial domain is thus exploited to mitigate the contamination which is able to discriminate across interfering users. Gains over conventional channel estimation techniques are presented in our simulations which are also valid for a small number of antennas.
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...
CHANNEL ESTIMATION FOR ITERATIVE DECODING OVER FADING CHANNELS
Institute of Scientific and Technical Information of China (English)
K.H.Sayhood; WuLenan
2002-01-01
A method of coherent detection and channel estimation for punctured convolutional coded binary Quadrature Amplitude Modulation (QAM) signals transmitted over a frequency-flat Rayleigh fading channels used for a digital radio broadcasting transmission is presented.Some known symbols are inserted in the encoded data stream to enhance the channel estimation process.The puilot symbols are used to replace the existing parity symbols so no bandwidth expansion is required.An iterative algorithm that uses decoding information as well as the information contained in the known symbols is used to improve the channel parameter estimate.The scheme complexity grows exponentially with the channel estimation filter length,The performance of the system is compared for a normalized fading rate with both perfect coherent detection(Corresponding to a perfect knowledge of the fading process and noise variance)and differential detection of Differential Amplitude Phase Shift Keying (DAPSK).The tradeoff between simplicity of implementation and bit-error-rate performance of different techniques is also compared.
Blind estimation of shallow water acoustic channel
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
This paper proposed a method for blind estimation of underwater channels in shallow water environment by using received data at a single hydrophone or from single beam.First, the received signal is used for source signal reconstruction by means of signal-dependent TF (Time-Frequency) distribution, in association with instantaneous frequency estimation and TF inversion. Then the shallow-water channel estimation is achieved via WRELAX technique by use of the received signal and the estimated source signal. Finally, the results of numerical simulation and experimental test from real data taken in South China Sea trial have proved satisfactory. It is shown that the proposed method is useful for underwater channel estimation.
Application of Bayesian Hierarchical Prior Modeling to Sparse Channel Estimation
DEFF Research Database (Denmark)
Pedersen, Niels Lovmand; Manchón, Carles Navarro; Shutin, Dmitriy
2012-01-01
. The estimators result as an application of the variational message-passing algorithm on the factor graph representing the signal model extended with the hierarchical prior models. Numerical results demonstrate the superior performance of our channel estimators as compared to traditional and state......Existing methods for sparse channel estimation typically provide an estimate computed as the solution maximizing an objective function defined as the sum of the log-likelihood function and a penalization term proportional to the l1-norm of the parameter of interest. However, other penalization......-of-the-art sparse methods....
On Channels with Action-Dependent States
Ahmadi, Behzad
2012-01-01
Action-dependent channels model scenarios in which transmission takes place in two successive phases. In the first phase, the encoder selects an "action" sequence, with the twofold aim of conveying information to the receiver and of affecting in a desired way the state of the channel to be used in the second phase. In the second phase, communication takes place in the presence the mentioned action-dependent state. In this work, two extensions of the original action-dependent channel are studied. In the first, the decoder is interested in estimating not only the message, but also the state sequence within an average per-letter distortion. Under the constraint of common knowledge (i.e., the decoder's estimate of the state must be recoverable also at the encoder) and assuming non-causal state knowledge at the encoder in the second phase, we obtain a single-letter characterization of the achievable rate-distortion-cost trade-off. In the second extension, we study an action-dependent degraded broadcast channel. Un...
Institute of Scientific and Technical Information of China (English)
Wang Hui-Song; Zeng Gui-Hua
2008-01-01
In this paper,the effect of imperfect channel state information at the receiver, which is caused by noise and other interference, on the multi-access channel capacity is analysed through a statistical-mechanical approach. Replica analyses focus on analytically studying how the minimum mean square error (MMSE) channel estimation error appears in a multiuser channel capacity formula. And the relevant mathematical expressions are derived. At the same time,numerical simulation results are demonstrated to validate the Replica analyses. The simulation results show how the system parameters, such as channel estimation error, system load and signal-to-noise ratio, affect the channel capacity.
Ahmad, Mukhtar
2012-01-01
State estimation is one of the most important functions in power system operation and control. This area is concerned with the overall monitoring, control, and contingency evaluation of power systems. It is mainly aimed at providing a reliable estimate of system voltages. State estimator information flows to control centers, where critical decisions are made concerning power system design and operations. This valuable resource provides thorough coverage of this area, helping professionals overcome challenges involving system quality, reliability, security, stability, and economy.Engineers are
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...
On Quantum Channel Estimation with Minimal Resources
Zorzi, M; Ferrante, A
2011-01-01
We determine the minimal experimental resources that ensure a unique solution in the estimation of trace-preserving quantum channels with both direct and convex optimization methods. A convenient parametrization of the constrained set is used to develop a globally converging Newton-type algorithm that ensures a physically admissible solution to the problem. Numerical simulations are provided to support the results, and indicate that the minimal experimental setting is sufficient to guarantee good estimates.
Channel Estimation Techniques in MIMO-OFDM LTE Systems
Directory of Open Access Journals (Sweden)
P. Venkateswarlu
2014-07-01
Full Text Available There is an increasing demand for high data transmission rates with the evolution of the very large scale integration (VLSI technology. The multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM systems are used to fulfill these requirements because of their unique properties such as high spectral efficiency, high data rate and resistance towards multipath propagation. MIMO-OFDM systems are finding their applications in the modern wireless communication systems like IEEE 802.11n, 4G and LTE. They also offer reliable communication with the increased coverage area. The bottleneck to the MIMO-OFDM systems is the estimation of the channel state information (CSI. This can be estimated with the help of any one of the Training Based, Semiblind and Blind Channel estimation algorithms. This paper presents various channel estimation algorithms, optimization techniques and their effective utilization in MIMO-OFDM for modern wireless LTE systems.
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.
Secure Broadcasting with Uncertain Channel State Information
Hyadi, Amal
2017-03-13
We investigate the problem of secure broadcasting over fast fading channels with imperfect main channel state information (CSI) at the transmitter. In particular, we analyze the effect of the noisy estimation of the main CSI on the throughput of a broadcast channel where the transmission is intended for multiple legitimate receivers in the presence of an eavesdropper. Besides, we consider the realistic case where the transmitter is only aware of the statistics of the eavesdropper\\'s CSI and not of its channel\\'s realizations. First, we discuss the common message transmission case where the source broadcasts the same information to all the receivers, and we provide an upper and a lower bounds on the ergodic secrecy capacity. For this case, we show that the secrecy rate is limited by the legitimate receiver having, on average, the worst main channel link and we prove that a non-zero secrecy rate can still be achieved even when the CSI at the transmitter is noisy. Then, we look at the independent messages case where the transmitter broadcasts multiple messages to the receivers, and each intended user is interested in an independent message. For this case, we present an expression for the achievable secrecy sum-rate and an upper bound on the secrecy sum-capacity and we show that, in the limit of large number of legitimate receivers K, our achievable secrecy sum-rate follows the scaling law log((1-a ) log(K)), where is the estimation error variance of the main CSI. The special cases of high SNR, perfect and no-main CSI are also analyzed. Analytical derivations and numerical results are presented to illustrate the obtained expressions for the case of independent and identically distributed Rayleigh fading channels.
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.
Performance Analysis of Hard Iterative Channel Estimation in Turbo Equalization
Institute of Scientific and Technical Information of China (English)
DENG Yongjun; YANG Zhixing; PAN Changyong; WANG Jun
2006-01-01
Reasonable bit error rate performance requires perfect channel state information (CSI) in traditional turbo equalization (TE), which is hard to obtain in practice. Soft and hard iterative algorithms have been developed to address the channel estimation problem with the performance of the soft iterative channel estimate based on the recursive least square algorithm. This paper presents an analysis of the performance of hard iterative channel estimation (HICE) based on the least mean square algorithm. The analysis uses a cost function with the hard decision on the TE output. An iterative channel correction (ICC) algorithm based on the gradient descent algorithm is used to iteratively minimize the cost function. The simulation results agree with the theoretical lower bound for the mean square error (MSE) of the estimated channels. Simulations show that, given an imperfect CSI with an MSE below the upper bound, the linear minimum mean squared error TE (LMMSE-TE) using the ICC has only small performance degradation compared to that with a perfect CSI, while the traditional LMMSE-TE suffers from severe error floor effect even with more iterations.
Secure Broadcasting with Uncertain Channel State Information
Hyadi, Amal
2016-01-06
We investigate the problem of secure broadcasting over fast fading channels with imperfect main channel state information (CSI) at the transmitter. In particular, we analyze the effect of the noisy estimation of the main CSI on the throughput of a broadcast channel where the transmission is intended for multiple legitimate receivers in the presence of an eavesdropper. Besides, we consider the realistic case where the transmitter is only aware of the statistics of the eavesdropper s CSI and not of its channel s realizations. First, we discuss the common message transmission case where the source broadcasts the same information to all the receivers, and we provide an upper and a lower bounds on the ergodic secrecy capacity. For this case, we show that the secrecy rate is limited by the legitimate receiver having, on average, the worst main channel link and we prove that a non-zero secrecy rate can still be achieved even when the CSI at the transmitter is noisy. Then, we look at the independent messages case where the transmitter broadcasts multiple messages to the receivers, and each intended user is interested in an independent message. For this case, we present an expression for the achievable secrecy sum-rate and an upper bound on the secrecy sum-capacity and we show that, in the limit of large number of legitimate receivers K, our achievable secrecy sum-rate follows the scaling law log((1-a ) log(K)), where is the estimation error variance of the main CSI. The special cases of high SNR, perfect and no-main CSI are also analyzed. Analytical derivations and numerical results are presented to illustrate the obtained expressions for the case of independent and identically distributed Rayleigh fading channels.
Multiple Parameter Estimation With Quantized Channel Output
Mezghani, Amine; Nossek, Josef A
2010-01-01
We present a general problem formulation for optimal parameter estimation based on quantized observations, with application to antenna array communication and processing (channel estimation, time-of-arrival (TOA) and direction-of-arrival (DOA) estimation). The work is of interest in the case when low resolution A/D-converters (ADCs) have to be used to enable higher sampling rate and to simplify the hardware. An Expectation-Maximization (EM) based algorithm is proposed for solving this problem in a general setting. Besides, we derive the Cramer-Rao Bound (CRB) and discuss the effects of quantization and the optimal choice of the ADC characteristic. Numerical and analytical analysis reveals that reliable estimation may still be possible even when the quantization is very coarse.
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.
A simple channel estimator for space-time coded OFDM systems in rapid fading channels
Institute of Scientific and Technical Information of China (English)
单淑伟; 罗汉文; 宋文涛
2004-01-01
A simple channel estimator for space-time coded orthogonal frequency division multiplexing (OFDM) systems in rapid fading channels is proposed. The channels at the training bauds are estimated using the EM (expectation-maximization) algorithm, while the channels at the data bauds are estimated based on the method for modelling the time-varying channel as the linear combination of several time-invariant " Doppler channels". Computer simulations showed that this estimator outperforms the decision-directed tracking in rapid fading channels and that the performance of this method can be improved by iteration.
A simple channel estimator for space-time coded OFDM systems in rapid fading channels
Institute of Scientific and Technical Information of China (English)
SHAN Shu-wei(单淑伟); LUO Han-wen(罗汉文); SONG Wen-tao(宋文涛)
2004-01-01
A simple channel estimator for space-time coded orthogonal frequency division multiplexing (OFDM) systems in rapid fading channels is proposed. The channels at the training bauds are estimated using the EM (expectation-maximization) algorithm, while the channels at the data bauds are estimated based on the method for modelling the time-varying channel as the linear combination of several time-invariant "Doppler channels". Computer simulations showed that this estimator outperforms the decision-directed tracking in rapid fading channels and that the performance of this method can be improved by iteration.
DEFF Research Database (Denmark)
Knudsen, Torben
2014-01-01
Dynamic inflow is an effect which is normally not included in the models used for wind turbine control design. Therefore, potential improvement from including this effect exists. The objective in this project is to improve the methods previously developed for this and especially to verify...... the results using full-scale wind turbine data. The previously developed methods were based on extended Kalman filtering. This method has several drawback compared to unscented Kalman filtering which has therefore been developed. The unscented Kalman filter was first tested on linear and non-linear test cases...... which was successful. Then the estimation of a wind turbine state including dynamic inflow was tested on a simulated NREL 5MW turbine was performed. This worked perfectly with wind speeds from low to nominal wind speed as the output prediction errors where white. In high wind where the pitch actuator...
On the low SNR capacity of MIMO fading channels with imperfect channel state information
Benkhelifa, Fatma
2014-05-01
The capacity of Multiple Input Multiple Output (MIMO) Rayleigh fading channels with full knowledge of channel state information (CSI) at both the transmitter and the receiver (CSI-TR) has been shown recently to scale at low Signal-to-Noise Ratio (SNR) essentially as SNR log(1=SNR), independently of the number of transmit and receive antennas. In this paper, we investigate the ergodic capacity of MIMO Rayleigh fading channel with estimated channel state information at the transmitter (CSI-T) and possibly imperfect channel state information at the receiver (CSI-R). Our framework can be seen as a generalization of previous works as it can capture the perfect CSI-TR as a special case when the estimation error variance goes to zero. In our work, we mainly focus on the low SNR regime and we show that the capacity scales as (1-α) SNR log(1=SNR), where α is the estimation error variance. This characterization shows the loss of performance due to error estimation over the perfect channel state information at both the transmitter and the receiver. As a by-product of our new analysis, we show that our framework can also be extended to characterize the capacity of MIMO Rician fading channels at low SNR with possibly imperfect CSI-T and CSI-R. © 2014 IFIP.
On the low SNR capacity of MIMO fading channels with imperfect channel state information
Benkhelifa, Fatma
2014-06-01
The capacity of multiple-input multiple-output (MIMO) Rayleigh fading channels with full knowledge of channel state information (CSI) at both the transmitter and the receiver (CSI-TR) has been shown recently to scale at low signal-to-noise ratio (SNR) essentially as SNR log(1/SNR), independently of the number of transmit and receive antennas. In this paper, we investigate the ergodic capacity of MIMO Rayleigh fading channel with estimated channel state information at the transmitter (CSI-T) and possibly imperfect channel state information at the receiver (CSI-R). Our framework can be seen as a generalization of previous works as it can capture the perfect CSI-TR as a special case when the estimation error variance goes to zero. In this paper, we mainly focus on the low SNR regime, and we show that the capacity scales as (1-α) SNR log(1/SNR), where α is the estimation error variance. This characterization shows the loss of performance due to error estimation over the perfect channel state information at both the transmitter and the receiver. As a by-product of our new analysis, we show that our framework can be also extended to characterize the capacity of MIMO Rician fading channels at low SNR with possibly imperfect CSI-T and CSI-R. © 1972-2012 IEEE.
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.
BLIND CHANNEL ESTIMATION OF SPACE-TIME FREQUENCY-SHIFT KEYING
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
The decoupled coherent Maximum Likelihood (ML) detection algorithm presented in this lettercan sharply reduce the complexity of the receiver as well as provide better error performance under the pre-condition that channel should be estimated first. Considering the bandwidth inefficiency of Frequency ShiftKeying (FSK), the acquisition of channel state information through training sequences will further decreasethe transmission efficiency. This letter presents a blind channel estimation algorithm based on noise subspacetheory which can acquire channel information without any training symbols. The simulation shows that thealgorithm brings about fewer channel estimation errors while the frequency efficiency can be increased.
Channel estimation for OFDM in mobile communication systems
Zheng, Kan; Zeng, Guoyan; Wang, Wenbo
2004-04-01
Orthogonal Frequency Division Multiplexing (OFDM)is one of the best candidates for the future mobile communication systems. This paper analyzes channel estimation algorithms for OFDM systems not only for the downlink but also for the uplink. With reasonable constraint and well-designed preambles for each user, the DFT-based uplink channel estimation algorithm on the uplink can achieve good estimation accuracy without sacrificing much system capacity. Computer simulation demonstrates effectiveness of channel estimation algorithms and conclusion is followed.
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.
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.
A Channelization-Based DOA Estimation Method for Wideband Signals.
Guo, Rui; Zhang, Yue; Lin, Qianqiang; Chen, Zengping
2016-07-04
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.
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.
Joint Synchronization and Channel Estimation for OFDM Systems
Institute of Scientific and Technical Information of China (English)
CAO Xue-hong
2005-01-01
OFDM systems are extremely sensitive to synchronization and channel estimation imperfections. Meanwhile the timing, frequency synchronization and channel estimation may affect each other. This paper investigates a new algorithm of joint estimation utilizing one training signal which can be used in preamble-based OFDM system, such as IEEE 802.11a WLAN system. The scheme includes two stages for performance improvement and simplicity. At the first stage, the coarse timing and frequency offset and channel response are obtained. The fine synchronization and channel estimation based on the coarse stage are obtained at the second stage. The simulation results show that the channel estimation of the proposed joint estimation is quite close to the case with known sync parameters and the BER of the system is quite close to the case with known channel response.
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.
Wang, Xin
2010-01-01
Optimal and suboptimal decentralized estimators in wireless sensor networks (WSNs) over orthogonal multiple-access fading channels are studied in this paper. Considering multiple-bit quantization before digital transmission, we develop maximum likelihood estimators (MLEs) with both known and unknown channel state information (CSI). When training symbols are available, we derive a MLE that is a special case of the MLE with unknown CSI. It implicitly uses the training symbols to estimate the channel coefficients and exploits the estimated CSI in an optimal way. To reduce the computational complexity, we propose suboptimal estimators. These estimators exploit both signal and data level redundant information to improve the estimation performance. The proposed MLEs reduce to traditional fusion based or diversity based estimators when communications or observations are perfect. By introducing a general message function, the proposed estimators can be applied when various analog or digital transmission schemes are u...
Blind channel estimation for redundant precoded OFDM systems
Institute of Scientific and Technical Information of China (English)
Liang Yongming; Luo Hanwen; Wu Yadong; Huang Jianguo
2007-01-01
Considering that channel estimation can play a crucial role in coherent detection of the information symbols in each data block, a blind channel estimation approach is proposed for redundant precoded orthogonal frequency-division multiplexing (OFDM) systems. A redundant linear frequency-domain precoder is applied to each pair of blocks before they enter the OFDM system. Because of the introduced structure, the frequency-selective channel can be identified at the receiver based on autocorrelation operations, singular value decomposition (SVD),and by resolving the scalar ambiguity. The proposed channel estimation method has low computational complexity and requires no prior statistical information on channel or noise. And the proposed blind method has high spectral efficiency owing to exploiting no training sequence. Computer simulations confirm that this proposed blind channel estimation method can identify the frequency-selective channels perfectly and obtain a good performance.
Robust Design of Pilot-symbol-aided MIMO Channel Estimation
Institute of Scientific and Technical Information of China (English)
LUO Zhen-dong; LIU Yuan-an; GAO Jin-chun
2004-01-01
This paper investigates pilot-symbol-aided channel estimation/prediction for Multiple-Input Multiple-Output (MIMO) systems in fast fading environments. We first derive the design criteria of the optimal pilot blocks for energy, power and bandwidth-limited systems, respectively. Then two low-complexity channel estimation schemes are provided. Finally, we present a robust Minimum Mean Square Error (MMSE) channel estimator based on channel time correlation. Simulation shows the proposed MMSE estimator is considerably insensitive to channel statistics and significantly outperforms the traditional estimators with a low additional complexity in fast fading environments. By simply adjusting some parameters, the MMSE estimator can work as an estimator and a predictor simultaneously.
Gui, Guan; 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.
Novel Channel Estimation Method Based on Decision-Directed in OFDM
Institute of Scientific and Technical Information of China (English)
BU Xiang-yuan; ZHANG Jian-kang; YANG Jing
2009-01-01
Based on the analysis of decision-directed (DD) channel estimation by using training symbols,a novel DD channel estimation method is proposed for orthogonal frequency division multiplexing (OFDM) system.The proposed algorithm takes the impact of decision error into account,and calculates the impact to next symbol duration channel state information.Analysis shows that the error propagation can be effectively restrained and the channel variation is tracked well.Simulation results demonstrate that both the signal error rate (SER) and the normalized mean square error (NMSE) performance of the proposed method are better than the traditional DD (DD+ IS) and the maximum likelihood estimate (DD+ MLE) method.
Estimation of Sparse MIMO Channels with Common Support
Barbotin, Yann; Rangan, Sundeep; Vetterli, Martin
2011-01-01
We consider the problem of estimating sparse communication channels in the MIMO context. In small to medium bandwidth communications, as in the current standards for OFDM and CDMA communication systems (with bandwidth up to 20 MHz), such channels are individually sparse and at the same time share a common support set. Since the underlying physical channels are inherently continuous-time, we propose a parametric sparse estimation technique based on finite rate of innovation (FRI) principles. Parametric estimation is especially relevant to MIMO communications as it allows for a robust estimation and concise description of the channels. The core of the algorithm is a generalization of conventional spectral estimation methods to multiple input signals with common support. We show the application of our technique for channel estimation in OFDM (uniformly/contiguous DFT pilots) and CDMA downlink (Walsh-Hadamard coded schemes). In the presence of additive white Gaussian noise, theoretical lower bounds on the estimat...
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 ...
An Adaptive Channel Estimation Technique in MIMO OFDM Systems
Institute of Scientific and Technical Information of China (English)
Pei-Sheng Pan; Bao-Yu Zheng
2008-01-01
In this paper, an adaptive channel estimation for MIMO OFDM is proposed. A set of pilot tones first are placed in each OFDM block, then the channel frequency response of these pilot tones are adaptively estimated by reeursive least squares (RLS) directly in frequency domain not in time domain. Then after the estimation of the channel frequency response of pilot tones, to obtain the channel frequency response of data tones, a new interpolation method based on DFT different from traditional linear interpolation method according to adjacent pilot tones is proposed. Simulation results show good performance of the technique.
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.
A Study of Channel Estimation for OFDM WLAN System
Institute of Scientific and Technical Information of China (English)
CAOXuehong
2005-01-01
This paper addresses two important issues in channel estimation for OFDM system: the selection of the pilot tones and the interpolation methods. We first obtain the minimum number and the optimal position sets of the pilot tones, and the MSE bound of the channel estimation. Then two special schemes of channel estimate for IEEE802.11a WLAN system are proposed, which are named as LS method and interpolation method. We compare the performance by measuring MSE of the channel estimate and BER with BPSK, QPSK and 16QAM as uncoded OFDM modulations. The simulation results show that these two proposed schemes are pretty good especially for interpolation method. The MSE of these estimations are close to the bound, and the BER performance of uncoded system is very close to the case with known channel response.
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.
Wavelet Based Semi-blind Channel Estimation For Multiband OFDM
Sadough, Sajad; Jaffrot, Emmanuel; Duhamel, Pierre
2007-01-01
This paper introduces an expectation-maximization (EM) algorithm within a wavelet domain Bayesian framework for semi-blind channel estimation of multiband OFDM based UWB communications. A prior distribution is chosen for the wavelet coefficients of the unknown channel impulse response in order to model a sparseness property of the wavelet representation. This prior yields, in maximum a posteriori estimation, a thresholding rule within the EM algorithm. We particularly focus on reducing the number of estimated parameters by iteratively discarding ``unsignificant'' wavelet coefficients from the estimation process. Simulation results using UWB channels issued from both models and measurements show that under sparsity conditions, the proposed algorithm outperforms pilot based channel estimation in terms of mean square error and bit error rate and enhances the estimation accuracy with less computational complexity than traditional semi-blind methods.
The Diversity Potential of Relay Selection with Practical Channel Estimation
Michalopoulos, Diomidis S; Schober, Robert; Karagiannidis, George K
2011-01-01
We investigate the diversity order of decode-and-forward relay selection in Nakagami-m fading, in cases where practical channel estimation techniques are applied. In this respect, we introduce a unified model for the imperfect channel estimates, where the effects of noise, time-varying channels, and feedback delays are jointly considered. Based on this model, the correlation between the actual and the estimated channel values, \\rho, is expressed as a function of the signal-to-noise ratio (SNR), yielding closed-form expressions for the overall outage probability as a function of \\rho. The resulting diversity order and power gain reveal a high dependence of the performance of relay selection on the high SNR behavior of \\rho, thus shedding light onto the effect of channel estimation on the overall performance. It is shown that when the channel estimates are not frequently updated in applications involving time-varying channels, or when the amount of power allocated for channel estimation is not sufficiently high...
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.
Hadei, Sayed A
2011-01-01
In this paper, we propose novel low-complexity adaptive channel estimation techniques for mob ile wireless chan- n els in presence of Rayleigh fading, carrier frequency offsets (CFO) and random channel variations. We show that the selective p artial update of the estimated channel tap-weight vector offers a better trade-off between the performance and computational complexity, compared to the full update of the estimated channel tap-weight vector. We evaluate the mean-square weight error of th e proposed methods and demonstrate the usefulness of its via simulation studies.
Estimation and Direct Equalization of Doubly Selective Channels
Directory of Open Access Journals (Sweden)
Leus Geert
2006-01-01
Full Text Available We propose channel estimation and direct equalization techniques for transmission over doubly selective channels. The doubly selective channel is approximated using the basis expansion model (BEM. Linear and decision feedback equalizers implemented by time-varying finite impulse response (FIR filters may then be used to equalize the doubly selective channel, where the time-varying FIR filters are designed according to the BEM. In this sense, the equalizer BEM coefficients are obtained either based on channel estimation or directly. The proposed channel estimation and direct equalization techniques range from pilot-symbol-assisted-modulation- (PSAM- based techniques to blind and semiblind techniques. In PSAM techniques, pilot symbols are utilized to estimate the channel or directly obtain the equalizer coefficients. The training overhead can be completely eliminated by using blind techniques or reduced by combining training-based techniques with blind techniques resulting in semiblind techniques. Numerical results are conducted to verify the different proposed channel estimation and direct equalization techniques.
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.
Channel Estimation Based in Comb-Type Pilots Arrangement for OFDM System over Time Varying Channel
Directory of Open Access Journals (Sweden)
Hala M. Mahmoud
2010-07-01
Full Text Available Orthogonal Frequency Division Multiplexing (OFDM has been recently applied widely in wireless communication systems, due to its high data rate, transmission capability with high bandwidth, efficiency and its robustness to multipath delay .Channel estimation is an essential problem in OFDM system. Pilot-aided channel estimation has been used; a good choice of the pilot pattern should match the channel behavior both in time and frequency domains. We explored comb pilot arrangements. The advantage for comb type pilots arrangement in channel estimation is the ability to track the variation of the channel caused by doppler frequency, it is observed that the doppler effect can be reduced, and so this will increase the system mobility. Kalman and Least Square (LS estimators have been proposed to estimate the Channel Frequency Response (CFR at the pilots location, then CFR at data sub channels are obtained by mean of interpolation between estimates at pilot locations. Different types of interpolations have been used such as; low pass interpolation; spline cubic interpolation and linear interpolation. Kalman estimation has better performance than LS estimation. The estimators perform about the same for SNR lower than 10 dB. The performances of all schemes have been compared by finding Bit Error Rate (BER, where BPSK modulation scheme was used.
Interference Alignment with Analog Channel State Feedback
Ayach, Omar El
2010-01-01
Interference alignment (IA) is a multiplexing gain optimal transmission strategy for the interference channel with an arbitrary number of users. While the achieved sum rate with IA is much higher than previously thought possible, the improvement comes at the cost of requiring network channel state information at the transmitters. This can be achieved by explicit feedback, a flexible yet costly approach that incurs large overhead and limits throughput. We propose using analog feedback as an alternative to limited feedback or reciprocity based alignment. We show that the full multiplexing gain observed with perfect channel knowledge is preserved by analog feedback and the mean loss in sum rate is bounded by a constant when signal-to-noise ratio is comparable in both forward and feedback channels. When such feedback quality is not quite possible, a fraction of the degrees of freedom is achieved. We consider the overhead of training and feedback and use this framework to optimize the system's effective throughput...
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.
A Novel Pilot Expansion Approach for MIMO Channel Estimation
Directory of Open Access Journals (Sweden)
Ming Fei SIYAU
2015-05-01
Full Text Available A training-based MIMO channel estimation scheme is presented to operate in severe frequency and time selective fading channels. Besides the new pilot bits designed from the ‘Paley-Hadamard’ matrix to exploit its orthogonal and ‘Toeplitz-like’ structures and minimising its pilot length, a novel pilot expansion technique is proposed to estimate the length of the channel impulse response, by flexibly extending its pilot length as required in order to capture the number of multipath existed within the MIMO channel. The pilot expansion can also help to deduce the initial channel variation and its Doppler rate which can be subsequently applied for MIMO channel tracking using decision feedback Kalman filter during the data payload.
Wiretap Channel with Causal State Information
Chia, Yeow-Khiang
2010-01-01
A lower bound on the secrecy capacity of the wiretap channel with state information available causally at both the encoder and decoder is established. The lower bound is shown to be strictly larger than that for the noncausal case by Liu and Chen. Achievability is proved using block Markov coding, Shannon strategy, and key generation from common state information. The state sequence available at the end of each block is used to generate a key, which is used to enhance the transmission rate of the confidential message in the following block. An upper bound on the secrecy capacity when the state is available noncausally at the encoder and decoder is established and is shown to coincide with the lower bound for several classes of wiretap channels with state.
Dual Turbo MIMO-OFDM Channel Estimation Based on Puncher Technique via UWA Channels
Directory of Open Access Journals (Sweden)
Gang Qiao
2013-02-01
Full Text Available In this study, various techniques of UWA (Underwater Acoustic, UWA channel estimation for underwater MIMO-OFDM system are studied. Dual turbo channel estimation algorithm based on channel puncture technique is proposed. In order to judge the criteria of channel compensation, difference between the raw received signal and the re-coded information signal is carried out. The uncertain sub-channels are punched by using channel puncture technique and replaced by the responses estimated by MMSE (Minimum Mean Square Error, MMSE or OMP (Orthogonal Matching Pursuit, OMP algorithms. Compared with the conventional existing algorithms, the proposed algorithm can effectively reduce the occupancy of pilots, offer confined error propagation and significantly increase the stability of the system with Monte Caro simulation. The results of in-tank-experiment further indorse the reliable performance with improved efficiency of 1.51 bits/s/Hz.
Adaptive channel estimation for soft decision decoding over non-Gaussian optical channel
Xiang, Jing-song; Miao, Tao-tao; Huang, Sheng; Liu, Huan-lin
2016-10-01
An adaptive priori likelihood ratio (LLR) estimation method is proposed over non-Gaussian channel in the intensity modulation/direct detection (IM/DD) optical communication systems. Using the nonparametric histogram and the weighted least square linear fitting in the tail regions, the LLR is estimated and used for the soft decision decoding of the low-density parity-check (LDPC) codes. This method can adapt well to the three main kinds of intensity modulation/direct detection (IM/DD) optical channel, i.e., the chi-square channel, the Webb-Gaussian channel and the additive white Gaussian noise (AWGN) channel. The performance penalty of channel estimation is neglected.
Impact of channel estimation error on channel capacity of multiple input multiple output system
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
In order to investigate the impact of channel estimation error on channel capacity of multiple input multiple output (MIMO) system, a novel method is proposed to explore the channel capacity in correlated Rayleigh fading environment. A system model is constructed based on the channel estimation error at receiver side. Using the properties of Wishart distribution, the lower bound of the channel capacity is derived when the MIMO channel is of full rank. Then a method is proposed to select the optimum set of transmit antennas based on the lower bound of the mean channel capacity. The novel method can be easily implemented with low computational complexity. The simulation results show that the channel capacity of MIMO system is sensitive to channel estimation error, and is maximized when the signal-to-noise ratio increases to a certain point. Proper selection of transmit antennas can increase the channel capacity of MIMO system by about 1 bit/s in a flat fading environment with deficient rank of channel matrix.
Sparse Recovery Algorithms for Pilot Assisted MIMO OFDM Channel Estimation
Qi, Chenhao; Wu, Lenan
In this letter, the sparse recovery algorithm orthogonal matching pursuit (OMP) and subspace pursuit (SP) are applied for MIMO OFDM channel estimation. A new algorithm named SOMP is proposed, which combines the advantage of OMP and SP. Simulation results based on 3GPP spatial channel model (SCM) demonstrate that SOMP performs better than OMP and SP in terms of normalized mean square error (NMSE).
Channel Estimation And Multiuser Detection In Asynchronous Satellite Communications
Chaouech, Helmi; 10.5121/ijwmn.2010.2411
2010-01-01
In this paper, we propose a new method of channel estimation for asynchronous additive white Gaussian noise channels in satellite communications. This method is based on signals correlation and multiuser interference cancellation which adopts a successive structure. Propagation delays and signals amplitudes are jointly estimated in order to be used for data detection at the receiver. As, a multiuser detector, a single stage successive interference cancellation (SIC) architecture is analyzed and integrated to the channel estimation technique and the whole system is evaluated. The satellite access method adopted is the direct sequence code division multiple access (DS CDMA) one. To evaluate the channel estimation and the detection technique, we have simulated a satellite uplink with an asynchronous multiuser access.
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.
Wavelet Based Semi-blind Channel Estimation For Multiband OFDM
Sadough, Sajad; Ichir, Mahieddine; Jaffrot, Emmanuel; Duhamel, Pierre
2007-01-01
This paper introduces an expectation-maximization (EM) algorithm within a wavelet domain Bayesian framework for semi-blind channel estimation of multiband OFDM based UWB communications. A prior distribution is chosen for the wavelet coefficients of the unknown channel impulse response in order to model a sparseness property of the wavelet representation. This prior yields, in maximum a posteriori estimation, a thresholding rule within the EM algorithm. We particularly focus on reducing the nu...
Radio Channel State Prediction by Kalman Filter
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Peter Ziacik
2005-01-01
Full Text Available In this article there is the description Kalman filter using as a radio channel state predictor. Simulator of prediction has been created in MATLAB environment and it is capable to simulate the prediction of radio signal envelope by Clark’s model of radio channel, which is implemented to the simulator. Simulations were realized for prediction range 0.41 ms and 6.24 ms and as comparing criterion we used the prediction error. It is clear from simulations, that with the duration of prediction the prediction error is enlarging, which may cause the erroneous decision of adaptation algorithms.
Institute of Scientific and Technical Information of China (English)
MAZhangyong; YANYongqing; ZHAOChunming; YOUXiaohu
2003-01-01
In this paper, an improved channel esti-mation algorithm based on tracking the level crossing rate (LCR) for fading rate is proposed in the CDMA systems with the continuous pilot channel. By using a simple LCRestimator, the Doppler-shift can be calculated approxi-mately, thus the observation length of the channel estima-tion can be adjusted dynamically. The procedure is pre-sented which includes the iterative algorithm for the time varying channel. Moreover, computer simulation results show that the algorithm achieves good tradeoff between the noise compression capability and the channel tracking performance.
Selective transmission and channel estimation in massive MIMO systems
Institute of Scientific and Technical Information of China (English)
杨睿哲
2016-01-01
Massive MIMO systems have got extraordinary spectral efficiency using a large number of base station antennas, but it is in the challenge of pilot contamination using the aligned pilots.To address this issue, a selective transmission is proposed using time-shifted pilots with cell grouping, where the strong interfering users in downlink transmission cells are temporally stopped during the pilots transmission in uplink cells.Based on the spatial characteristics of physical channel models, the strong interfering users are selected to minimize the inter-cell interference and the cell grouping is designed to have less temporally stopped users within a smaller area.Furthermore, a Kalman estima-tor is proposed to reduce the unexpected effect of residual interferences in channel estimation, which exploits both the spatial-time correlation of channels and the share of the interference information. The numerical results show that our scheme significantly improves the channel estimation accuracy and the data rates.
State Estimation for Tensegrity Robots
Caluwaerts, Ken; Bruce, Jonathan; Friesen, Jeffrey M.; Sunspiral, Vytas
2016-01-01
Tensegrity robots are a class of compliant robots that have many desirable traits when designing mass efficient systems that must interact with uncertain environments. Various promising control approaches have been proposed for tensegrity systems in simulation. Unfortunately, state estimation methods for tensegrity robots have not yet been thoroughly studied. In this paper, we present the design and evaluation of a state estimator for tensegrity robots. This state estimator will enable existing and future control algorithms to transfer from simulation to hardware. Our approach is based on the unscented Kalman filter (UKF) and combines inertial measurements, ultra wideband time-of-flight ranging measurements, and actuator state information. We evaluate the effectiveness of our method on the SUPERball, a tensegrity based planetary exploration robotic prototype. In particular, we conduct tests for evaluating both the robot's success in estimating global position in relation to fixed ranging base stations during rolling maneuvers as well as local behavior due to small-amplitude deformations induced by cable actuation.
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.
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.
Channel estimation for MIMO-OFDM systems in mobile wireless channels
Institute of Scientific and Technical Information of China (English)
WU Yun; LUO Han-wen; SONG Wen-tao
2008-01-01
A channel estimation method is proposed for multiple-input multiple-output orthogonal frequency di-vision multiplexing (MIMO-OFDM) systems in time-varying fading channels. In this method, a decision-direct-ed space-ahernating generalized expectation-maximization (SAGE) algorithm is introduced to the tracking of time-varying fading. In order to improve the estimation performance of the SAGE algorithm, a low rank approxi-mation method is presented by using the signal subspaee of the channel frequency autocorrelation matrix. The study reveals that this method can be incorporated into the SAGE algorithm. Furthermore, a modified fast sub-space tracking algorithm is given to adaptively estimate the signal subspace by utilizing training OFDM blocks sent at regular interval. Simulation results demonstrate the considerable benefits of the proposed channel estima-tion method.
Adaptive Bit Loading Scheme with Semi-Blind Channel Estimation for OFDM Systems
Institute of Scientific and Technical Information of China (English)
LI Ying; SU Guang-chuan
2006-01-01
An adaptive bit loading and power-allocation scheme is proposed in order to augment the performance of the system based on orthogonal frequency division multiplexing (OFDM), which is based on the maximum power margin. Coinciding with the adaptive loading scheme, a semi-blind channel estimation algorithm using subspace decomposition method is proposed, which uses the information in the cyclic prefix. An initial channel state information is estimated by using the training sequences with the method of interpolation filtering. The proposed adaptive scheme is simulated on an OFDM wireless local area network(WLAN) system in a time-varying channel. The performance is compared to the constant loading scheme.
Sparse Channel Estimation for Dual-Hop Amplify-and-Forward Cooperative Communiacion Systems
Directory of Open Access Journals (Sweden)
Guan Gui
2013-01-01
Full Text Available Cooperative transmission is one of key techniques which can improve system capacity and transmit range with limit power in the next-generation communication systems. However, accurate Channel State Information (CSI is necessary at the destination for coherent detection. Consider a Dual-Hop Amplify-and-Forward (DHAF Cooperative Communication System (CCS, traditional linear channel estimation method, e.g., Least Square (LS, based assumption of the rich multipath cascaded channel, is robust and simple while at the cost of low spectrum efficiency. Recent channel measurements have shown that the wireless channel exhibits great sparse in some highdimensional space. In this study, we confirmed that cascaded channel exhibits sparse distribution if the two individual channels are sparse by using representative simulation results. Later, we propose an efficient sparse channel estimation method to take advantage of the inherent sparse prior information in DHAF CCS. Simulation results confirm the superiority of our proposed methods over LS-based linear channel estimation method.
Spatially Common Sparsity Based Adaptive Channel Estimation and Feedback for FDD Massive MIMO
Gao, Zhen; Dai, Linglong; Wang, Zhaocheng; Chen, Sheng
2015-12-01
This paper proposes a spatially common sparsity based adaptive channel estimation and feedback scheme for frequency division duplex based massive multi-input multi-output (MIMO) systems, which adapts training overhead and pilot design to reliably estimate and feed back the downlink channel state information (CSI) with significantly reduced overhead. Specifically, a non-orthogonal downlink pilot design is first proposed, which is very different from standard orthogonal pilots. By exploiting the spatially common sparsity of massive MIMO channels, a compressive sensing (CS) based adaptive CSI acquisition scheme is proposed, where the consumed time slot overhead only adaptively depends on the sparsity level of the channels. Additionally, a distributed sparsity adaptive matching pursuit algorithm is proposed to jointly estimate the channels of multiple subcarriers. Furthermore, by exploiting the temporal channel correlation, a closed-loop channel tracking scheme is provided, which adaptively designs the non-orthogonal pilot according to the previous channel estimation to achieve an enhanced CSI acquisition. Finally, we generalize the results of the multiple-measurement-vectors case in CS and derive the Cramer-Rao lower bound of the proposed scheme, which enlightens us to design the non-orthogonal pilot signals for the improved performance. Simulation results demonstrate that the proposed scheme outperforms its counterparts, and it is capable of approaching the performance bound.
Channel estimation for MIMO-OFDM systems in wireless mobile channels
Institute of Scientific and Technical Information of China (English)
Lu Zhen; Ge Jianhua
2008-01-01
New training sequences and frame structure are proposed to estimate time-varying channel for multiple-input multiple-output and orthogonal frequency division multiplexing (MIMO-OFDM) systems. The training sequences are modulatable orthogonal polyphase sequences, which have both good autocorrelations and cross-correlations. The channel impulse response (CIR) can be obtained by measuring the correlation between the received training sequence and the locally generated training sequence. The training sequences are used as guard interval instead of cyclic prefix, which not only improve the transmission efficiency but also enable the channel estimator to track time-varying channel. The simulation results show that the proposed method has about 2dB SNR gain over conventional methods in fast time-varying channel.
On the capacity of cognitive radio under limited channel state information over fading channels
Rezki, Zouheir
2011-06-01
A spectrum-sharing communication system where the secondary user is aware of the instantaneous channel state information (CSI) of the secondary link, but knows only the statistics and an estimated version of the secondary transmitter-primary receiver (ST-PR) link, is investigated. The optimum power profile and the ergodic capacity of the secondary link are derived for general fading channels (with continuous probability density function) under average and peak transmit-power constraints and with respect to two different interference constraints: an interference outage constraint and a signal-to-interference (SI) outage constraint. When applied to Rayleigh fading channels, our results show, for instance, that the interference constraint is harmful at high-power regime, whereas at low-power regime, it has a marginal impact and no-interference performance may be achieved. © 2011 IEEE.
A New Adaptive Channel Estimation for Frequency Selective Time Varying Fading OFDM Channels
Afifi, Wessam M
2010-01-01
In this paper a new algorithm for adaptive dynamic channel estimation for frequency selective time varying fading OFDM channels is proposed. The new algorithm adopts a new strategy that successfully increases OFDM symbol rate. Instead of using a fixed training pilot sequence, the proposed algorithm uses a logic controller to choose among several available training patterns. The controller choice is based on the cross-correlation between pilot symbols over two consecutive time instants (which is considered to be a suitable measure of channel stationarity) as well as the deviation from the desired BER. Simulation results of the system performance confirm the effectiveness of this new channel estimation technique over traditional non-adaptive estimation methods in increasing the data rate of OFDM symbols while maintaining the same probability of error.
PERFORMANCE ANALYSIS OF CHANNEL ESTIMATION FOR LDPC-CODED OFDM SYSTEM IN MULTIPATH FADING CHANNEL
Institute of Scientific and Technical Information of China (English)
Zhu Qi; Li Hao; Feng Guangzeng
2006-01-01
In this paper, the channel estimation techniques for Orthogonal Frequency Division Multiplexing (OFDM) systems based on pilot arrangement are studied and we apply Low Density Parity Check (LDPC) codes to the system of IEEE 802.16a with OFDM modulation. First investigated is the influence of channel estimation schemes on LDPC-code based OFDM system in static and multipath fading channels. According to the different propagation environments in 802.16a system, a dynamic channel estimation scheme is proposed.A good irregular LDPC code is designed with code rate of 1/2 and code length of 1200. Simulation results show that the performance of LDPC coded OFDM system proposed in this paper is better than that of the convolution Turbo coded OFDM system proposed in IEEE standard 802.16a.
Channel Estimation for MIMO MC-CDMA Systems
Sureshkumar, K; Vetrikanimozhi, A
2011-01-01
The concepts of MIMO MC-CDMA are not new but the new technologies to improve their functioning are an emerging area of research. In general, most mobile communication systems transmit bits of information in the radio space to the receiver. The radio channels in mobile radio systems are usually multipath fading channels, which cause inter-symbol interference (ISI) in the received signal. To remove ISI from the signal, there is a need of strong equalizer. In this thesis we have focused on simulating the MIMO MC-CDMA systems in MATLAB and designed the channel estimation for them.
Ergodic Capacity of Cognitive Radio under Imperfect Channel State Information
Rezk, Zouheir
2012-01-01
A spectrum-sharing communication system where the secondary user is aware of the instantaneous channel state information (CSI) of the secondary link, but knows only the statistics and an estimated version of the secondary transmitter-primary receiver (ST-PR) link, is investigated. The optimum power profile and the ergodic capacity of the secondary link are derived for general fading channels (with continuous probability density function) under average and peak transmit-power constraints and with respect to two different interference constraints: an interference outage constraint and a signal-to-interference outage constraint. When applied to Rayleigh fading channels, our results show, for instance, that the interference constraint is harmful at high-power regime in the sense that the capacity does not increase with the power, whereas at low-power regime, it has a marginal impact and no-interference performance corresponding to the ergodic capacity under average or peak transmit power constraint in absence of ...
Institute of Scientific and Technical Information of China (English)
Jiang Wei; Xiang Haige
2004-01-01
This paper addresses the issues of channel estimation in a Multiple-Input/Multiple-Output (MIMO) system. Markov Chain Monte Carlo (MCMC) method is employed to jointly estimate the Channel State Information (CSI) and the transmitted signals. The deduced algorithms can work well under circumstances of low Signal-to-Noise Ratio (SNR). Simulation results are presented to demonstrate their effectiveness.
Modeling, Real-Time Estimation, and Identification of UWB Indoor Wireless Channels
Energy Technology Data Exchange (ETDEWEB)
Olama, Mohammed M [ORNL; Djouadi, Seddik M [ORNL; Li, Yanyan [ORNL; Fathy, Aly [University of Tennessee (UT)
2013-01-01
In this paper, stochastic differential equations (SDEs) are used to model ultrawideband (UWB) indoor wireless channels. We show that the impulse responses for time-varying indoor wireless channels can be approximated in a mean square sense as close as desired by impulse responses that can be realized by SDEs. The state variables represent the inphase and quadrature components of the UWB channel. The expected maximization and extended Kalman filter are employed to recursively identify and estimate the channel parameters and states, respectively, from online received signal strength measured data. Both resolvable and non-resolvable multipath received signals are considered and represented as small-scaled Nakagami fading. The proposed models together with the estimation algorithm are tested using UWB indoor measurement data demonstrating the method s viability and the results are presented.
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
Tufvesson, Fredrik
2000-01-01
This thesis deals with certain aspects in the design of wireless communications systems. It is focused on problems related to the mobile or wireless channel: synchronization, channel estimation and design of wireless orthogonal frequency division multiplex (OFDM) systems. There is a short introduction to the field of wireless systems and a deeper review of pervious work and the state of the art in each of the research fields. Throughout the thesis the goal has been to analyze the problems ana...
Crosstalk Channel Estimation via Standardized Two-Port Measurements
Directory of Open Access Journals (Sweden)
2009-03-01
Full Text Available The emerging multiuser transmission techniques for enabling higher data rates in the copper-access network relies upon accurate knowledge of the twisted-pair cables. In particular, the square-magnitude of the crosstalk channels between the transmission lines are of interest for crosstalk-mitigation techniques. Acquiring such information normally requires dedicated apparatus since crosstalk-channel measurement is not included in the current digital subscriber line (DSL standards. We address this problem by presenting a standard-compliant estimator for the square-magnitude of the frequency-dependent crosstalk channels that uses only functionality existing in today's standards. The proposed estimator is evaluated by laboratory experiments with standard-compliant DSL modems and real copper access network cables. The estimation results are compared with both reference measurements and with a widely used crosstalk model. The results indicate that the proposed estimator obtains an estimate of the square-magnitude of the crosstalk channels with a mean deviation from the reference measurement less than 3 dB for most frequencies.
Channel Impulse Response Estimation in IEEE 802.11p via Data Fusion and MMSE Estimator
Directory of Open Access Journals (Sweden)
Giulio Ministeri
2015-01-01
Full Text Available Tracking the channel impulse response in systems based on the IEEE 802.11p standard, the most widely accepted standard for the physical layer in vehicular area networks (VANETs, is still an open research topic. In this paper we aim to improve previously proposed channel estimators by utilizing data aided algorithm that includes the channel decoding to enhance the quality of the estimated data. Moreover we propose a novel technique that exploits information provided by external sensors like GPS or speedometer, usually present in vehicles. The algorithm proposed so far has been analyzed in non-line-of-sight link conditions; in this paper we present an analysis of performances in the line-of-sight condition as well. Simulations show that both proposals give considerable improvements in terms of packet error rate and channel estimation error in the highway scenario which is surely the most stressing environment for the channel response tracker.
Single channel signal component separation using Bayesian estimation
Institute of Scientific and Technical Information of China (English)
Cai Quanwei; Wei Ping; Xiao Xianci
2007-01-01
A Bayesian estimation method to separate multicomponent signals with single channel observation is presented in this paper. By using the basis function projection, the component separation becomes a problem of limited parameter estimation. Then, a Bayesian model for estimating parameters is set up. The reversible jump MCMC (Monte Carlo Markov Chain) algorithmis adopted to perform the Bayesian computation. The method can jointly estimate the parameters of each component and the component number. Simulation results demonstrate that the method has low SNR threshold and better performance.
Channel Sounding for the Masses: Low Complexity GNU 802.11b Channel Impulse Response Estimation
Firooz, Mohammad H; Zhang, Junxing; Patwari, Neal; Kasera, Sneha K
2010-01-01
New techniques in cross-layer wireless networks are building demand for ubiquitous channel sounding, that is, the capability to measure channel impulse response (CIR) with any standard wireless network and node. Towards that goal, we present a software-defined IEEE 802.11b receiver and CIR estimation system with little additional computational complexity compared to 802.11b reception alone. The system implementation, using the universal software radio peripheral (USRP) and GNU Radio, is described and compared to previous work. By overcoming computational limitations and performing direct-sequence spread-spectrum (DS-SS) matched filtering on the USRP, we enable high-quality yet inexpensive CIR estimation. We validate the channel sounder and present a drive test campaign which measures hundreds of channels between WiFi access points and an in-vehicle receiver in urban and suburban areas.
Analysis of OFDM System using Pilot Channel Estimation
Directory of Open Access Journals (Sweden)
Amit
2012-04-01
Full Text Available Orthogonal Frequency Division Multiplexing (OFDM ismultiplexing technology of orthogonal multicarrier, and thechannel estimation model based on pilot in OFDM systemsis analyzed; Now that, the channel estimation based onpilot needs interpolation, in order to reduce the complexityof the interpolation algorithm, the FFT channel estimationalgorithm based on pilot is studied. Because of the directFFT channel estimation algorithm existing energy spectrumleakage problems, the optimized FFT channel estimationalgorithm based on the Hamming windowed function is putforward. A lot of conventional algorithms have tried tocancel the residual frame synchronization error (RFSE,which causes the performance degradation of channelestimation when using interpolation between pilot subcarriersin comb-type pilot-aided OFDM systems.Orthogonal frequency-division multiplexing (OFDM is atransmission technique that is based on many orthogonalcarriers that are transmitted simultaneously. Channelestimation techniques for OFDM systems, based on combtypepilot arrangement, over frequency-selective Rican andtime-varying fading channel are investigated. Theadvantage of comb-type pilot arrangement, in channelestimation, is the ability to track the variation in thechannel, which is the main reason for inter-carrierinterference modeled as an additive white Gaussian noise,leading to an increase in the noise level.
Channel Estimation using Adaptive Filtering for LTE-Advanced
Directory of Open Access Journals (Sweden)
Saqib Saleem
2011-05-01
Full Text Available For demand of high data rates, enhanced system capacity and coverage, ITU made proposal for the standardization of next generation wireless communication systems, known as IMT-Advanced. To achieve these targets, a priori knowledge of the channel is required at the transmitter side. In this paper, three adaptive channel estimation techniques: Least Mean Square (LMS, Recursive Least Square (RLS and Kalman-Filtering Based, are compared in terms of performance and complexity. For performance, Mean Square Error (MSE and Symbol Error Rate (SER while for complexity, computational time is measured for variable channel impulse response (CIR lengths and channel taps. MATLAB Monte-Carlo Simulations are used to evaluate these techniques.
Polynomial based Channel Estimation Technique with Sliding Window for M-QAM Systems
Directory of Open Access Journals (Sweden)
O. O. Ogundile
2016-11-01
Full Text Available Pilot Symbol Assisted Modulation (PSAM channel estimation techniques over Rayleigh fading channels have been analysed in recent years. Fluctuations in the Rayleigh fading channel gain degrades the performance of any modulation scheme. This paper develops and analyses a PSAM Polynomial interpolation technique based on Least Square (LS approxi-mations to estimate the Channel State Information (CSI for M-ary Quadrature Amplitude Modulation (M-QAM over flat Rayleigh fading channels. A Sliding window approach with pilot symbol adjustment is employed in order to minimize the computational time complexity of the estimation technique. The channel estimation performance, and its computational delay and time complexity is verified for di?erent Doppler frequen-cies ( fd, frame lengths (L, and Polynomial orders (P-orders. Simulation results show that the Cubic Polynomial interpolation gives superior Symbol Error Rate (SER performance than the Quadratic Polynomial interpolation and higher P-orders, and the performance of the Polynomial estimation techniques degrade with increase in the P-orders.
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.
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.
Over-sampling basis expansion model aided channel estimation for OFDM systems with ICI
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
The rapid variation of channel can induce the intercarrier interference in orthogonal frequency-division multiplexing (OFDM) systems. Intercarrier interference will significantly increase the difficulty of OFDM channel estimation because too many channel coefficients need be estimated. In this article, a novel channel estimator is proposed to resolve the above problem. This estimator consists of two parts: the channel parameter estimation unit (CPEU), which is used to estimate the number of channel taps and the multipath time delays, and the channel coefficient estimation unit (CCEU), which is used to estimate the channel coefficients by using the estimated channel parameters provided by CPEU. In CCEU, the over-sampling basis expansion model is resorted to solve the problem that a large number of channel coefficients need to be estimated. Finally, simulation results are given to scale the performance of the proposed scheme.
Hou, Xueying; Kiong, Buon; Lau,
2010-01-01
Base station (BS) cooperative transmission can improve the spectrum efficiency of cellular systems, whereas using which the channels will become asymmetry. In this paper, we study the impact of the asymmetry on the performance of channel estimation and precoding in downlink BS cooperative multiple-antenna multiple-carrier systems. We first present three linear estimators which jointly estimate the channel coefficients from users in different cells with minimum mean square error, robust design and least square criterion, and then study the impact of uplink channel asymmetry on their performance. It is shown that when the large scale channel information is exploited for channel estimation, using non-orthogonal training sequences among users in different cells leads to minor performance loss. Next, we analyze the impact of downlink channel asymmetry on the performance of precoding with channel estimation errors. Our analysis shows that although the estimation errors of weak cross links are large, the resulting r...
Estimation of discharge and its distribution in compound channels
Institute of Scientific and Technical Information of China (English)
MOHANTY Prabir Kumar; KHATUA Kishanjit Kumar
2014-01-01
Results of research into a compound channel having width ratio (a) in excess of 11 are presented in the form of boun-dary shear distributions across the compound cross section. New relationship is derived between the percentage of shear carried by the flood plains (%S fp ) and the percentage of area occupied by the flood plains (%Afp ) . The equation so derived is taken as the basis to develop a new methodology to predict the stage discharge relationship specifically for wide compound channels using Darcy’s friction factor ( f ) for the main channel and flood plain regions. The methodology also is used for compound channels with smaller width ratios by applying the appropriate relation for %S fp derived earlier by different researchers and seems to work well. Next, as a corollary to the methodology, separate formulae are proposed to estimate flow distribution in main channel and flood plain regions. The proposed method and its corollary are tested for their validity against well-published small-scale data series of pre-vious researchers along with some large-scale data series from EPSRC-FCF (A-Series) compound channel experiments and very good agreement is observed between the measured values and predicted values for total flow as well as zonal distribution of flow. The methodology is also applied to some compound river section data published in literature and is found to serve well the purpose of predicting flow in real world application. This new method gives the least RMS value of error for discharge prediction compared with some other well-known methods used for estimating stage-discharge relation in compound channels by considering all data sets.
Min, Rui
2012-01-01
In this paper, channel estimation and data detection for multihop relaying orthogonal frequency division multiplexing (OFDM) system is investigated under time-varying channel. Different from previous works, which highly depend on the statistical information of the doubly-selective channel (DSC) and noise to deliver accurate channel estimation and data detection results, we focus on more practical scenarios with unknown channel orders and Doppler frequencies. Firstly, we integrate the multilink, multihop channel matrices into one composite channel matrix. Then, we formulate the unknown channel using generalized complex exponential basis expansion model (GCE-BEM) with a large oversampling factor to introduce channel sparsity on delay-Doppler domain. To enable the identification of nonzero entries, sparsity enhancing Gaussian distributions with Gamma hyperpriors are adopted. An iterative algorithm is developed under variational inference (VI) framework. The proposed algorithm iteratively estimate the channel, re...
Estimation of channel impulse response and FPGA simulation
Directory of Open Access Journals (Sweden)
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.
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...
Fast DOA estimation using wavelet denoising on MIMO fading channel
Meenakshi, A V; Kayalvizhi, R; Asha, S
2011-01-01
This paper presents a tool for the analysis, and simulation of direction-of-arrival (DOA) estimation in wireless mobile communication systems over the fading channel. It reviews two methods of Direction of arrival (DOA) estimation algorithm. The standard Multiple Signal Classification (MUSIC) can be obtained from the subspace based methods. In improved MUSIC procedure called Cyclic MUSIC, it can automatically classify the signals as desired and undesired based on the known spectral correlation property and estimate only the desired signal's DOA. In this paper, the DOA estimation algorithm using the de-noising pre-processing based on time-frequency conversion analysis was proposed, and the performances were analyzed. This is focused on the improvement of DOA estimation at a lower SNR and interference environment. This paper provides a fairly complete image of the performance and statistical efficiency of each of above two methods with QPSK signal.
Channel estimation based on distributed compressed sensing in amplify-and-forward relay networks
Institute of Scientific and Technical Information of China (English)
WANG Dong-hao; NIU Kai; HE Zhi-qiang; TIAN Bao-yu
2010-01-01
In orthogonal frequency-division multiplexing(OFDM)amplify-and-forward(AF)relay networks,in order to exploit diversity gains over frequency-selective fading channels,the receiver needs to acquire the knowledge of channel state information(CSI).In this article,based on the recent methodology of distributed compressed sensing(DCS),a novel channel estimation scheme is proposed.The joint sparsity model 2(JSM-2)in DCS theory and simultaneous orthogonal matching pursuit(SOMP)are both introduced to improve the estimation performance and increase the spectral efficiency.Simulation results show that compared with current compressed sensing(CS)methods,the estimation error of our scheme is reduced dramatically in high SNR region while the pilot number is still kept small.
Secure Broadcasting with Imperfect Channel State Information at the Transmitter
Hyadi, Amal
2015-11-13
We investigate the problem of secure broadcasting over fast fading channels with imperfect main channel state information (CSI) at the transmitter. In particular, we analyze the effect of the noisy estimation of the main CSI on the throughput of a broadcast channel where the transmission is intended for multiple legitimate receivers in the presence of an eavesdropper. Besides, we consider the realistic case where the transmitter is only aware of the statistics of the eavesdropper’s CSI and not of its channel’s realizations. First, we discuss the common message transmission case where the source broadcasts the same information to all the receivers, and we provide an upper and a lower bounds on the ergodic secrecy capacity. For this case, we show that the secrecy rate is limited by the legitimate receiver having, on average, the worst main channel link and we prove that a non-zero secrecy rate can still be achieved even when the CSI at the transmitter is noisy. Then, we look at the independent messages case where the transmitter broadcasts multiple messages to the receivers, and each intended user is interested in an independent message. For this case, we present an expression for the achievable secrecy sum-rate and an upper bound on the secrecy sum-capacity and we show that, in the limit of large number of legitimate receivers K, our achievable secrecy sum-rate follows the scaling law log((1−) log(K)), where is the estimation error variance of the main CSI. The special cases of high SNR, perfect and no-main CSI are also analyzed. Analytical derivations and numerical results are presented to illustrate the obtained expressions for the case of independent and identically distributed Rayleigh fading channels.
Fast and Robust CD and DGD Estimation Based on Data-Aided Channel Estimation
DEFF Research Database (Denmark)
Pittalà, Fabio; Hauske, Fabian N.; Ye, Yabin;
2011-01-01
In this paper data-aided (DA) frequency domain (FD) channel estimation in a 2×2 multi-input-multi-output (MIMO) system is investigated. Using orthogonal training sequences, fast and robust CD and DGD estimation is demonstrated for a 112 Gbit/s PDM-QPSK system over a wide range of combined linear...
Weighted-noise threshold based channel estimation for OFDM systems
Indian Academy of Sciences (India)
Pallaviram Sure; Chandra Mohan Bhuma
2015-10-01
Orthogonal frequency division multiplexing (OFDM) technology is the key to evolving telecommunication standards including 3GPP-LTE Advanced and WiMAX. Reliability of any OFDM system increases with improvedmean square error performance (MSE) of its channel estimator (CE). Particularly, a least squares (LS) based CE incorporating a time-domain denoising threshold, enables better MSE performance, while avoiding the need for a-priori knowledge of channel statistics (KCS). Existing optimal time-domain thresholds exhibit suboptimal behavior for completely unavailable KCS environments. This is because they involve consistent estimation of one or more KCS parameters, and corresponding estimation errors introduce severe degradation in MSE performance of the CE. To overcome the MSE degradation, this paper proposes a weighted-noise threshold, by introducing a modified hypothesis-testing-problem (HTP) interpretation. Derivation of resulting analytical MSE expression is also provided. Results of OFDM system simulations carried out in rayleigh faded ITU-TU6 and WiMAX-SUI4 channel environments with U-shaped power spectral densities, are presented. The performance results show that, compared to many of the existing thresholds, the proposed threshold renders better MSE performance to the CE and higher reliability to the OFDM system in terms of better bit error rate (BER) performance.
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.
Institute of Scientific and Technical Information of China (English)
Nguyen ThanhSon; Guo Shuxu; Chen Haipeng
2013-01-01
Multipath arrivals in an Ultra-WideBand (UWB) channel have a long time intervals between clusters and rays where the signal takes on zero or negligible values.It is precisely the signal sparsity of the impulse response of the UWB channel that is exploited in this work aiming at UWB channel estimation based on Compressed Sensing (CS).However,these multipath arrivals mainly depend on the channel environments that generate different sparse levels (low-sparse or high-sparse) of the UWB channels.According to this basis,we have analyzed the two most basic recovery algorithms,one based on linear programming Basis Pursuit (BP),another using greedy method Orthogonal Matching Pursuit (OMP),and chosen the best recovery algorithm which are suitable to the sparse level for each type of channel environment.Besides,the results of this work is an open topic for further research aimed at creating a optimal algorithm specially for application of CS based UWB systems.
Contributions in Radio Channel Sounding, Modeling, and Estimation
DEFF Research Database (Denmark)
Pedersen, Troels
2009-01-01
the necessary and sufficient conditions for spatio-temporal apertures to minimize the Cramer-Rao lower bound on the joint bi-direction and Doppler frequency estimation. The spatio-temporal aperture also impacts on the accuracy of MIMO-capacity estimation from measurements impaired by colored phase noise. We......, than corresponding results from literature. These findings indicate that the per-path directional spreads (or cluster spreads) assumed in standard models are set too large. Finally, we propose a model of the specular-to-diffuse transition observed in measurements of reverberant channels. The model...
Asyhari, A Taufiq; Fàbregas, Albert Guillén i
2011-01-01
We study a noncoherent multiple-input multiple-output (MIMO) fading multiple-access channel (MAC), where the transmitters and the receiver are aware of the statistics of the fading, but not of its realisation. We analyse the rate region that is achievable with nearest neighbour decoding and pilot-assisted channel estimation and determine the corresponding pre-log region, which is defined as the limiting ratio of the rate region to the logarithm of the SNR as the SNR tends to infinity.
Low-complexity fractional phase estimation for totally blind channel estimation
Institute of Scientific and Technical Information of China (English)
Xu Wang; Tao Yang; Bo Hu
2015-01-01
To remove the scalar ambiguity in conventional blind channel estimation algorithms, total y blind channel estimation (TBCE) is proposed by using multiple constel ations. To estimate the unknown scalar, its phase is decomposed into a fractional phase and an integer phase. However, the maximum-likelihood (ML) algorithm for the fractional phase does not have closed-form solutions and suffers from high computational complexity. By ex-ploring the structures of widely used constel ations, this paper proposes a low-complexity fractional phase estimation algorithm which requires no exhaustive search. Analytical expressions of the asymptotic mean squared error (MSE) are also derived. The theo-retical analysis and simulation results indicate that the proposed fractional phase estimation algorithm exhibits almost the same performance as the ML algorithm but with significantly reduced computational burden.
State energy data report 1994: Consumption estimates
Energy Technology Data Exchange (ETDEWEB)
NONE
1996-10-01
This document provides annual time series estimates of State-level energy consumption by major economic sector. The estimates are developed in the State Energy Data System (SEDS), operated by EIA. SEDS provides State energy consumption estimates to members of Congress, Federal and State agencies, and the general public, and provides the historical series needed for EIA`s energy models. Division is made for each energy type and end use sector. Nuclear electric power is included.
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.
A Comparative Analysis of LS and MMSE Channel Estimation Techniques for MIMO-OFDM System
Directory of Open Access Journals (Sweden)
Avinash Sahu
2014-06-01
Full Text Available Multiple transmit and receive antennas can be used to form multiple-input multiple-output (MIMO channels to increase the capacity by a factor of the minimum number of transmit and receive antennas. In this paper, orthogonal frequency division multiplexing (OFDM for MIMO channels (MIMO-OFDM is considered for wideband transmission to mitigate intersymbol interference and enhance system capacity. In this paper performance analysis of channel estimation through different algorithms for estimating channel using BPSK modulation scheme are investigated for different channel delay spread. The estimation of channel at pilot frequencies is based on Least Square, Minimum mean square channel estimation algorithm. We have compared the performances of these two channel estimation algorithm by measuring bit error rate Vs SNR. Minimum Mean Square estimation has been shown to perform much better than Least Square channel estimation algorithm.
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.
Conceptual Study of OFDM-Coding, PAPR Reduction, Channel Estimation
Directory of Open Access Journals (Sweden)
S S Riya Rani
2014-06-01
Full Text Available At present for high data rate transmission, Orthogonal Frequency Division Multiplexing (OFDM which is one of multi-carrier modulation (MCM techniques offers a considerable spectral efficiency; multipath delay spread tolerance, immunity to the frequency selective fading channels and power efficiency. As a result, OFDM has widely been deployed in many wireless communication standards such as Digital Video Broadcasting (DVB.In using turbo codes for OFDM performance can be sufficiently improved as seen in LTE standard systems. One of the challenging issues for Orthogonal Frequency Division Multiplexing (OFDM system is its high Peak-to-Average Power Ratio (PAPR. In this paper we present turbo coded OFDM systems, its channel estimation scheme and methods for reducing PAPR in the system.
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.
State Alcohol-Impaired-Driving Estimates
... estimates presented, and for 2012 range from a low of 10-percent known BACs to a high of 91-percent known BACs. States with higher rates of known BACs yield estimates of fatal crash alcohol involvement with greater accuracy and precision. State-by-State ...
State energy data report 1993: Consumption estimates
Energy Technology Data Exchange (ETDEWEB)
NONE
1995-07-01
The State Energy Data Report (SEDR) provides annual time series estimates of State-level energy consumption by major economic sector. The estimates are developed in the State Energy Data System (SEDS), which is maintained and operated by the Energy Information Administration (EIA). The goal in maintaining SEDS is to create historical time series of energy consumption by State that are defined as consistently as possible over time and across sectors. SEDS exists for two principal reasons: (1) to provide State energy consumption estimates to Members of Congress, Federal and State agencies, and the general public; and (2) to provide the historical series necessary for EIA`s energy models.
Power system operations: State estimation distributed processing
Ebrahimian, Mohammad Reza
We present an application of a robust and fast parallel algorithm to power system state estimation with minimal amount of modifications to existing state estimators presently in place using the Auxiliary Problem Principle. We demonstrate its effectiveness on IEEE test systems, the Electric Reliability Counsel of Texas (ERCOT), and the Southwest Power Pool (SPP) systems. Since state estimation formulation may lead to an ill-conditioned system, we provide analytical explanations of the effects of mixtures of measurements on the condition of the state estimation information matrix. We demonstrate the closeness of the analytical equations to condition of several test case systems including IEEE RTS-96 and IEEE 118 bus systems. The research on the condition of the state estimation problem covers the centralized as well as distributed state estimation.
Information-guided communications in MIMO systems with channel state impairments
Yang, Yuli
2013-06-20
Information-guided channel hopping (IGCH) is a promising technique for high-data-rate communications using multiple antennas for information mapping at the transmitter and optional antenna diversity at the receiver. Compared with some popular multi-antenna techniques, the advantage of this scheme is proven in ideal channel conditions, where the channel is spatially white and the perfect channel state information is assumed available at the receiver. The main objective of this paper is to present an information theoretical study on IGCH in realistic propagation environments with channel degeneracy due to spatial correlation and keyhole phenomena as well as imperfect channel estimation. It is proven that good performance promised by IGCH can be achieved in a variety of non-ideal channel conditions. Moreover, the analysis in this paper provides a convenient tool for the corresponding system design in practical operating environments. © 2013 John Wiley & Sons, Ltd.
VLSI IMPLEMENTATION OF CHANNEL ESTIMATION FOR MIMO-OFDM TRANSCEIVER
Directory of Open Access Journals (Sweden)
Joseph Gladwin Sekar
2013-01-01
Full Text Available In this study the VLSI architecture for MIMO-OFDM transceiver and the algorithm for the implementation of MMSE detection in MIMO-OFDM system is proposed. The implemented MIMO-OFDM system is capable of transmitting data at high throughput in physical layer and provides optimized hardware resources while achieving the same data rate. The proposed architecture has low latency, high throughput and efficient resource utilization. The result obtained is compared with the MATLAB results for verification. The main aim is to reduce the hardware complexity of the channel estimation.
Equalization of Time-Varying Dispersive Channels via Sequence Estimation.
1983-07-13
Vol. 4, Academic Press 1975. [8] F. R. Magee and J. G. Proakis , "Adaptive Maximum-Likelihood Sequence Estimation for Digital Signaling in the Presence...courses of action which can be pursued to maintain reliable comunications over the selective fading channel are; 1) to reduce the maxinum information...and the complex (I,Q) received signal samples are given by rk =Z c(tj)h(t- tj) + n,(tk) + nQ(tk) (2) 4. where the sumnation is the digital convolution
Gaussian matrix product states for coding in bosonic communication channels
Schäfer, Joachim; Cerf, Nicolas J
2012-01-01
The communication capacity of Gaussian bosonic channels with memory has recently attracted much interest. Here, we investigate a method to prepare the multimode entangled input symbol states for encoding classical information into these channels. In particular, we study the usefulness of a Gaussian matrix product state (GMPS) [G. Adesso and M. Ericsson, Phys. Rev. A 74, 030305 (2006)] as an input symbol state, which can be sequentially generated although it remains heavily entangled for an arbitrary number of modes. We show that the GMPS can achieve more than 99.9% of the Gaussian capacity for Gaussian bosonic memory channels with a Markovian or non-Markovian correlated noise model in a large range of noise correlation strengths. Furthermore, we present a noise class for which the GMPS is the exact optimal input symbol state of the corresponding channel. Since GMPS are ground states of particular quadratic Hamiltonians, our results suggest a possible link between the theory of quantum communication channels a...
A Novel OFDM Channel Estimation Algorithm with ICI Mitigation over Fast Fading Channels
Directory of Open Access Journals (Sweden)
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.
State Energy Data Report, 1991: Consumption estimates
Energy Technology Data Exchange (ETDEWEB)
1993-05-01
The State Energy Data Report (SEDR) provides annual time series estimates of State-level energy consumption by major economic sector. The estimates are developed in the State Energy Data System (SEDS), which is maintained and operated by the Energy Information Administration (EIA). The goal in maintaining SEDS is to create historical time series of energy consumption by State that are defined as consistently as possible over time and across sectors. SEDS exists for two principal reasons: (1) to provide State energy consumption estimates to the Government, policy makers, and the public; and (2) to provide the historical series necessary for EIA`s energy models.
On event based state estimation
Sijs, J.; Lazar, M.
2009-01-01
To reduce the amount of data transfer in networked control systems and wireless sensor networks, measurements are usually taken only when an event occurs, rather than at each synchronous sampling instant. However, this complicates estimation and control problems considerably. The goal of this paper
On event based state estimation
Sijs, J.; Lazar, M.
2009-01-01
To reduce the amount of data transfer in networked control systems and wireless sensor networks, measurements are usually taken only when an event occurs, rather than at each synchronous sampling instant. However, this complicates estimation and control problems considerably. The goal of this paper
Liao, Xiang-Ping; Fang, Mao-Fa; Zhou, Xin
2017-10-01
An efficient method is proposed to enhance the parameter-estimation precision for noisy quantum channels based on measurement reversal from partial-collapse measurement. It is shown that the quantum Fisher information can be distinctly improved for amplitude-damping channel, phase-damping channel and depolarizing channel with partial-collapse measurement. This also means that choosing the appropriate measurement strengths can lead to higher precision of estimation on noisy quantum channels.
Xu, Ru-Gang; Koga, Dennis (Technical Monitor)
2001-01-01
The goal of 'Estimate' is to take advantage of attitude information to produce better pose while staying flexible and robust. Currently there are several instruments that are used for attitude: gyros, inclinometers, and compasses. However, precise and useful attitude information cannot come from one instrument. Integration of rotational rates, from gyro data for example, would result in drift. Therefore, although gyros are accurate in the short-term, accuracy in the long term is unlikely. Using absolute instruments such as compasses and inclinometers can result in an accurate measurement of attitude in the long term. However, in the short term, the physical nature of compasses and inclinometers, and the dynamic nature of a mobile platform result in highly volatile and therefore useless data. The solution then is to use both absolute and relative data. Kalman Filtering is known to be able to combine gyro and compass/inclinometer data to produce stable and accurate attitude information. Since the model of motion is linear and the data comes in as discrete samples, a Discrete Kalman Filter was selected as the core of the new estimator. Therefore, 'Estimate' can be divided into two parts: the Discrete Kalman Filter and the code framework.
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.
Low-Speed ADC Sampling Based High-Resolution Compressive Channel Estimation
Gui, Guan; Kuang, Aihua; Wang, Ling
2012-01-01
Broadband channel is often characterized by a sparse multipath channel where dominant multipath taps are widely separated in time, thereby resulting in a large delay spread. Traditionally, accurate channel estimation is done by sampling received signal by analog-to-digital converter (ADC) at Nyquist rate (high-speed ADC sampling) and then estimate all channel taps with high-resolution. However, traditional linear estimation methods have two mainly disadvantages: 1) demand of the high-speed AD...
Parameter and State Estimator for State Space Models
Directory of Open Access Journals (Sweden)
Ruifeng Ding
2014-01-01
Full Text Available This paper proposes a parameter and state estimator for canonical state space systems from measured input-output data. The key is to solve the system state from the state equation and to substitute it into the output equation, eliminating the state variables, and the resulting equation contains only the system inputs and outputs, and to derive a least squares parameter identification algorithm. Furthermore, the system states are computed from the estimated parameters and the input-output data. Convergence analysis using the martingale convergence theorem indicates that the parameter estimates converge to their true values. Finally, an illustrative example is provided to show that the proposed algorithm is effective.
Parameter and state estimator for state space models.
Ding, Ruifeng; Zhuang, Linfan
2014-01-01
This paper proposes a parameter and state estimator for canonical state space systems from measured input-output data. The key is to solve the system state from the state equation and to substitute it into the output equation, eliminating the state variables, and the resulting equation contains only the system inputs and outputs, and to derive a least squares parameter identification algorithm. Furthermore, the system states are computed from the estimated parameters and the input-output data. Convergence analysis using the martingale convergence theorem indicates that the parameter estimates converge to their true values. Finally, an illustrative example is provided to show that the proposed algorithm is effective.
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.
Minimum decoherence cat-like states in Gaussian noisy channels
Energy Technology Data Exchange (ETDEWEB)
Serafini, A [Dipartimento di Fisica ' E R Caianiello' , Universita di Salerno, INFM UdR Salerno, INFN Sezione Napoli, G C Salerno, Via S Allende, 84081 Baronissi, SA (Italy); De Siena, S [Dipartimento di Fisica ' E R Caianiello' , Universita di Salerno, INFM UdR Salerno, INFN Sezione Napoli, G C Salerno, Via S Allende, 84081 Baronissi, SA (Italy); Illuminati, F [Dipartimento di Fisica ' E R Caianiello' , Universita di Salerno, INFM UdR Salerno, INFN Sezione Napoli, G C Salerno, Via S Allende, 84081 Baronissi, SA (Italy); Paris, M G A [ISIS ' A Sorbelli' , I-41026 Pavullo nel Frignano, MO (Italy)
2004-06-01
We address the evolution of cat-like states in general Gaussian noisy channels, by considering superpositions of coherent and squeezed coherent states coupled to an arbitrarily squeezed bath. The phase space dynamics is solved and decoherence is studied, keeping track of the purity of the evolving state. The influence of the choice of the state and channel parameters on purity is discussed and optimal working regimes that minimize the decoherence rate are determined. In particular, we show that squeezing the bath to protect a non-squeezed cat state against decoherence is equivalent to orthogonally squeezing the initial cat state while letting the bath be phase insensitive.
Minimum decoherence cat-like states in Gaussian noisy channels
Serafini, A; Illuminati, F; Paris, M G A
2004-01-01
We address the evolution of cat-like states in general Gaussian noisy channels, by considering superpositions of coherent and squeezed-coherent states coupled to an arbitrarily squeezed bath. The phase space dynamics is solved and decoherence is studied keeping track of the purity of the evolving state. The influence of the choice of the state and channel parameters on purity is discussed and optimal working regimes that minimize the decoherence rate are determined. In particular, we show that squeezing the bath to protect a non squeezed cat state against decoherence is equivalent to orthogonally squeezing the initial cat state while letting the bath be phase insensitive.
Algorithm of the managing systems state estimation
Directory of Open Access Journals (Sweden)
Skubilin M. D.
2010-02-01
Full Text Available The possibility of an electronic estimation of automatic and automated managing systems state is analyzed. An estimation of a current state (functional readiness of technical equipment and person-operator as integrated system allows to take operatively adequate measures on an exception and-or minimisation of consequences of system’s transition in a supernumerary state. The offered method is universal enough and can be recommended for normalisation of situations on transport, mainly in aircraft.
TRAFFIC CHANNEL SIR ESTIMATION BASED ON REVERSE PILOT CHANNEL IN cdma2000
Institute of Scientific and Technical Information of China (English)
Zhou Hua Yang Dacheng
2004-01-01
Signal-to-Interference Ratio(SIR) is a very important metric of communication link quality. For wireless cellular systems, several control mechanisms, such as power control mechanisms, rate control mechanisms, and allocation of radio resource, are based on SIR estimation.In previous researches, most of researchers concentrated on WCDMA systems, in which pilot symbol is time-multiplexed with data symbol; the method developed in this case is not feasible for cdma2000 systems where pilot symbol is code-multiplexed with data symbol. This paper first develops the SIR estimators based on the reverse pilot channel and then derives the approximate analytic expression for its Mean Squared Error (MSE) function, the accuracy of which is validated through simulation. It is shown that the MSE of the new SIR estimator is significantly smaller than that of other widely used SIR estimators, especially in low SIR case. Finally, the estimate quality of the proposed method is further improved by long-termly averaging the sample interference.
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 The performance of space time trellis coded orthogonal frequency division multiplexing (STTC-OFDM) systems relies on accurate channel state information at the receiver for proper decoding. One method of obtaining channel state information...
Streamflow characteristics related to channel geometry of streams in western United States
Hedman, E.R.; Osterkamp, W.R.
1982-01-01
Assessment of surface-mining and reclamation activities generally requires extensive hydrologic data. Adequate streamflow data from instrumented gaging stations rarely are available, and estimates of surface- water discharge based on rainfall-runoff models, drainage area, and basin characteristics sometimes have proven unreliable. Channel-geometry measurements offer an alternative method of quickly and inexpensively estimating stream-flow characteristics for ungaged streams. The method uses the empirical development of equations to yield a discharge value from channel-geometry and channel-material data. The equations are developed by collecting data at numerous streamflow-gaging sites and statistically relating those data to selected discharge characteristics. Mean annual runoff and flood discharges with selected recurrence intervals can be estimated for perennial, intermittent, and ephemeral streams. The equations were developed from data collected in the western one-half of the conterminous United States. The effect of the channel-material and runoff characteristics are accounted for with the equations.
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.
Free-space optical channel estimation for physical layer security.
Endo, Hiroyuki; Fujiwara, Mikio; Kitamura, Mitsuo; Ito, Toshiyuki; Toyoshima, Morio; Takayama, Yoshihisa; Takenaka, Hideki; Shimizu, Ryosuke; Laurenti, Nicola; Vallone, Giuseppe; Villoresi, Paolo; Aoki, Takao; Sasaki, Masahide
2016-04-18
We present experimental data on message transmission in a free-space optical (FSO) link at an eye-safe wavelength, using a testbed consisting of one sender and two receiver terminals, where the latter two are a legitimate receiver and an eavesdropper. The testbed allows us to emulate a typical scenario of physical-layer (PHY) security such as satellite-to-ground laser communications. We estimate information-theoretic metrics including secrecy rate, secrecy outage probability, and expected code lengths for given secrecy criteria based on observed channel statistics. We then discuss operation principles of secure message transmission under realistic fading conditions, and provide a guideline on a multi-layer security architecture by combining PHY security and upper-layer (algorithmic) security.
Free-space optical channel estimation for physical layer security
Endo, Hiroyuki; Fujiwara, Mikio; Kitamura, Mitsuo; Ito, Toshiyuki; Toyoshima, Morio; Takayama, Yoshihisa; Takenaka, Hideki; Shimizu, Ryosuke; Laurenti, Nicola; Vallone, Giuseppe; Villoresi, Paolo; Aoki, Takao; Sasaki, Masahide
2016-04-01
We present experimental data on message transmission in a free-space optical (FSO) link at an eye-safe wavelength, using a testbed consisting of one sender and two receiver terminals, where the latter two are a legitimate receiver and an eavesdropper. The testbed allows us to emulate a typical scenario of physical-layer (PHY) security such as satellite-to-ground laser communications. We estimate information-theoretic metrics including secrecy rate, secrecy outage probability, and expected code lengths for given secrecy criteria based on observed channel statistics. We then discuss operation principles of secure message transmission under realistic fading conditions, and provide a guideline on a multi-layer security architecture by combining PHY security and upper-layer (algorithmic) security.
Side Channel Passive Quantum Key Distribution with One Uninformative State
Kang, Guo-Dong; Zhou, Qing-Ping; Fang, Mao-Fa
2017-03-01
In most of quantum key distribution schemes, real random number generators are required on both sides for preparation and measurement bases choice. In this paper, via entangled photon pairs, we present a side channel passive quantum key distribution scheme, in which random number generator is unneeded on the receiver side. On the sender Alice side, along with massive of signal photons, small amount of uninformative photons are randomly sent to her partner Bob for eavesdropper-presence testing and error estimation. While on the other side channel, without using random number generator Bob do not actively measure the income signals randomly in two non-orthogonal bases. Instead, he just passively register photon click events, in two settled symmetric (i.e. X) bases, and the raw key(click events) is the probable outcomes of a special quantum measurement module constructed by Alice and Bob. Further, security analysis and formulas of security bounds for this scheme is also investigated under reasonable assumptions. Our work shows that the uninformative state employed in this paper is powerful to fight against eavesdropper Eve.
State and parameter estimation in bio processes
Energy Technology Data Exchange (ETDEWEB)
Maher, M.; Roux, G.; Dahhou, B. [Centre National de la Recherche Scientifique (CNRS), 31 - Toulouse (France)]|[Institut National des Sciences Appliquees (INSA), 31 - Toulouse (France)
1994-12-31
A major difficulty in monitoring and control of bio-processes is the lack of reliable and simple sensors for following the evolution of the main state variables and parameters such as biomass, substrate, product, growth rate, etc... In this article, an adaptive estimation algorithm is proposed to recover the state and parameters in bio-processes. This estimator utilizes the physical process model and the reference model approach. Experimentations concerning estimation of biomass and product concentrations and specific growth rate, during batch, fed-batch and continuous fermentation processes are presented. The results show the performance of this adaptive estimation approach. (authors) 12 refs.
Outlier Rejecting Multirate Model for State Estimation
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
Wavelet transform was introduced to detect and eliminate outliers in time-frequency domain. The outlier rejection and multirate information extraction were initially incorporated by wavelet transform, a new outlier rejecting multirate model for state estimation was proposed. The model is applied to state estimation with interacting multiple model, as the outlier is eliminated and more reasonable multirate information is extracted, the estimation accuracy is greatly enhanced. The simulation results prove that the new model is robust to outliers and the estimation performance is significantly improved.
Absence of quantum states corresponding to unstable classical channels
DEFF Research Database (Denmark)
Herbst, Ira; Skibsted, Erik
2008-01-01
We develop a general theory of absence of quantum states corresponding to unstable classical scattering channels. We treat in detail Hamiltonians arising from symbols of degree zero in x and outline a generalization in an Appendix....
State energy data report 1996: Consumption estimates
Energy Technology Data Exchange (ETDEWEB)
NONE
1999-02-01
The State Energy Data Report (SEDR) provides annual time series estimates of State-level energy consumption by major economic sectors. The estimates are developed in the Combined State Energy Data System (CSEDS), which is maintained and operated by the Energy Information Administration (EIA). The goal in maintaining CSEDS is to create historical time series of energy consumption by State that are defined as consistently as possible over time and across sectors. CSEDS exists for two principal reasons: (1) to provide State energy consumption estimates to Members of Congress, Federal and State agencies, and the general public and (2) to provide the historical series necessary for EIA`s energy models. To the degree possible, energy consumption has been assigned to five sectors: residential, commercial, industrial, transportation, and electric utility sectors. Fuels covered are coal, natural gas, petroleum, nuclear electric power, hydroelectric power, biomass, and other, defined as electric power generated from geothermal, wind, photovoltaic, and solar thermal energy. 322 tabs.
Introduction to quantum-state estimation
Teo, Yong Siah
2016-01-01
Quantum-state estimation is an important field in quantum information theory that deals with the characterization of states of affairs for quantum sources. This book begins with background formalism in estimation theory to establish the necessary prerequisites. This basic understanding allows us to explore popular likelihood- and entropy-related estimation schemes that are suitable for an introductory survey on the subject. Discussions on practical aspects of quantum-state estimation ensue, with emphasis on the evaluation of tomographic performances for estimation schemes, experimental realizations of quantum measurements and detection of single-mode multi-photon sources. Finally, the concepts of phase-space distribution functions, which compatibly describe these multi-photon sources, are introduced to bridge the gap between discrete and continuous quantum degrees of freedom. This book is intended to serve as an instructive and self-contained medium for advanced undergraduate and postgraduate students to gra...
Estimating state-contingent production functions
DEFF Research Database (Denmark)
Rasmussen, Svend; Karantininis, Kostas
The paper reviews the empirical problem of estimating state-contingent production functions. The major problem is that states of nature may not be registered and/or that the number of observation per state is low. Monte Carlo simulation is used to generate an artificial, uncertain production...... environment based on Cobb Douglas production functions with state-contingent parameters. The pa-rameters are subsequently estimated based on different sizes of samples using Generalized Least Squares and Generalized Maximum Entropy and the results are compared. It is concluded that Maximum Entropy may...
Two-state filtering for joint state-parameter estimation
Santitissadeekorn, Naratip
2014-01-01
This paper presents an approach for simultaneous estimation of the state and unknown parameters in a sequential data assimilation framework. The state augmentation technique, in which the state vector is augmented by the model parameters, has been investigated in many previous studies and some success with this technique has been reported in the case where model parameters are additive. However, many geophysical or climate models contains non-additive parameters such as those arising from physical parametrization of sub-grid scale processes, in which case the state augmentation technique may become ineffective since its inference about parameters from partially observed states based on the cross covariance between states and parameters is inadequate if states and parameters are not linearly correlated. In this paper, we propose a two-stages filtering technique that runs particle filtering (PF) to estimate parameters while updating the state estimate using Ensemble Kalman filter (ENKF; these two "sub-filters" ...
State estimation for wave energy converters
Energy Technology Data Exchange (ETDEWEB)
Bacelli, Giorgio; Coe, Ryan Geoffrey
2017-04-01
This report gives a brief discussion and examples on the topic of state estimation for wave energy converters (WECs). These methods are intended for use to enable real-time closed loop control of WECs.
New Concepts for Shipboard Sea State Estimation
DEFF Research Database (Denmark)
Nielsen, Ulrik D.; Bjerregård, Mikkel; Galeazzi, Roberto
2015-01-01
The wave buoy analogy is a tested means for shipboard sea state estimation. Basically, the estimation principle resembles that of a traditional wave rider buoy which relies, fundamentally, on transfer functions used to relate measured wave-induced responses and the unknown wave excitation. This p...
State estimation for random closed sets
Lieshout, van M.N.M.; Stein, Alfred; Allard, Denis
2015-01-01
State estimation entails the estimation of an unobserved random closed set from (partial) observation of an associated random set. Examples include edge effect correction, cluster detection, filtering and prediction. We focus on inference for random sets based on points sampled on its boundary. Such
State Estimation for the VASIMR Plasma Engine
2008-01-01
This paper presents work on the application of virtual metrology techniques to the VAriable Specific Impulse Magnetoplasma Rocket (VASMIR) engine. The work concentrates on the estimation of internal temperatures of the rocket using state space models and Optical Emission Spectroscopy (OES). These estimations are useful as direct thermal measurements will not be available in the final system design.
Perfect Entanglement Teleportation via Two Parallel W State Channels
Institute of Scientific and Technical Information of China (English)
WANG Mei-Yu; YAN Feng-Li
2011-01-01
We present a scheme for perfectly teleporting a two-qubit entangled state via two parallel W state channels. The scheme consists of a positive operator valued measurement (POVM), classical communication and the corresponding local unitary operation. How to realize the POVM using unitary operation and projective measurement is explicitly designed.%@@ We present a scheme for perfectly teleporting a two-qubit entangled state via two parallel W state channels.The scheme consists of a positive operator valued measurement (POVM), classical communication and the corre- sponding local unitary operation.How to realize the POVM using unitary operation and projective measurement is explicitly designed.
Permeation mechanism of a two-state potassium channel
Institute of Scientific and Technical Information of China (English)
WANG Xiangqun; ZHAO Tongjun; SONG Yang; ZHAN Yong
2007-01-01
A two-state hopping model was proposed to study the permeation of ion channel.The Nemst equation in equilibrium and the Michaelis-Menten relation in steady state were derived from the two-state kinetic model.The currentvoltage relationship obtained in the symmetrical solutions case was linear when the applied potential was less than 100 mV,which met Ohm's law.The conductance-concentration relationship exhibited the saturation property.Moreover,the characteristic time reaching the steady state of the KcsA channel was also discussed.
Estimation of MIMO channel capacity from phase-noise impaired measurements
DEFF Research Database (Denmark)
Pedersen, Troels; Yin, Xuefeng; Fleury, Bernard Henri
2008-01-01
phase noise samples affecting measurement samples collected with real TDMMIMO channel sounders are correlated. In this contribution a capacity estimator that accounts for the phase noise correlation is proposed. The estimator is based on a linear minimum mean square error estimate of the MIMO channel...
Directory of Open Access Journals (Sweden)
V. K. Hohlov
2016-01-01
Full Text Available The article presents a statement of technique to research performances of multi-channel combo standalone information systems with positional analyzers of the signal states at the channel outputs. In most cases, in considered multi-channel systems there has been impossible to coincide in time the random moments of signals coming from the objects through various channels in all ways of encounter environment and conditions of practical application. The analyzer makes decision on the signal using the discrete operations on the quantized signals of the certain duration from the channel outputs. The analyzer performance is described by a set of Boolean algebra functions defined for all possible states of the signals at the outputs of the channels, and in the general case is specified in a perfect disjunctive normal form. To determine the validity or falsity of functions of the algebra of logics, which are calculated statements concerning the available or unavailable useful signal at the system input, on the authority of the Poretsky’s theorem and the theory of coincidence in time of the random pulse flow of the channels response because of uncorrelated and correlated noise, are obtained dependences to calculate the probabilities of false alarms and omissions of the signals in discrete combined systems. It is shown that the flows of false alarms because of noise at the channel outputs in the system are Poisson streams. On the basis of the ordinary Poisson flows the paper justifies the relationships for calculating the false alarms of the system with uncorrelated and correlated noise in the channels. The paper also justifies the relationships for performance of multichannel combined systems with positional analyzers of the channels states. Based on the obtained relationships was calculated the average coincidence frequency of the extended pulses of the channel response in a dualchannel system, depending on the noise cross-correlation coefficient with
On the capacity of Rician fading channels with full channel state information at low SNR
Rezki, Zouheir
2012-06-01
The capacity of flat Rayleigh fading channels with full channel state information (CSI) at the transmitter and at the receiver at asymptotically low SNR has been recently shown to scale essentially as SNR log (1/SNR). In this paper, we investigate the Rician fading channel capacity with full CSI, and show that the capacity of this channel scales essentially as 1/1+K SNR log (1 /SNR), where K is the Rician factor. This characterization includes perfect CSI at both the transmitter and the receiver or noisy CSI at the transmitter and perfect CSI at the receiver. We also show that one-bit CSI at the transmitter is enough to achieve this asymptotic capacity using an On-Off power control scheme. Our framework may be seen as a generalization of previous works as it captures the Rayleigh fading channel as a special case by letting K goes to zero. © 2012 IEEE.
Institute of Scientific and Technical Information of China (English)
CHEN Peng; WU Wei-ling
2005-01-01
The impact of imperfect channel estimation on the forward-link performance in CDMA distributed antenna systems in multi-path fading environment is investigated.A detailed analytical model based on a hybrid signal combining method is presented and exact outage probability expression is derived.The investigation shows that the effect of imperfect channel estimates varies with system load.Furthermore,if simulcasting is employed,macro-diversity can decrease the sensitivity of forward-link to channel estimation errors and increase the forward-link outage performance,which is contrary to the conclusion drawn based on the ideal channel estimation assumption.
Minimum Mean-Square Error Single-Channel Signal Estimation
DEFF Research Database (Denmark)
Beierholm, Thomas
2008-01-01
are expressed and in the way the estimator is approximated. The starting point of the first method is prior probability density functions for both signal and noise and it is assumed that their Laplace transforms (moment generating functions) are available. The corresponding posterior mean integral that defines...... 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...... particle filtering using the reparameterized speech model because it is relative straightforward to exploit prior information about formant features. A modified MMSE estimator is introduced and performance of the particle filtering algorithm is compared to a state of the art hearing aid noise reduction...
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.
Millimeter Wave MIMO Channel Estimation Using Overlapped Beam Patterns and Rate Adaptation
Kokshoorn, Matthew; Chen, He; Wang, Peng; Li, Yonghui; Vucetic, Branka
2017-02-01
This paper is concerned with the channel estimation problem in Millimeter wave (mmWave) wireless systems with large antenna arrays. By exploiting the inherent sparse nature of the mmWave channel, we first propose a fast channel estimation (FCE) algorithm based on a novel overlapped beam pattern design, which can increase the amount of information carried by each channel measurement and thus reduce the required channel estimation time compared to the existing non-overlapped designs. We develop a maximum likelihood (ML) estimator to optimally extract the path information from the channel measurements. Then, we propose a novel rate-adaptive channel estimation (RACE) algorithm, which can dynamically adjust the number of channel measurements based on the expected probability of estimation error (PEE). The performance of both proposed algorithms is analyzed. For the FCE algorithm, an approximate closed-form expression for the PEE is derived. For the RACE algorithm, a lower bound for the minimum signal energy-to-noise ratio required for a given number of channel measurements is developed based on the Shannon-Hartley theorem. Simulation results show that the FCE algorithm significantly reduces the number of channel estimation measurements compared to the existing algorithms using non-overlapped beam patterns. By adopting the RACE algorithm, we can achieve up to a 6dB gain in signal energy-to-noise ratio for the same PEE compared to the existing algorithms.
Irreducible Decompositions and Stationary States of Quantum Channels
Carbone, Raffaella; Pautrat, Yan
2016-06-01
For a quantum channel (completely positive, trace-preserving map), we prove a generalization to the infinite-dimensional case of a result by Baumgartner and Narnhofer [3]: this result is, in a probabilistic language, a decomposition of a general quantum channel into its irreducible recurrent components. More precisely, we prove that the positive recurrent subspace (i.e. the space supporting the invariant states) can be decomposed as the direct sum of supports of extremal invariant states; this decomposition is not unique, in general, but we can determine all the possible decompositions. This allows us to describe the full structure of invariant states.
Estimating the Energy State of Liquids
Directory of Open Access Journals (Sweden)
Lianwen Wang
2014-12-01
Full Text Available In contrast to the gaseous and the solid states, the liquid state does not have a simple model that could be developed into a quantitative theory. A central issue in the understanding of liquids is to estimate the energy state of liquids. Here, on the basis of our recent studies on crystal melting, we show that the energy sate of liquids may be reasonably approximated by the energy and volume of a vacancy. Consequently, estimation of the liquid state energy is significantly simplified comparing with previous methods that inevitably invoke many-body interactions. Accordingly, a possible equation for the state for liquids is proposed. On this basis, it seems that a simple model for liquids is in sight.
Sub-Second Parallel State Estimation
Energy Technology Data Exchange (ETDEWEB)
Chen, Yousu [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Rice, Mark J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Glaesemann, Kurt R. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Wang, Shaobu [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Huang, Zhenyu [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
2014-10-31
This report describes the performance of Pacific Northwest National Laboratory (PNNL) sub-second parallel state estimation (PSE) tool using the utility data from the Bonneville Power Administrative (BPA) and discusses the benefits of the fast computational speed for power system applications. The test data were provided by BPA. They are two-days’ worth of hourly snapshots that include power system data and measurement sets in a commercial tool format. These data are extracted out from the commercial tool box and fed into the PSE tool. With the help of advanced solvers, the PSE tool is able to solve each BPA hourly state estimation problem within one second, which is more than 10 times faster than today’s commercial tool. This improved computational performance can help increase the reliability value of state estimation in many aspects: (1) the shorter the time required for execution of state estimation, the more time remains for operators to take appropriate actions, and/or to apply automatic or manual corrective control actions. This increases the chances of arresting or mitigating the impact of cascading failures; (2) the SE can be executed multiple times within time allowance. Therefore, the robustness of SE can be enhanced by repeating the execution of the SE with adaptive adjustments, including removing bad data and/or adjusting different initial conditions to compute a better estimate within the same time as a traditional state estimator’s single estimate. There are other benefits with the sub-second SE, such as that the PSE results can potentially be used in local and/or wide-area automatic corrective control actions that are currently dependent on raw measurements to minimize the impact of bad measurements, and provides opportunities to enhance the power grid reliability and efficiency. PSE also can enable other advanced tools that rely on SE outputs and could be used to further improve operators’ actions and automated controls to mitigate effects
Distributed Robust Power System State Estimation
Kekatos, Vassilis
2012-01-01
Deregulation of energy markets, penetration of renewables, advanced metering capabilities, and the urge for situational awareness, all call for system-wide power system state estimation (PSSE). Implementing a centralized estimator though is practically infeasible due to the complexity scale of an interconnection, the communication bottleneck in real-time monitoring, regional disclosure policies, and reliability issues. In this context, distributed PSSE methods are treated here under a unified and systematic framework. A novel algorithm is developed based on the alternating direction method of multipliers. It leverages existing PSSE solvers, respects privacy policies, exhibits low communication load, and its convergence to the centralized estimates is guaranteed even in the absence of local observability. Beyond the conventional least-squares based PSSE, the decentralized framework accommodates a robust state estimator. By exploiting interesting links to the compressive sampling advances, the latter jointly es...
On state estimation in electric drives
Energy Technology Data Exchange (ETDEWEB)
Leon, A.E., E-mail: aleon@ymail.co [Instituto de Investigaciones en Ingenieria Electrica (IIIE) ' Alfredo Desages' (UNS-CONICET), Departamento de Ingenieria Electrica y de Computadoras, Universidad Nacional del Sur - UNS, 1253 Alem Avenue, P.O. 8000, Bahia Blanca (Argentina); Solsona, J.A., E-mail: jsolsona@uns.edu.a [Instituto de Investigaciones en Ingenieria Electrica (IIIE) ' Alfredo Desages' (UNS-CONICET), Departamento de Ingenieria Electrica y de Computadoras, Universidad Nacional del Sur - UNS, 1253 Alem Avenue, P.O. 8000, Bahia Blanca (Argentina)
2010-03-15
This paper deals with state estimation in electric drives. On one hand a nonlinear observer is designed, whereas on the other hand the speed state is estimated by using the dirty derivative from the position measured. The dirty derivative is an approximate version of the perfect derivative which introduces an estimation error few times analyzed in drive applications. For this reason, our proposal in this work consists in illustrating several aspects on the performance of the dirty derivator in presence of both model uncertainties and noisy measurements. To this end, a case study is introduced. The case study considers rotor speed estimation in a permanent magnet stepper motor, by assuming that rotor position and electrical variables are measured. In addition, this paper presents comments about the connection between dirty derivators and observers, and advantages and disadvantages of both techniques are also remarked.
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.
DEFF Research Database (Denmark)
Shutin, Dmitriy; Fleury, Bernard Henri
2011-01-01
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...... scattering, calibration and discretization errors, allowing for a robust extraction of the relevant multipath components. The performance of the sparse VB-SAGE algorithm and its advantages over conventional channel estimation methods are demonstrated in synthetic single-input-multiple-output (SIMO) time......-invariant channels. The algorithm is also applied to real measurement data in a multiple-input-multiple-output (MIMO) time-invariant context....
Mass and heat balances in the Santa Barbara Channel: estimation, description and forcing
Auad, Guillermo; Hendershott, Myrl C.; Winant, Clinton D.
1999-01-01
Current meter, temperature and wind observations from the 1984 MMS experiment are used to estimate the mass and heat budgets in the Santa Barbara Channel. The mass transports estimated at the western, eastern and southern boundaries of the channel are characterized by fluctuations whose energy is concentrated around three different periods: 5, 14 and 2.8 days respectively. These three transports fluctuate along with the dominant EOF modes obtained at those 3 entrances respectively. The mean transport passing through the channel from east to west is about 0.28 Sv. There are two frequency bands where winds and mass transports are coherent: 2.5-3.0 and 4.7-5.2 day bands. Winds on the northern shelf lead the transports in both bands by about 1.0 day. At the western half of the channel there is a recirculating (counterclockwise) mean transport of about 0.30 Sv. The time dependent part of the recirculating transport is coherent with the wind in the 4.7-5.2 day band where it also shows an absolute maximum of variance. The recirculating transport lags the local downwelling-favorable winds by about 1.5 day and seems to be the channel response to wind relaxations with respect to its most persistent upwelling-favorable state. The main mean balance in the channel-integrated heat equation is between the heat transport passing through the western mouth, which cools off the channel, and the heat transport caused by the mass transport (the transport heat flux), which warms up the channel. This latter transport results from the advection of the temperature difference between the channel boundaries (mainly east and west) by the mass transport. There are no two terms that dominate the heat equation for the time dependent heat transports, but it can be simplified by balancing the along channel heat divergence (heat transport passing through the mouth plus transport heat flux), the vertical heat flux and the local change of heat. A clear thermal-wind balance at the eastern and western
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.
Error estimation in the direct state tomography
Sainz, I.; Klimov, A. B.
2016-10-01
We show that reformulating the Direct State Tomography (DST) protocol in terms of projections into a set of non-orthogonal bases one can perform an accuracy analysis of DST in a similar way as in the standard projection-based reconstruction schemes, i.e., in terms of the Hilbert-Schmidt distance between estimated and true states. This allows us to determine the estimation error for any measurement strength, including the weak measurement case, and to obtain an explicit analytic form for the average minimum square errors.
Du, Jie; Deng, Honggui; Qian, Xuewen; Zhang, Chaoyang
2016-11-01
In order to mitigate bandwidth attenuation of diffusion link visible light communication systems caused by multipath effects, we present an optical orthogonal frequency division multiplexing channel estimation scheme based on compressed sensing (CS) and estimation of signal parameters via rotational invariance techniques (ESPRIT). First, we derived a parametric channel model. Then, we used ESPRIT to obtain multipath channel parameters. After that, we built a dynamic over-complete dictionary that can be used in CS processing. Finally, we reconstructed the channel response by using a basis pursuit denoising algorithm to equalize the received signal in frequency domain. Compared with traditional schemes, the proposed scheme can improve channel estimation accuracy without increasing dictionary size. A set of computer simulations demonstrated the effectiveness of the proposed scheme.
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.
Design the MC-CDMA System with LS-PSO Channel Estimation Based FPGA
Directory of Open Access Journals (Sweden)
Ali Kareem Nahar
2015-07-01
Full Text Available The aim of study, providing the best BER performance in channel estimation for Multi Carrier-Code Division Multiple Access (MC-CDMA system and flexible manner, FPGA design, is using a combination of the SIMULINK family of products, XILINX system generators, XILINX and MATLAB which is suitable for rapid design and verification. In MC-CDMA system, channel estimation is a very important method to work around the influence of channel fading’s which jamming pilot symbols and caused BER degradation. That the market for wireless communications infrastructure matures equipment vendors are under increasing pressure to provide low cost solutions for operators and reduce wireless technology complexity. In this study new MC-CDMA channel estimate schema suggested that was based on a combination of Local Search and Particle Swarm Optimization. The proposed channel estimator tested under channel fast fading for different situations. In particular, the transmitter design focus on the 64-QAM system and spreading gold code.
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.
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.
On the secrecy capacity of the broadcast wiretap channel with imperfect channel state information
Hyadi, Amal
2014-12-01
In this paper, we consider secure broadcasting over fast fading channels. Assuming imperfect main channel state information (CSI) at the transmitter, we first provide an upper and a lower bounds on the ergodic secrecy capacity when a common message is broadcasted to multiple legitimate receivers in the presence of one eavesdropper. For this case, we show that the secrecy rate is limited by the legitimate receiver having, on average, the worst main channel link. Then, we present an expression for the achievable secrecy sum-rate when each legitimate receiver is interested in an independent message. The special cases of high SNR, perfect and no-main CSI are also analyzed. Numerical results are presented to illustrate the obtained results for the case of independent but not necessarily identically distributed Rayleigh fading channels.
State energy data report 1992: Consumption estimates
Energy Technology Data Exchange (ETDEWEB)
1994-05-01
This is a report of energy consumption by state for the years 1960 to 1992. The report contains summaries of energy consumption for the US and by state, consumption by source, comparisons to other energy use reports, consumption by energy use sector, and describes the estimation methodologies used in the preparation of the report. Some years are not listed specifically although they are included in the summary of data.
The investigation on two-dimensional pilot-symbol-aided channel estimation method for OFDM system
Institute of Scientific and Technical Information of China (English)
Sun Juying; Zhang Yanhua
2008-01-01
Channel estimation for orthogonal frequency division multiplexing (OFDM) system has attracted widespread attention. In this paper, a novel efficient two-dimensional (2-D) channel estimation algorithm based on fast Fourier transform (FFT) is proposed for a time-variant, frequency-selective wideband wireless channel. Both theoretical analysis and simulation results are addressed in the paper. The simulation results prove that the proposed algorithm has simpler implementation, better performance and wider application than other traditional decision-directed algorithms.
Bayes-Optimal Joint Channel-and-Data Estimation for Massive MIMO With Low-Precision ADCs
Wen, Chao-Kai; Wang, Chang-Jen; Jin, Shi; Wong, Kai-Kit; Ting, Pangan
2016-05-01
This paper considers a multiple-input multiple-output (MIMO) receiver with very low-precision analog-to-digital convertors (ADCs) with the goal of developing massive MIMO antenna systems that require minimal cost and power. Previous studies demonstrated that the training duration should be {\\em relatively long} to obtain acceptable channel state information. To address this requirement, we adopt a joint channel-and-data (JCD) estimation method based on Bayes-optimal inference. This method yields minimal mean square errors with respect to the channels and payload data. We develop a Bayes-optimal JCD estimator using a recent technique based on approximate message passing. We then present an analytical framework to study the theoretical performance of the estimator in the large-system limit. Simulation results confirm our analytical results, which allow the efficient evaluation of the performance of quantized massive MIMO systems and provide insights into effective system design.
A Full Performance Analysis of Channel Estimation Methods for Time Varying OFDM Systems
Aida, Zaier; 10.5121/ijmnct.2011.1201
2012-01-01
In this paper, we have evaluated various methods of time-frequency-selective fading channels estimation in OFDM system and some of them improved under time varying conditions. So, these different techniques will be studied through different algorithms and for different schemes of modulations (16 QAM, BPSK, QPSK, ...). Channel estimation gathers different schemes and algorithms, some of them are dedicated for slowly time varying (such as block type arrangement insertion, Bayesian Cramer-Rao Bound, Kalman estimator, Subspace estimator, ...) whereas the others concern highly time varying channels (comb type insertion, ...). There are others methods that are just suitable for stationary channels like blind or semi blind estimators. For this aim, diverse algorithms were used for these schemes such as Least Squares estimator LS, Least Minimum Squares LMS, Minimum Mean-Square-Error MMSE, Linear Minimum Mean-Square-Error LMMSE, Maximum Likelihood ML, ... to refine estimators shown previously.
Simulation and Comparison of Channel Estimation Based on Block-type Pilot Frequency in OFDM System
Di, Weiguo; Li, Zhendong; Yang, Ming; Zhao, Xiaobo
Orthogonal Frequency Division Multiplexing (OFDM) splits a high-speed data stream into a number of lower-speed data streams that are transmitted simultaneously over a number of subcarriers. The capability of resistance of intersymbol interference and bandwidth efficiency are improved, and multipath fading is effectively combated. In order to improve communication efficiency and communication quality, it is necessary to make a dynamic estimation of the current characteristics of the channel. In OFDM system, the technology of channel estimation based on the pilot frequency of block-type distribution is that pilot signal is inserted at regular intervals of time on the transmitting terminal, and on the receiving terminal extract pilot signal from the received data stream, and according to that the channel characteristics are estimated at the period of time. Three common methods of channel estimation based on pilot frequency: MMSE estimation, LS estimation and SVD estimation are discussed with comparison in OFDM system. Through the simulation of matlab, three channel estimation methods and their characteristics are analyzed and compared. The results show that the performance of MMSE estimation is far better than that of the LS estimation, but MMSE estimation has high computational complexity. The performance and computational complexity of SVD estimation are ranged between that of the MMSE estimation and LS estimation.
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.
State estimation for integrated vehicle dynamics control
Zuurbier, J.; Bremmer, P.
2002-01-01
This paper discusses a vehicle controller and a state estimator that was implemented and tested in a vehicle equipped with a combined braking and chassis control system to improve handling. The vehicle dynamics controller consists of a feed forward body roll compensation and a feedback stability con
State Estimation for the Automotive SCR Process
DEFF Research Database (Denmark)
Zhou, Guofeng; Huusom, Jakob Kjøbsted; Jørgensen, John Bagterp
2012-01-01
Selective catalytic reduction (SCR) of NOx is a widely applied diesel engine exhaust gas aftertreatment technology. For advanced SCR process control, like model predictive control, full state information of the process is required. The ammonia coverage ratio inside the catalyst is difficult...... present for SCR in engine applications, we recommend to estimating the ammonia coverage using the extended Kalman filter....
Equations of States in Singular Statistical Estimation
Watanabe, Sumio
2007-01-01
Learning machines which have hierarchical structures or hidden variables are singular statistical models because they are nonidentifiable and their Fisher information matrices are singular. In singular statistical models, neither the Bayes a posteriori distribution converges to the normal distribution nor the maximum likelihood estimator satisfies asymptotic normality. This is the main reason why it has been difficult to predict their generalization performances from trained states. In this paper, we study four errors, (1) Bayes generalization error, (2) Bayes training error, (3) Gibbs generalization error, and (4) Gibbs training error, and prove that there are mathematical relations among these errors. The formulas proved in this paper are equations of states in statistical estimation because they hold for any true distribution, any parametric model, and any a priori distribution. Also we show that Bayes and Gibbs generalization errors are estimated by Bayes and Gibbs training errors, and propose widely appl...
Motorcycle state estimation for lateral dynamics
Teerhuis, A. P.; Jansen, S. T. H.
2012-08-01
The motorcycle lean (or roll) angle development is one of the main characteristics of motorcycle lateral dynamics. Control of motorcycle motions requires an accurate assessment of this quantity and for safety applications also the risk of sliding needs to be considered. Direct measurement of the roll angle and tyre slip is not available; therefore, a method of model-based estimation is developed to estimate the state of a motorcycle. This paper investigates the feasibility of such a motorcycle state estimator (MCSE). A simplified analytic model of a motorcycle is developed by comparison to an extended multi-body model of the motorcycle, designed in Matlab/SimMechanics. The analytic model is used inside an extended Kalman filter. Experimental results of an instrumented Yamaha FJR1300 motorcycle show that the MCSE is a feasible concept for obtaining signals related to the lateral dynamics of the motorcycle.
On the Capacity of Compound State-Dependent Channels with States Known at the Transmitter
Piantanida, Pablo
2010-01-01
This paper investigates the capacity of compound state-dependent channels with non-causal state information available at only the transmitter. A new lower bound on the capacity of this class of channels is derived. This bound is shown to be tight for the special case of compound channels with stochastic degraded components, yielding the full characterization of the capacity. Specific results are derived for the compound Gaussian Dirty-Paper (GDP) channel. This model consists of an additive white Gaussian noise (AWGN) channel corrupted by an additive Gaussian interfering signal, known at the transmitter only, where the input and the state signals are affected by fading coefficients whose realizations are unknown at the transmitter. Our bounds are shown to be tight for specific cases. Applications of these results arise in a variety of wireless scenarios as multicast channels, cognitive radio and problems with interference cancellation.
Duan, Hanjun; Wu, Haifeng; Zeng, Yu; Chen, Yuebin
2016-03-26
In a passive ultra-high frequency (UHF) radio-frequency identification (RFID) system, tag collision is generally resolved on a medium access control (MAC) layer. However, some of collided tag signals could be recovered on a physical (PHY) layer and, thus, enhance the identification efficiency of the RFID system. For the recovery on the PHY layer, channel estimation is a critical issue. Good channel estimation will help to recover the collided signals. Existing channel estimates work well for two collided tags. When the number of collided tags is beyond two, however, the existing estimates have more estimation errors. In this paper, we propose a novel channel estimate for the UHF RFID system. It adopts an orthogonal matrix based on the information of preambles which is known for a reader and applies a minimum-mean-square-error (MMSE) criterion to estimate channels. From the estimated channel, we could accurately separate the collided signals and recover them. By means of numerical results, we show that the proposed estimate has lower estimation errors and higher separation efficiency than the existing estimates.
Study on Channel Estimate and Joint Detection in 3G Network
Directory of Open Access Journals (Sweden)
Yanchun Shen
2012-04-01
Full Text Available In order to study the contribution of the channel estimation and joint measuring technology on the third generation mobile communications (3G, the channel estimation and joint detection model of the 3G system has been installed to analyze the channel estimation approaches grounded on emergency setups and training sequence. Pulse shaping filtering has been conducted by operations such as QPSK baseband modulation and Spread Spectrum on the User Data Source; then to channel estimate and joint measure the data received from base station via the Additive White Gaussian Noise channel. In line with the simulation results, with the increase of signal to noise ratio，the impulse response graph of the signal via the Steiner Estimator channel levels with that via the noise-free channel. Zero Forcing Block Linear Equalizer (ZF-BLE has a good effect on eliminating the multipath interference and the inter-symbol interference in the system, which prove the good effects on the 3G system of using both the channel estimation technology of the Steiner Estimator and the joint measuring technology of the ZF-BLE, which is of good application prospects.
Automatic Estimation of the Dynamics of Channel Conductance Using a Recurrent Neural Network
Directory of Open Access Journals (Sweden)
Masaaki Takahashi
2009-01-01
Full Text Available In order to simulate neuronal electrical activities, we must estimate the dynamics of channel conductances from physiological experimental data. However, this approach requires the formulation of differential equations that express the time course of channel conductance. On the other hand, if the dynamics are automatically estimated, neuronal activities can be easily simulated. By using a recurrent neural network (RNN, it is possible to estimate the dynamics of channel conductances without formulating the differential equations. In the present study, we estimated the dynamics of the Na+ and K+ conductances of a squid giant axon using two different fully connected RNNs and were able to reproduce various neuronal activities of the axon. The reproduced activities were an action potential, a threshold, a refractory phenomenon, a rebound action potential, and periodic action potentials with a constant stimulation. RNNs can be trained using channels other than the Na+ and K+ channels. Therefore, using our RNN estimation method, the dynamics of channel conductance can be automatically estimated and the neuronal activities can be simulated using the channel RNNs. An RNN can be a useful tool to estimate the dynamics of the channel conductance of a neuron, and by using the method presented here, it is possible to simulate neuronal activities more easily than by using the previous methods.
Rezki, Zouheir
2013-06-01
We study the throughput capacity region of the Gaussian multiaccess (MAC) fading channel with perfect channel state information (CSI) at the receiver (CSI-R) and at the transmitters (CSI-T), at low power regime. We show that it has a multidimensional rectangle structure and thus is simply characterized by single user capacity points. More specifically, we show that at low power regime, the boundary surface of the capacity region shrinks to a single point corresponding to the sum rate maximizer and that the coordinates of this point coincide with single user capacity bounds. Inspired from this result, we propose an on-off scheme, compute its achievable rate, and provide a necessary condition on the fading channels under which this scheme achieves single user capacity bounds of the MAC channel at asymptotically low power regime. We argue that this necessary condition characterizes a class of fading that encompasses all known wireless channels, where the capacity region of the MAC channel has a simple expression in terms of users\\' average power constraints only. © 2013 IEEE.
Improving MIMO-OFDM decision-directed channel estimation by utilizing error-correcting codes
Directory of Open Access Journals (Sweden)
P. Beinschob
2009-05-01
Full Text Available In this paper a decision-directed Multiple-Input Multiple-Output (MIMO channel tracking algorithm is enhanced to raise the channel estimate accuracy. While DDCE is prone to error propagation the enhancement employs channel decoding in the tracking process. Therefore, a quantized block of symbols is checked on consistency via the channel decoder, possibly corrected and then used. This yields a more robust tracking of the channel in terms of bit error rate and improves the channel estimate under certain conditions.
Equalization is performed to prove the feasibility of the obtained channel estimate. Therefore a combined signal consisting of data and pilot symbols is sent. Adaptive filters are applied to exploit correlations in time, frequency and spatial domain. By using good error-correcting coding schemes like Turbo Codes or Low Density Parity Check (LDPC codes, adequate channel estimates can be acquired even at low signal to noise ratios (SNR. The proposed algorithm among two others is applied for channel estimation and equalization and results are compared.
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
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.
Estimated Water Flows in 2005: United States
Energy Technology Data Exchange (ETDEWEB)
Smith, C A; Belles, R D; Simon, A J
2011-03-16
Flow charts depicting water use in the United States have been constructed from publicly available data and estimates of water use patterns. Approximately 410,500 million gallons per day of water are managed throughout the United States for use in farming, power production, residential, commercial, and industrial applications. Water is obtained from four major resource classes: fresh surface-water, saline (ocean) surface-water, fresh groundwater and saline (brackish) groundwater. Water that is not consumed or evaporated during its use is returned to surface bodies of water. The flow patterns are represented in a compact 'visual atlas' of 52 state-level (all 50 states in addition to Puerto Rico and the Virgin Islands) and one national water flow chart representing a comprehensive systems view of national water resources, use, and disposition.
An Empirical State Error Covariance Matrix for Batch State Estimation
Frisbee, Joseph H., Jr.
2011-01-01
State estimation techniques serve effectively to provide mean state estimates. However, the state error covariance matrices provided as part of these techniques suffer from some degree of lack of confidence in their ability to adequately describe the uncertainty in the estimated states. A specific problem with the traditional form of state error covariance matrices is that they represent only a mapping of the assumed observation error characteristics into the state space. Any errors that arise from other sources (environment modeling, precision, etc.) are not directly represented in a traditional, theoretical state error covariance matrix. Consider that an actual observation contains only measurement error and that an estimated observation contains all other errors, known and unknown. It then follows that a measurement residual (the difference between expected and observed measurements) contains all errors for that measurement. Therefore, a direct and appropriate inclusion of the actual measurement residuals in the state error covariance matrix will result in an empirical state error covariance matrix. This empirical state error covariance matrix will fully account for the error in the state estimate. By way of a literal reinterpretation of the equations involved in the weighted least squares estimation algorithm, it is possible to arrive at an appropriate, and formally correct, empirical state error covariance matrix. The first specific step of the method is to use the average form of the weighted measurement residual variance performance index rather than its usual total weighted residual form. Next it is helpful to interpret the solution to the normal equations as the average of a collection of sample vectors drawn from a hypothetical parent population. From here, using a standard statistical analysis approach, it directly follows as to how to determine the standard empirical state error covariance matrix. This matrix will contain the total uncertainty in the
Estimated United States Transportation Energy Use 2005
Energy Technology Data Exchange (ETDEWEB)
Smith, C A; Simon, A J; Belles, R D
2011-11-09
A flow chart depicting energy flow in the transportation sector of the United States economy in 2005 has been constructed from publicly available data and estimates of national energy use patterns. Approximately 31,000 trillion British Thermal Units (trBTUs) of energy were used throughout the United States in transportation activities. Vehicles used in these activities include automobiles, motorcycles, trucks, buses, airplanes, rail, and ships. The transportation sector is powered primarily by petroleum-derived fuels (gasoline, diesel and jet fuel). Biomass-derived fuels, electricity and natural gas-derived fuels are also used. The flow patterns represent a comprehensive systems view of energy used within the transportation sector.
On State Estimation with Bad Data Detection
Xu, Weiyu; Tang, Ao
2011-01-01
In this paper, we consider the problem of state estimation through observations possibly corrupted with both bad data and additive observation noises. A mixed $\\ell_1$ and $\\ell_2$ convex programming is used to separate both sparse bad data and additive noises from the observations. Through using the almost Euclidean property for a linear subspace, we derive a new performance bound for the state estimation error under sparse bad data and additive observation noises. Our main contribution is to provide sharp bounds on the almost Euclidean property of a linear subspace, using the "escape-through-a-mesh" theorem from geometric functional analysis. We also propose and numerically evaluate an iterative convex programming approach to performing bad data detections in nonlinear electrical power networks problems.
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.
Banerjee, Kinshuk; Das, Biswajit; Gangopadhyay, Gautam
2013-04-28
In this paper, we have explored generic criteria of cooperative behavior in ion channel kinetics treating it on the same footing with multistate receptor-ligand binding in a compact theoretical framework. We have shown that the characterization of cooperativity of ion channels in terms of the Hill coefficient violates the standard Hill criteria defined for allosteric cooperativity of ligand binding. To resolve the issue, an alternative measure of cooperativity is proposed here in terms of the cooperativity index that sets a unified criteria for both the systems. More importantly, for ion channel this index can be very useful to describe the cooperative kinetics as it can be readily determined from the experimentally measured ionic current combined with theoretical modelling. We have analyzed the correlation between the voltage value and slope of the voltage-activation curve at the half-activation point and consequently determined the standard free energy of activation of the ion channel using two well-established mechanisms of cooperativity, namely, Koshland-Nemethy-Filmer (KNF) and Monod-Wyman-Changeux (MWC) models. Comparison of the theoretical results for both the models with appropriate experimental data of mutational perturbation of Shaker K(+) channel supports the experimental fact that the KNF model is more suitable to describe the cooperative behavior of this class of ion channels, whereas the performance of the MWC model is unsatisfactory. We have also estimated the mechanistic performance through standard free energy of channel activation for both the models and proposed a possible functional disadvantage in the MWC scheme.
A subspace-based parameter estimation algorithm for Nakagami-m fading channels
Dianat, Sohail; Rao, Raghuveer
2010-04-01
Estimation of channel fading parameters is an important task in the design of communication links such as maximum ratio combining (MRC). The MRC weights are directly related to the fading channel coefficients. In this paper, we propose a subspace based parameter estimation algorithm for the estimation of the parameters of Nakagami-m fading channels in the presence of additive white Gaussian noise. Comparisons of our proposed approach are made with other techniques available in the literature. The performance of the algorithm with respect to the Cramer-Rao bound (CRB) is investigated. Computer simulation results for different signal to noise ratios (SNR) are presented.
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...
A COMPARISON OF TWO 2D CHANNEL ESTIMATORS FOR OFDM SYSTEM
Institute of Scientific and Technical Information of China (English)
Shu Feng; Cheng Shixin; Chen Ming
2006-01-01
The paper deals with two-dimensional (2D) channel estimation of Orthogonal Frequency Division Multiplexing (OFDM) system in slow fading wireless channel. We concentrate on two channel estimation schemes: Least Square (LS)+Weighted BiLinear (WBL) and LS+Linear Minimum Mean-Squared Error (LMMSE) where the first method is proposed in this paper. After theory analysis and simulation in Typical Urban (TU) channel, we find that LS+LMMSE achieves the optimal performance by exploiting prior knowledge of channel whereas LS+WBL, without requiring channel knowledge and with only half of the computational amount of LS+LMMSE, approaches LS+LMMSE in Bit Error Ratio (BER) performance when the distance of two adjoining pilot symbols along frequency direction is sufficiently small. This makes LS+WBL very suitable for wideband wireless applications.
Estimation of FBMC/OQAM fading channels using dual Kalman filters.
Aldababseh, Mahmoud; Jamoos, Ali
2014-01-01
We address the problem of estimating time-varying fading channels in filter bank multicarrier (FBMC/OQAM) wireless systems based on pilot symbols. The standard solution to this problem is the least square (LS) estimator or the minimum mean square error (MMSE) estimator with possible adaptive implementation using recursive least square (RLS) algorithm or least mean square (LMS) algorithm. However, these adaptive filters cannot well-exploit fading channel statistics. To take advantage of fading channel statistics, the time evolution of the fading channel is modeled by an autoregressive process and tracked by Kalman filter. Nevertheless, this requires the autoregressive parameters which are usually unknown. Thus, we propose to jointly estimate the FBMC/OQAM fading channels and their autoregressive parameters based on dual optimal Kalman filters. Once the fading channel coefficients at pilot symbol positions are estimated by the proposed method, the fading channel coefficients at data symbol positions are then estimated by using some interpolation methods such as linear, spline, or low-pass interpolation. The comparative simulation study we carried out with existing techniques confirms the effectiveness of the proposed method.
Estimation of FBMC/OQAM Fading Channels Using Dual Kalman Filters
Directory of Open Access Journals (Sweden)
Mahmoud Aldababseh
2014-01-01
Full Text Available We address the problem of estimating time-varying fading channels in filter bank multicarrier (FBMC/OQAM wireless systems based on pilot symbols. The standard solution to this problem is the least square (LS estimator or the minimum mean square error (MMSE estimator with possible adaptive implementation using recursive least square (RLS algorithm or least mean square (LMS algorithm. However, these adaptive filters cannot well-exploit fading channel statistics. To take advantage of fading channel statistics, the time evolution of the fading channel is modeled by an autoregressive process and tracked by Kalman filter. Nevertheless, this requires the autoregressive parameters which are usually unknown. Thus, we propose to jointly estimate the FBMC/OQAM fading channels and their autoregressive parameters based on dual optimal Kalman filters. Once the fading channel coefficients at pilot symbol positions are estimated by the proposed method, the fading channel coefficients at data symbol positions are then estimated by using some interpolation methods such as linear, spline, or low-pass interpolation. The comparative simulation study we carried out with existing techniques confirms the effectiveness of the proposed method.
Remote State Preparation via a Non-Maximally Entangled Channel
Institute of Scientific and Technical Information of China (English)
郑亦庄; 顾永建; 郭光灿
2002-01-01
We investigate remote state preparation (RSP) via a non-maximally entangled channel for three cases: a general qubit; a special ensemble of qubits (qubit states on the equator of the Bloch sphere); and an asymptotic limit of N copies ofa general state. The results show that the classical communication cost of RSP for the two latter cases can be less than that of teleportation, but for the first case, in a restricted setting, the classical communication cost is equal to that of teleportation. Whether or not this is the case for a more general setting is still an open question.
The widespread use of stream channelization and subsurface tile drainage for removing water from agricultural fields has led to the development of numerous channelized agricultural headwater streams within agricultural watersheds of the Midwestern United States. Channelized agricultural headwater s...
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.
Gaussian private quantum channel with squeezed coherent states
Jeong, Kabgyun; Kim, Jaewan; Lee, Su-Yong
2015-01-01
While the objective of conventional quantum key distribution (QKD) is to secretly generate and share the classical bits concealed in the form of maximally mixed quantum states, that of private quantum channel (PQC) is to secretly transmit individual quantum states concealed in the form of maximally mixed states using shared one-time pad and it is called Gaussian private quantum channel (GPQC) when the scheme is in the regime of continuous variables. We propose a GPQC enhanced with squeezed coherent states (GPQCwSC), which is a generalization of GPQC with coherent states only (GPQCo) [Phys. Rev. A 72, 042313 (2005)]. We show that GPQCwSC beats the GPQCo for the upper bound on accessible information. As a subsidiary example, it is shown that the squeezed states take an advantage over the coherent states against a beam splitting attack in a continuous variable QKD. It is also shown that a squeezing operation can be approximated as a superposition of two different displacement operations in the small squeezing regime. PMID:26364893
Shallow water acoustic channel estimation using two-dimensional frequency characterization.
Ansari, Naushad; Gupta, Anubha; Gupta, Ananya Sen
2016-11-01
Shallow water acoustic channel estimation techniques are presented at the intersection of time, frequency, and sparsity. Specifically, a mathematical framework is introduced that translates the problem of channel estimation to non-uniform sparse channel recovery in two-dimensional frequency domain. This representation facilitates disambiguation of slowly varying channel components against high-energy transients, which occupy different frequency ranges and also exhibit significantly different sparsity along their local distribution. This useful feature is exploited to perform non-uniform sampling across different frequency ranges, with compressive sampling across higher Doppler frequencies and close to full-rate sampling at lower Doppler frequencies, to recover both slowly varying and rapidly fluctuating channel components at high precision. Extensive numerical experiments are performed to measure relative performance of the proposed channel estimation technique using non-uniform compressive sampling against traditional compressive sampling techniques as well as sparsity-constrained least squares across a range of observation window lengths, ambient noise levels, and sampling ratios. Numerical experiments are based on channel estimates from the SPACE08 experiment as well as on a recently developed channel simulator tested against several field trials.
Nonlinear Channel Estimation for OFDM System by Complex LS-SVM under High Mobility Conditions
Charrada, Anis; 10.5121/ijwmn.2011.3412
2011-01-01
A nonlinear channel estimator using complex Least Square Support Vector Machines (LS-SVM) is proposed for pilot-aided OFDM system and applied to Long Term Evolution (LTE) downlink under high mobility conditions. The estimation algorithm makes use of the reference signals to estimate the total frequency response of the highly selective multipath channel in the presence of non-Gaussian impulse noise interfering with pilot signals. Thus, the algorithm maps trained data into a high dimensional feature space and uses the structural risk minimization (SRM) principle to carry out the regression estimation for the frequency response function of the highly selective channel. The simulations show the effectiveness of the proposed method which has good performance and high precision to track the variations of the fading channels compared to the conventional LS method and it is robust at high speed mobility.
Pilot Based Channel Estimation in IEEE 802.16a OFDM System
Institute of Scientific and Technical Information of China (English)
ZHU Qi; LU Hao
2005-01-01
Orthogonal Frequency Division Multiplexing(OFDM)is a kind of transmission techniques with high frequency efficiency,which will be widely used in next-generation wireless communication systems.In this paper,pilot-based channel estimation for IEEE 802.16a OFDM system is studied.By comparing the performance of LS(least squares)estimator and Linear Minimum Mean-Square Error(LMMSE)estimator using Preamble 1 and Preamble 2 suggested by IEEE 802.16a standard in slow fading channel,we propose that Preamble 1 can be used in small multipath delay spread channel and Preamble 2 can be used in large multipath delay spread channel.Considering the tradeoff between performance and complexity,the LS estimator is suggested.
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....
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...
Directory of Open Access Journals (Sweden)
K. Vidhya
2014-05-01
Full Text Available This research study mainly focuses to develop an efficient channel estimation approach through swarm intelligence approach with lesser computational complexity. Orthogonal Frequency Division Multiplexing (OFDM is a modulation approach used to fight with the selection of frequency of the transmission channels to attain high data rate without any disturbances. OFDM principle is to gain popularity in the wireless transmission area. OFDM is united with antenna at the transmitter and receiver to amplify the variety gain and to improve the system capacity on time-variant and frequency selective channels, ensuing in a Multiple-Input Multiple-Output (MIMO pattern. Least Square (LS and Minimum Mean Square Error (MMSE approaches are the most commonly used channel estimation techniques. In LS, the estimation process is simple but the problem is that it has high mean square error. In Low SNR, the MMSE is better than that of LS, but its main problem is its high computational complexity. In order to overcome the above said problems, a novel method is proposed in this research study which combines LS and MMSE. In this study improved PSO is introduced to select the best channel. Also that this proposed approach is more efficient and also requires less time to estimate the best channel when compared with other techniques. The experimental results show the performance of the proposed channel estimation method over the existing methods.
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.
Channel estimation in space and frequency domain for MIMO-OFDM systems
Institute of Scientific and Technical Information of China (English)
PAN Pei-sheng; ZHENG Bao-yu
2009-01-01
Multiple-input multiple-output (MIMO) systems can be combined with orthogonal frequency division multiplexing (OFDM) systems to improve the capacity and quality of wireless communications. In this article, a channel estimation technique in both space and frequency domain for MIMO-OFDM systems is proposed. It is shown that the proposed scheme with space-frequency pilot tones achieve optimal minimum mean square error (MMSE) channel estimation. Simulation results indicate that the proposed method achieves good performance.
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.
Combined CD and DGD Monitoring Based on Data-Aided Channel Estimation
DEFF Research Database (Denmark)
Pittalà, Fabio; Hauske, Fabian N.; Ye, Yabin;
2011-01-01
By use of a training sequence, fast and robust CD and DGD estimation is demonstrated for a 112 Gbit/s PDM-QPSK system over a wide range of combined channel impairments.......By use of a training sequence, fast and robust CD and DGD estimation is demonstrated for a 112 Gbit/s PDM-QPSK system over a wide range of combined channel impairments....
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 b...... 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....
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.
Multiple Access Channels with States Causally Known at Transmitters
Li, Min; Yener, Aylin
2010-01-01
The state-dependent multiple access channel (MAC) is considered where the state sequences are known causally to the encoders. First, a MAC with two independent states each known causally to one encoder is revisited, and a new achievable scheme inspired by the recently proposed noisy network coding is presented. This scheme is shown to achieve a rate region that is potentially larger than that provided by recent work for the same model. Next, capacity results are presented for a class of channels that include modulo-additive state-dependent MACs. It is shown that the proposed scheme can be easily extended to an arbitrary number of users. Next, a similar scheme is proposed for a MAC with common state known causally to all encoders. The corresponding achievable rate region is shown to reduce to the one given in the previous work as a special case for two users. Finally, output feedback is introduced in the model at hand with independent states and an example is provided to show the advantage of feedback in enlar...
Capacity of cognitive radio under imperfect secondary and cross link channel state information
Sboui, Lokman
2011-09-01
In this paper, we study the ergodic capacity of secondary user channel in a spectrum sharing scenario in which the secondary transmitter is instantaneously aware of estimated versions of the cross link (between the secondary transmitter and the primary receiver) and the secondary link Channel State Information (CSI). The secondary link optimal power profile along with the ergodic capacity are derived for a class of fading channels, under an average power constraint and an instantaneous interference outage constraint. We also show that our framework is rather general as it encompasses several previously studied spectrum sharing settings as special cases. In order to gain some insights on the capacity behavior, numerical results are shown for independent Rayleigh fading channels where it is found for instance, that at low SNR regime, only the secondary channel estimation matters and that the cross link CSI has no effect on the ergodic capacity; whereas at high SNR regime, the capacity is rather driven by the cross link CSI. © 2011 IEEE.
Two-Way Training Design for Discriminatory Channel Estimation in Wireless MIMO Systems
Huang, Chao-Wei
2011-01-01
This work examines the use of two-way training in multiple-input multiple-output (MIMO) wireless systems to discriminate the channel estimation performances between a legitimate receiver (LR) and an unauthorized receiver (UR). This thesis extends upon the previously proposed discriminatory channel estimation (DCE) scheme that allows only the transmitter to send training signals. The goal of DCE is to minimize the channel estimation error at LR while requiring the channel estimation error at UR to remain beyond a certain level. If the training signal is sent only by the transmitter, the performance discrimination between LR and UR will be limited since the training signals help both receivers perform estimates of their downlink channels. In this work, we consider instead the two-way training methodology that allows both the transmitter and LR to send training signals. In this case, the training signal sent by LR helps the transmitter obtain knowledge of the transmitter-to-LR channel, but does not help UR estim...
Preamble Design and Iterative Channel Estimation for OFDM/Offset QAM System
Directory of Open Access Journals (Sweden)
Su Hu
2009-12-01
Full Text Available In present of multi-path effect, the inter symbol interference (ISI always exists in the OFDM/OQAM system and the preamble based channel estimation for the conventional orthogonal frequency division multiplex with cyclic prefix (CP-OFDM is not feasible any more. Considering the characteristic of the extended Gaussian function (EGF, we propose two modified preamble based channel estimation by adding zero-value guard symbols, which are located at both sides (method A and the left side (method B of preamble reference symbol. Compared with the CP-OFDM system, the proposed preamble based channel estimation achieves 2dB improvement. Furthermore, we shorten the preamble without zero-value guard symbol to improve the spectrum efficiency. Unfortunately, the residual inter symbol interference (ISI from neighbor symbols degrade the channel estimation performance. We propose an iterative channel estimation method for OFDM/OQAM system to remove the residual ISI. Simulation results demonstrate that those proposed preamble design and iterative channel estimation methods are effective for OFDM/OQAM system.
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
Frequency direction Pilot-symbol Aided Channel Estimation (PACE) for Orthogonal Frequency Division Multiplexing (OFDM) is crucial in high-rate wireless systems. The choice of an estimator for upcoming standards, such as the Long Term Evolution (LTE) of UTRA, has to take into account their specifi......Frequency direction Pilot-symbol Aided Channel Estimation (PACE) for Orthogonal Frequency Division Multiplexing (OFDM) is crucial in high-rate wireless systems. The choice of an estimator for upcoming standards, such as the Long Term Evolution (LTE) of UTRA, has to take into account...
Improved Channel Estimation for CDD-OFDM Systems in Time-Varying Channels%时变CDD-OFDM系统中的改进EM信道估计
Institute of Scientific and Technical Information of China (English)
陈东华; 仇洪冰
2012-01-01
针对循环延时分集OFDM系统中的时变信道估计导频开销较大问题,提出了一种递归的改进期望最大化（EM）信道估计方法。该方法首先建立时变信道基扩展模型（BEM）与符号时间平均信道脉冲响应之间的数学关系,然后用其预测EM信道估计的初值,从而一方面利用了BEM参数的慢变特性来提高时变信道的预测精度,另一方面利用了BEM的简约化参数特性来保持算法实时性。仿真结果表明,当信噪比大于15 dB时,改进方法有效降低了判决辅助方法的误差传播效应,其误码性能接近理想信道时的性能。%For reducing the pilot overhead used in time-varying channel estimation of orthogonal frequency division multiplexing system with cyclic delay diversity (CDD-OFDM), an improved expectation-maximization (EM) based channel estimation scheme with recur- sive fashion was proposed. In this scheme, the mathematical relationship between the basis expansion model (BEM) of time-varying channels and the symbol time-averaged channel impulse response was firstly established and then used to predict the initial value of the EM based channel estimator, therefore the parsimonious parameterization properties of the BEM and the slow variations of the BEM pa- rameters could be exploited to improve the channel prediction accuracy and make the algorithm real-time, respectively. Simulation re- sults showed that when the signal to noise ratio is above 15 dB, the proposed scheme effectively reduces the error propagation of deci- sion directed channel tracking scheme, and has nearly the same bit error rate performance as that with perfect channel state informa- tion.
Blind Joint Maximum Likelihood Channel Estimation and Data Detection for SIMO Systems
Institute of Scientific and Technical Information of China (English)
Sheng Chen; Xiao-Chen Yang; Lei Chen; Lajos Hanzo
2007-01-01
A blind adaptive scheme is proposed for joint maximum likelihood (ML) channel estimation and data detection of singleinput multiple-output (SIMO) systems. The joint ML optimisation over channel and data is decomposed into an iterative optimisation loop. An efficient global optimisation algorithm called the repeated weighted boosting search is employed at the upper level to optimally identify the unknown SIMO channel model, and the Viterbi algorithm is used at the lower level to produce the maximum likelihood sequence estimation of the unknown data sequence. A simulation example is used to demonstrate the effectiveness of this joint ML optimisation scheme for blind adaptive SIMO systems.
RBF multiuser detector with channel estimation capability in a synchronous MC-CDMA system.
Ko, K; Choi, S; Kang, C; Hong, D
2001-01-01
The authors propose a multiuser detector with channel estimation capability using a radial basis function (RBF) network in a synchronous multicarrier-code division multiple access (MC-CDMA) system. The authors propose to connect an RBF network to the frequency domain to effectively utilize the frequency diversity. Simulations were performed over frequency-selective and multi-path fading channels. These simulations confirmed that the proposed receiver can be used both for the channel estimation and as a multi-user receiver, thus permitting an increase in the number of active users.
MIMO Channel Estimation and Equalization Using Three-Layer Neural Networks with Feedback
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
This paper describes a channel estimation and equalization algorithm using three-layer artificial neural networks (ANNs) with feedback for multiple input multiple output wireless communication systems.An ANN structure with feedback was designed to use different learning algorithms in the different ANN layers. This actually forms a Turbo iteration process between the different algorithms which effectively improves the estimation performance of the channel equalizer. Simulation results show that this channel equalization algorithm has better computational efficiency and faster convergence than higher order statistics based algorithms.
Institute of Scientific and Technical Information of China (English)
JIANG Zheng; QIN Xiao-fang; ZHANG Xin; CHANG Yong-yu
2008-01-01
A new Turbo iterative receiver structure is proposed for the uplink multiple-input multiple-output orthogonal frequency division multiple access (MIMO-OFDMA) systems. The space-alternating generalized expectation-maximization (SAGE) algorithm is naturally embedded in the framework of iterative receiver to perform synchronization and detection using the Turbo detector outputs. In each iteration, the expectation step intends to remove the multiple access interference (MAI) caused by other asynchronous users, and the maximization step is utilized to estimate the required parameters (i.e., timing offset, carrier frequency offset, channel state information, etc.) sequentially for each user. Simulation results show that the proposed algorithm can approach the performance of ideal receiver closely, while the processing complexity is rather lower than the conventional detectors.
Pilot Beam Pattern Design for Channel Estimation in Massive MIMO Systems
Noh, Song; Zoltowski, Michael D.; Sung, Youngchul; Love, David J.
2014-10-01
In this paper, the problem of pilot beam pattern design for channel estimation in massive multiple-input multiple-output systems with a large number of transmit antennas at the base station is considered, and a new algorithm for pilot beam pattern design for optimal channel estimation is proposed under the assumption that the channel is a stationary Gauss-Markov random process. The proposed algorithm designs the pilot beam pattern sequentially by exploiting the properties of Kalman filtering and the associated prediction error covariance matrices and also the channel statistics such as spatial and temporal channel correlation. The resulting design generates a sequentially-optimal sequence of pilot beam patterns with low complexity for a given set of system parameters. Numerical results show the effectiveness of the proposed algorithm.
Energy Efficient Estimation of Gaussian Sources Over Inhomogeneous Gaussian MAC Channels
Wei, Shuangqing; Iyengar, Sitharama; Rao, Nageswara S
2007-01-01
It has been shown lately the optimality of uncoded transmission in estimating Gaussian sources over homogeneous/symmetric Gaussian multiple access channels (MAC) using multiple sensors. It remains, however, unclear whether it still holds for any arbitrary networks and/or with high channel signal-to-noise ratio (SNR) and high signal-to-measurement-noise ratio (SMNR). In this paper, we first provide a joint source and channel coding approach in estimating Gaussian sources over Gaussian MAC channels, as well as its sufficient and necessary condition in restoring Gaussian sources with a prescribed distortion value. An interesting relationship between our proposed joint approach with a more straightforward separate source and channel coding scheme is then established. We then formulate constrained power minimization problems and transform them to relaxed convex geometric programming problems, whose numerical results exhibit that either separate or uncoded scheme becomes dominant over a linear topology network. In ...
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.
On Communications under Stochastic Energy Harvesting with Noisy Channel State Information
Zenaidi, Mohamed Ridha
2017-02-07
In energy harvesting communications, the transmitters have to adapt transmission to the availability of energy harvested during communication. The performance of the transmission depends on the channel conditions which vary randomly due environmental changes. In this paper, we consider the problem of power allocation taking into account the energy arrivals over time and imperfect channel state information (CSI) available at the transmitter, in order to maximize the throughput. Differently from previous work, the CSI at the transmitter is not perfect and may include estimation errors. We solve this problem with respect to energy harvesting constraints. We determine the optimal power policy in the case where the channel is perfectly known at the receiver. Furthermore, a study of the asymptotic behavior of the communication system is proposed. Specifically, we analyze the average throughput (AT) in a system where the average recharge rate (ARR) is asymptotically small and when it is very high. Selected numerical results are provided to illustrate our analysis.
Performance limits of energy harvesting communications under imperfect channel state information
Zenaidi, Mohamed Ridha
2016-07-26
In energy harvesting communications, the transmitters have to adapt transmission to availability of energy harvested during the course of communication. The performance of the transmission depends on the channel conditions which vary randomly due to mobility and environmental changes. In this paper, we consider the problem of power allocation taking into account the energy arrivals over time and the degree of channel state information (CSI) available at the transmitter, in order to maximize the throughput. Differently from previous work, the CSI at the transmitter is not perfect and may include estimation errors. We solve this problem with respect to the causality and energy storage constraints. We determine the optimal offline policy in the case where the channel is assumed to be perfectly known at the receiver. Also, we obtain the power policy when the transmitter has no CSI. Furthermore, we analyze the asymptotic average throughput in a system where the average recharge rate goes asymptotically to zero. © 2016 IEEE.
SIMPLE AND EFFICIENT SPACE-TIME CHANNEL AND DOA ESTIMATION TECHNIQUES IN TD-SCDMA SYSTEMS
Institute of Scientific and Technical Information of China (English)
Li Ping'an; Ma Ning
2006-01-01
In this paper, a simple method is presented for multi-user space-time channel estimation in Time Division-Synchronized Code Division Multiple Access (TD-SCDMA) systems. The method is based on a specific midamble assignment strategy, which results in a cyclic Toeplitz midamble-matrix in the linear equation of the received data vectors. A Fast Fourier Transform (FFT)-based algorithm is used to obtain the estimate of the uplink multi-user space-time channels. Furthermore, the estimated space-time channel is applied to the identification of multi-paths for each user, and Direction Of Arrival (DOA) estimation for each path is carried out by using the extracted spatial signature vector. Aside from the simplicity in computation, the proposed direction of arrival estimation method can effectively resolve multi-paths regardless of the correlation and angle separations of the multi-paths.
Como, Giacomo
2010-01-01
A single-letter characterization is provided for the capacity region of finite-state multiple-access channels, when the channel state process is an independent and identically distributed sequence, the transmitters have access to partial (quantized) state information, and complete channel state information is available at the receiver. The partial channel state information is assumed to be asymmetric at the encoders. As a main contribution, a tight converse coding theorem is presented. The difficulties associated with the case when the channel state has memory are discussed and connections to decentralized stochastic control theory are presented.
Teleportation of a multiqubit state by an entangled qudit channel
Institute of Scientific and Technical Information of China (English)
郑亦庄; 顾永建; 吴桂初; 郭光灿
2003-01-01
We investigate the problem of teleportation of an M-qubit state by using an entangled qudit pair as a quantum channe; and show that the teleportation of a multiparticle state can correspond to the teleportation of a multidimensional state.We also introduce a quantum-state converter composed of beamspliter arrays,on /off -detectors and coross-Kerr couplers and demonstrate that the stte concersion from an M-qubit to an N-dimensional qudit and vice versa can be implemented with this converter,where N=2M,Based on this ,an experimentallu feasible for the teleportation of an M-qubit via an entangl;ed N-level qudit pair channel is proposed.
A Coordinated Approach to Channel Estimation in Large-scale Multiple-antenna Systems
Yin, Haifan; Filippou, Miltiades; Liu, Yingzhuang
2012-01-01
This paper addresses the problem of channel estimation in multi-cell interference-limited cellular networks. We consider systems employing multiple antennas and are interested in both the finite and large-scale antenna number regimes (so-called "Massive MIMO"). Such systems deal with the multi-cell interference by way of per-cell beamforming applied at each base station. Channel estimation in such networks, which is known to be hampered by the pilot contamination effect, constitute a major bottleneck for overall performance. We present a novel approach which tackles this problem by enabling a low-rate coordination between cells during the channel estimation phase itself. The coordination makes use of the additional second-order statistical information about the user channels, which are shown to offer a powerful way of discriminating across interfering users with even strongly correlated pilot sequences. Importantly, we demonstrate analytically that in the large number of antennas regime the pilot contaminatio...
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.
Adaptive Modulation with Channel Estimation in High-Speed Packet-Based OFDM Communication Systems
Institute of Scientific and Technical Information of China (English)
HOU Xiao-lin; WU Jun-li; YIN Chang-chuan; YUE Guang-xin
2004-01-01
In this paper, adaptive modulation with channel estimation in high-speed packet-based Orthogonal Frequency Division Multiplexing (OFDM) communication systems for beyond 3G are discussed. Different adaptive modulation and channel estimation methods are presented and compared, then those methods suitable for our intended application are chosen. Conclusions can be drawn from computer simulations that with proper selection of packet length and subband width, wide subband adaptive modulation with Least Square plus Discrete-time Fourier Transform (LS-DFT) channel estimation can give an acceptable performance with low complexity for channel with low Doppler shift and small path delay. Otherwise, narrow subband or subcarrier adaptive modulation together with LS-DFT plus Decision Directed (LS-DFT-DD) must be used.
Preamble-based channel estimation in single-relay networks using FBMC/OQAM
Mavrokefalidis, Christos; Kofidis, Eleftherios; Rontogiannis, Athanasios A.; Theodoridis, Sergios
2014-12-01
Preamble-based channel estimation in filter bank-based multicarrier (FBMC) systems using offset quadrature amplitude modulation (OQAM) has been extensively studied in the last few years, due to the many advantages this modulation scheme can offer over cyclic prefix (CP)-based orthogonal frequency division multiplexing (OFDM) and in view of the interesting challenges posed on the channel estimator by the interference effect inherent in such an FBMC system. In particular, preambles of short duration and of both the block ( full) and comb ( sparse) types were designed so as to minimize the channel estimation mean squared error (MSE) subject to a given transmit energy. In the light of the important role that relay-based cooperative networks are expected to play in future wireless communication systems, it is of interest to consider FBMC/OQAM, and in particular questions associated to preamble-based channel estimation, in such a context as well. The goal of this paper is to address these problems and come up with optimal solutions that extend existing results in a single relay-based cooperative network. Both low and medium frequency selective channels are considered. In addition to optimal preamble and estimator design, the equalization/detection task is studied, shedding light to a relay-generated interference effect and proposing a simple way to come over it. The reported simulation results corroborate the analysis and reveal interesting behavior with respect to channel frequency selectivity and signal-to-noise ratio.
Reinhardt, Colin N.; Tsintikidis, Dimitris; Hammel, Stephen; Kuga, Yasuo; Ritcey, James A.; Ishimaru, Akira
2012-03-01
Using an 850-nanometer-wavelength free-space optical (FSO)communications system of our own design, we acquired field data for the transmitted and received signals in fog at Point Loma, CA for a range of optical depths within the multiple-scattering regime. Statistical estimators for the atmospheric channel transfer function and the related coherency function were computed directly from the experimental data. We interpret the resulting channel transfer function estimates in terms of the physics of the atmospheric propagation channel and fog aerosol particle distributions. We investigate the behavior of the estimators using both real field-test data and simulated propagation data. We compare the field-data channel transfer function estimates against the outputs from a computationally-intensive radiative-transfer theory model-based approach, which we also developed previously for the FSO multiple-scattering atmospheric channel. Our results show that the data-driven channel transfer function estimates are in close agreement with the radiative transfer modeling, and provide comparable receiver signal detection performance improvements while being significantly less time and computationally-intensive.
Multiuser detection and channel estimation: Exact and approximate methods
DEFF Research Database (Denmark)
Fabricius, Thomas
2003-01-01
. We also derive optimal detectors when nuisance parameters such as the channel and noise level are unknown, and show how well the proposed methods fit into this framework via the Generalised Expectation Maximisation algorithm. Our numerical evaluation show that naive mean field annealing and adaptive...... order Plefka expansion, adaptive TAP, and large system limit self-averaging behaviours, and a method based on Kikuchi and Bethe free energy approximations, which we denote the Generalised Graph Expansion. Since all these methods are improvements of the naive mean field approach we make a thorough...... analysis of the convexity and bifurcations of the naive mean field free energy and optima. This proves that we can avoid local minima by tracking a global convex solution into the non-convex region, effectively avoiding error propagation. This method is in statistical physics denoted mean field annealing...
Channel estimation for MIMO-OFDM systems in rapid fading channels%MIMO-OFDM系统中快衰落信道的估计
Institute of Scientific and Technical Information of China (English)
吴赟; 罗汉文; 宋文涛; 黄建国
2007-01-01
A channel estimation approach for orthogonal frequency division multiplexing with multiple-input and multipleoutput(MIMO-OFDM)in rapid fading channels is proposed.This approach combines the advantages of an optimal training sequence based least-square(DLS)algorithm and an expectation-maximization(EM)algorithm.The channels at the training blocks are estimated using an estimator based on the OLS algorithm.To compensate for the fast Rayleigh fading at the data blocks,a time domain based Gaussian interpolation filter is presented.Furthermore,an EM algorithm is introduced to improve the performance of channel estimation by a few iterations.Simulations show that this channel estimation approach can effectively track rapid channel variation.
Institute of Scientific and Technical Information of China (English)
XUGuoxing; GANLiangcai; ZHANGXuliang; HUANGTiaxi
2005-01-01
In this paper, we consider subspace based channel estimation methods for Turbo parallel interference cancellation and decoding integrating frequency diversity combining (Turbo FDC-PIC/decoding) over convolutionally coded multi-carrier Direct-sequence Code-division multiple access (DS-CDMA). Applying Turbo principle, we propose blind subspace iterative channel estimation, and apply it to Turbo FDC-PIC/decoding to perform joint channel estimation, detection and decoding. The simu- lation results show that Turbo FDC-PIC/decoding with blind subspace iterative channel estimation has greater performance improvement than that with blind subspace noniterative channel estimation or Pilot symbol aided (PSA) iterative channel estimation, and after a number of iterations, can even obtain performance close to Turbo FDC-PIC/decoding with ideal channel estimation. For example, with the chosen simulation parameter and for the fourth iteration, at the Signal-to-noise rate (SNR) of 7dB, Turbo FDC-PIC/decoding with blind subspace iterative channel estimation acquires the bit error rate of 9×10-4, nearly one order of magnitude lower than that of Turbo FDC-PIC/decoding with PSA iterative channel estimation or with blind subspace noniterative channel estimation. Besides, for blind subspace iterative channel estimation, pilot symbols aren't needed to insert in coded symbols, and therefore data rate is not lowered.
Directory of Open Access Journals (Sweden)
B. Prasad
2016-06-01
Full Text Available In this paper outage performance of a secondary user (SU is evaluated under amplify and forward (AF relay selection scheme with an imperfect channel state information (CSIwhile sharing spectrum in an underlay cognitive radio network (CRN. In underlay, the SU coexists with primary user (PU in the same band provided the interference produced by SU at the PU receiver is below the interference threshold of PU which limits the transmission power of SU and coverage area. Relays help to improve the performance of SU in underlay. However relays are also constrained in transmit power due to interference constraint imposed by PU. Closed form expression of the outage probability of SU with maximum transmit power constraint of relay under imperfect CSI is derived. A scaling factor based power control is used for the SU transmitter and the relay in order to maintain the interference constraint at PU receiver due to imperfect CSI. The impact of different parameters viz. correlation coefficient, channel estimation error, tolerable interference threshold, number of relays and the maximum transmit power constraint of relay on SU performance is investigated. A MATLAB based test bed has also been developed to carry out simulation in order to validate the theoretical result.
Institute of Scientific and Technical Information of China (English)
MEI Yu-Xue; CHEN Lin; CHEN Yi-Xin
2006-01-01
@@ In a process of remote state preparation, the universality of quantum channel is an essential ingredient. That is, one quantum channel should be feasible to remotely prepare any given qubit state. This problem appears in a process where one uses non-maximally entangled state as the passage. We present a scheme in which any given qubit |φ〉 = cosθ|0〉 + sinθeiψ|1〉 could be remotely prepared by using minimum classical bits and the previously shared non-maximally entangled state with a high fidelity, under the condition that the receiver holds the knowledge of θ. This condition is helpful to reduce the necessary amount of quantum channels, which is proven to be a low quantity to realize the universality. We also give several methods to investigate the trade-off between this amount and the achievable fidelity of the protocol.
Joint remote state preparation (JRSP) of two-qubit equatorial state in quantum noisy channels
Adepoju, Adenike Grace; Falaye, Babatunde James; Sun, Guo-Hua; Camacho-Nieto, Oscar; Dong, Shi-Hai
2017-02-01
This letter reports the influence of noisy channels on JRSP of two-qubit equatorial state. We present a protocol for JRSP of two-qubit equatorial state. Afterward, we investigate the effects of five quantum noises on the protocol. We find that the system loses some of its properties as consequence of unwanted interactions with environment. For instance, within the domain 0 < λ < 0.65, the information lost via transmission of qubits in amplitude channel is most minimal, while for 0.65 < λ ≤ 1, the information lost in phase flip channel becomes the most minimal. Also, for any given λ, the information transmitted through depolarizing channel has the least chance of success.
Impact of Crosstalk Channel Estimation on the DSM Performance for DSL Networks
Directory of Open Access Journals (Sweden)
Neiva Lindqvist
2010-01-01
Full Text Available The development and assessment of spectrum management methods for the copper access network are usually conducted under the assumption of accurate channel information. Acquiring such information implies, in practice, estimation of the crosstalk coupling functions between the twisted-pair lines in the access network. This type of estimation is not supported or required by current digital subscriber line (DSL standards. In this work, we investigate the impact of the inaccuracies in crosstalk estimation on the performance of dynamic spectrum management (DSM algorithms. A recently proposed crosstalk channel estimator is considered and a statistical sensitivity analysis is conducted to investigate the effects of the crosstalk estimation error on the bitloading and on the achievable data rate for a transmission line. The DSM performance is then evaluated based on the achievable data rates obtained through experiments with DSL setups and computer simulations. Since these experiments assume network scenarios consisting of real twisted-pair cables, both crosstalk channel estimates and measurements (for a reference comparison are considered. The results indicate that the error introduced by the adopted estimation procedure does not compromise the performance of the DSM techniques, that is, the considered crosstalk channel estimator provides enough means for a practical implementation of DSM.
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
The effect of flow data resolution on sediment yield estimation and channel design
Rosburg, Tyler T.; Nelson, Peter A.; Sholtes, Joel S.; Bledsoe, Brian P.
2016-07-01
The decision to use either daily-averaged or sub-daily streamflow records has the potential to impact the calculation of sediment transport metrics and stream channel design. Using bedload and suspended load sediment transport measurements collected at 138 sites across the United States, we calculated the effective discharge, sediment yield, and half-load discharge using sediment rating curves over long time periods (median record length = 24 years) with both daily-averaged and sub-daily streamflow records. A comparison of sediment transport metrics calculated with both daily-average and sub-daily stream flow data at each site showed that daily-averaged flow data do not adequately represent the magnitude of high stream flows at hydrologically flashy sites. Daily-average stream flow data cause an underestimation of sediment transport and sediment yield (including the half-load discharge) at flashy sites. The degree of underestimation was correlated with the level of flashiness and the exponent of the sediment rating curve. No consistent relationship between the use of either daily-average or sub-daily streamflow data and the resultant effective discharge was found. When used in channel design, computed sediment transport metrics may have errors due to flow data resolution, which can propagate into design slope calculations which, if implemented, could lead to unwanted aggradation or degradation in the design channel. This analysis illustrates the importance of using sub-daily flow data in the calculation of sediment yield in urbanizing or otherwise flashy watersheds. Furthermore, this analysis provides practical charts for estimating and correcting these types of underestimation errors commonly incurred in sediment yield calculations.
Coded DS-CDMA Systems with Iterative Channel Estimation and no Pilot Symbols
Torrieri, Don; Kwon, Hyuck
2010-01-01
In this paper, we describe direct-sequence code-division multiple-access (DS-CDMA) systems with quadriphase-shift keying in which channel estimation, coherent demodulation, and decoding are iteratively performed without the use of any training or pilot symbols. An expectation-maximization channel-estimation algorithm for the fading amplitude, phase, and the interference power spectral density (PSD) due to the combined interference and thermal noise is proposed for DS-CDMA systems with irregular repeat-accumulate codes. After initial estimates of the fading amplitude, phase, and interference PSD are obtained from the received symbols, subsequent values of these parameters are iteratively updated by using the soft feedback from the channel decoder. The updated estimates are combined with the received symbols and iteratively passed to the decoder. The elimination of pilot symbols simplifies the system design and allows either an enhanced information throughput, an improved bit error rate, or greater spectral eff...
Time-domain channel estimator based on cyclic correlation for OFDM systems with guard interval
Institute of Scientific and Technical Information of China (English)
JIA Min; GU Xue-mai; IM Se-bin; CHOI Hyung-jin
2008-01-01
Channel impulse response (CIR) can be estimated on the basis of cyclic correlation in time-domain for orthogonal frequency division multiplexing (OFDM) systems. This article proposes a generalized channel estimation method to reduce the estimation error by taking the average of different CIRs. Channel impulse responses are derived according to the different starting points of cyclic correlation. In addition, an effective CIR length estimation algorithm is also presented. The whole proposed methods are more effective to OFDM systems, especially to those with longer cyclic prefix. The analysis and the simulation results verify that the mean square error performance is 4-5 dB better than the conventional schemes under the same conditions.
Xu, Wei; Lu, Wu-Sheng; 10.1109/TSP.2010.2056687
2012-01-01
Multi-antenna relaying has emerged as a promising technology to enhance the system performance in cellular networks. However, when precoding techniques are utilized to obtain multi-antenna gains, the system generally requires channel state information (CSI) at the transmitters. We consider a linear precoding scheme in a MIMO relaying broadcast channel with quantized CSI feedback from both two-hop links. With this scheme, each remote user feeds back its quantized CSI to the relay, and the relay sends back the quantized precoding information to the base station (BS). An upper bound on the rate loss due to quantized channel knowledge is first characterized. Then, in order to maintain the rate loss within a predetermined gap for growing SNRs, a strategy of scaling quantization quality of both two-hop links is proposed. It is revealed that the numbers of feedback bits of both links should scale linearly with the transmit power at the relay, while only the bit number of feedback from the relay to the BS needs to gr...
A framework for interpreting regularized state estimation
Sugiura, Nozomi; Fujii, Yosuke; Kamachi, Masafumi; Ishikawa, Yoichi; Awaji, Toshiyuki
2015-01-01
Four-dimensional variational data assimilation (4D-Var) on a seasonal-to-interdecadal time scale under the existence of unstable modes can be viewed as an optimization problem of synchronized, coupled chaotic systems. The problem is tackled by adjusting initial conditions to bring all stable modes closer to observations and by using a continuous guide to direct unstable modes toward a reference time series. This interpretation provides a consistent and effective procedure for solving problems of long-term state estimation. By applying this approach to an ocean general circulation model with a parameterized vertical diffusion procedure, it is demonstrated that tangent linear and adjoint models in this framework should have no unstable modes and hence be suitable for tracking persistent signals. This methodology is widely applicable to extend the assimilation period in 4D-Var.
Estimation of Velocity Profile Based on Chiu’s Equation in Width of Channels
Directory of Open Access Journals (Sweden)
Saman Nikmehr
2010-08-01
Full Text Available Distribution of velocity in channel is one of the most parameters for solution of hydraulic problems. Determination of energy coefficient, momentum and distribution of sediment concentration depend on distribution of velocity profile. The entropy parameter of a channel section can be determined from the relation between the mean and maximum velocities. A technique has been developed to determine a velocity profile on a single vertical passing through the point of maximum velocity in a channel cross section. This method is a way in order to quick and cheap estimating of velocity distribution with high accuracy in channels. So that in this research the power estimation of Chiu method base on entropy concept was determined. Also Chiu’s equation that is based on entropy concept and probability domain, has compared with logarithmic and exponential equations to estimation of velocity profile in width of channel in various depths. The results show that Chiu’s equation better than logarithmic and exponential equations to estimation of velocity profile in width of channel.
CHANNEL ESTIMATION TECHNIQUE IN MULTI-ANTENNA AF RELAY COMMUNICATION SYSTEMS
Institute of Scientific and Technical Information of China (English)
Chen Mingxue; Xu Chengqi
2011-01-01
The channel estimation technique is investigated in OFDM communication systems with multi-antenna Amplify-and-Forward (AF) relay.The Space-Time Block Code (STBC) is applied at the transmitter of the relay to obtain diversity gain.According to the transmission characteristics of OFDM symbols on multiple antennas,a pilot-aided Linear Minimum Mean-Square-Error (LMMSE) channel estimation algorithm with low complexity is designed.Simulation results show that,the proposed LMMSE estimator outperforms least-square estimator and approaches the optimal estimator without error in the performance of Symbol Error Ratio (SER) under several modulation modes,and has a good estimation effect in the realistic relay communication scenario.
Application of radial basis neural network for state estimation of ...
African Journals Online (AJOL)
user
conventional Weighted Least Squares (WLS) State Estimator on basis of time, ... The conventional state estimation is based on algorithmic method of solving a large ... The RBF unit or transfer function is similar to Gaussian density function, ...
Advances in Derivative-Free State Estimation for Nonlinear Systems
DEFF Research Database (Denmark)
Nørgaard, Magnus; Poulsen, Niels Kjølstad; Ravn, Ole
In this paper we show that it involves considerable advantages to use polynomial approximations obtained with an interpolation formula for derivation of state estimators for nonlinear systems. The estimators become more accurate than estimators based on Taylor approximations, and yet...
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
An Improved Multicell MMSE Channel Estimation in a Massive MIMO System
Directory of Open Access Journals (Sweden)
Ke Li
2014-01-01
Full Text Available Massive MIMO is a promising technology to improve both the spectrum efficiency and the energy efficiency. The key problem that impacts the throughput of a massive MIMO system is the pilot contamination due to the nonorthogonality of the pilot sequences in different cells. Conventional channel estimation schemes cannot mitigate this problem effectively, and the computational complexity is increasingly becoming larger in views of the large number of antennas employed in a massive MIMO system. Furthermore, the channel estimation is always carried out with some ideal assumptions such as the complete knowledge of large-scale fading. In this paper, a new channel estimation scheme is proposed by utilizing interference cancellation and joint processing. Highly interfering users in neighboring cells are identified based on the estimation of large-scale fading and then included in the joint channel processing; this achieves a compromise between the effectiveness and efficiency of the channel estimation at a reasonable computational cost, and leads to an improvement in the overall system performance. Simulation results are provided to demonstrate the effectiveness of the proposed scheme.
CUCKOO SEARCH-AIDED LMS ALGORITHM FOR CHANNEL ESTIMATION IN MC-CDMA SYSTEMS
Directory of Open Access Journals (Sweden)
S. Balaji
2014-01-01
Full Text Available In the progress of transmission systems that uses the diversity in various domains, the execution of competent baseband receivers categorized by affordable computational load is an essential thing. This would be an imperative point in the future expansion of 4G systems in which the space, time and frequency diversity will be merged together to enhance the system throughput. Here, we develop a channel estimation technique for MC-CDMA system for the minimization of BER and the maximization of throughput. The maximization of throughput is an essential thing for the successful reception of signal. At the receiver side, the original data is obtained based on the channel estimation algorithm and the inverse process of the transmitter side is performed in the receiver side. The major contribution of our work is to estimate the channel information in an adaptive way. We estimate the channel using the cuckoo search algorithm based on the best solution we obtain from the cuckoo search algorithm. After estimating the channel, we calculate the Bit Error Rate (BER performance and throughput based on the acknowledgement send by the receiver. Experimental results show that our technique is better in terms of BER and throughput compared to the existing technique.
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.
Vision Aided State Estimation for Helicopter Slung Load System
DEFF Research Database (Denmark)
Bisgaard, Morten; Bendtsen, Jan Dimon; la Cour-Harbo, Anders
2007-01-01
This paper presents the design and verification of a state estimator for a helicopter based slung load system. The estimator is designed to augment the IMU driven estimator found in many helicopter UAV s and uses vision based updates only. The process model used for the estimator is a simple 4 st...... the estimator is verified using flight data and it is shown that it is capable of reliably estimating the slung load states....
Joint channel estimation and symbol detection for space-time block code
Institute of Scientific and Technical Information of China (English)
单淑伟; 罗汉文; 宋文涛
2004-01-01
The simplified joint channel estimation and symbol detection based on the EM (expectation-maximization) algorithm for space-time block code (STBC) are proposed. By assuming channel to be invariant within only one STBC word and utilizing the orthogonal structure of STBC, the computational complexity and cost of this algorithm are both very low, so it is very suitable to implementation in real systems.
Sensitivity analysis of the channel estimation deviation to the MAP decoding algorithm
Institute of Scientific and Technical Information of China (English)
WAN Ke; FAN Ping-zhi
2006-01-01
As a necessary input parameter for maximum a-posteriori(MAP) decoding algorithm,SNR is normally obtained from the channel estimation unit.Corresponding research indicated that SNR estimation deviation degraded the performance of Turbo decoding significantly.In this paper,MAP decoding algorithm with SNR estimation deviation was investigated in detail,and the degradation mechanism of Turbo decoding was explained analytically.The theoretical analysis and computer simulation disclosed the specific reasons for the performance degradation when SNR estimation was less than the actual value,and for the higher sensitivity of SNR estimation to long-frame Turbo codes.
Extended Lubrication Theory: Estimation of Fluid Flow in Channels with Variable Geometry
Tavakol, Behrouz; Froehlicher, Guillaume; Stone, Howard A
2014-01-01
Lubrication theory is broadly applicable to the flow characterization of thin fluid films and the motion of particles near surfaces. We offer an extension to lubrication theory by considering higher-order terms of the analytical approximation to describe the fluid flow in a channel with features of a modest aspect ratio. We find good agreement between our analytical results and numerical simulations. We show that the extended lubrication theory is a robust tool for an accurate estimate of laminar fluid flow in channels with features on the order of the channel height, accounting for both smooth and sharp changes in geometry.
Hybrid LS-LMMSE Channel Estimation Technique for LTE Downlink Systems
Khlifi, Abdelhakim; 10.5121/ijngn.2011.3401
2012-01-01
In this paper, we propose to improve the performance of the channel estimation for LTE Downlink systems under the effect of the channel length. As LTE Downlink system is a MIMO-OFDMA based system, a cyclic prefix (CP) is inserted at the beginning of each transmitted OFDM symbol in order to mitigate both inter-carrier interference (ICI) and inter-symbol interference (ISI). The inserted CP is usually equal to or longer than the channel length. However, the cyclic prefix can be shorter because of some unforeseen channel behaviour. Previous works have shown that in the case where the cyclic prefix is equal to or longer than the channel length, LMMSE performs better than LSE but at the cost of computational complexity .In the other case, LMMSE performs also better than LS only for low SNR values. However, LS shows better performance for LTE Downlink systems for high SNR values. Therefore, we propose a hybrid LS-LMMSE channel estimation technique robust to the channel length effect. MATLAB Monte-Carlo simulations a...
Estimation of turbulent channel flow based on the wall measurement with a statistical approach
Hasegawa, Yosuke; Suzuki, Takao
2016-11-01
A turbulent channel flow at Ret au = 100 with periodic boundary conditions is estimated with linear stochastic estimation only based on the wall measurement, i.e. the shear-stress in the streamwise and spanwise directions as well as the pressure over the entire wavenumbers. The results reveal that instantaneous measurement on the wall governs the success of the estimation in y+ feed the velocity components from the linear stochastic estimation via the body-force term into the Navier-Stokes system; however, the estimation slightly improves in the log layer, indicating some benefit of involving a dynamical system but over-suppression of turbulent kinetic energy beyond the viscous sublayer by the linear stochastic estimation. Motions inaccurately estimated in the buffer layer prevent from further reconstruction toward the centerline even if we relax the feedback forcing and let the flow evolve nonlinearly through the estimator. We also argue the inherent limitation of turbulent flow estimation based on the wall measurement.
Quantum Decoherence Timescales for Ionic Superposition States in Ion Channels
Salari, V; Fazileh, F; Shahbazi, F
2014-01-01
There are many controversial and challenging discussions about quantum effects in microscopic structures in neurons of the human brain. The challenge is mainly because of quick decoherence of quantum states due to hot, wet and noisy environment of the brain which forbids long life coherence for brain processing. Despite these critical discussions, there are only a few number of published papers about numerical aspects of decoherence in neurons. Perhaps the most important issue is offered by Max Tegmark who has calculated decoherence times for the systems of "ions" and "microtubules" in neurons of the brain. In fact, Tegmark did not consider ion channels which are responsible for ions displacement through the membrane and are the building blocks of electrical membrane signals in the nervous system. Here, we would like to re-investigate decoherence times for ionic superposition states by using the data obtained via molecular dynamics simulations. Our main approach is according to what Tegmark has used before. I...
Streamwise decay of localized states in channel flow
Zammert, Stefan
2016-01-01
Channel flow, the pressure driven flow between parallel plates, has exact coherent structures that show various degrees of localization. For states which are localized in streamwise direction but extended in spanwise direction, we show that they are exponentially localized, with decay constants that are different on the upstream and downstream side. We extend the analysis of Brand and Gibson, J. Fluid Mech. 750, R1 (2014), for stationary states to the case of advected structures that is needed here, and derive expressions for the decay in terms of eigenvalues and eigenfunctions of certain second order differential equations. The results are in very good agreement with observations on exact coherent structures of different transversal wave length.
Training sequence based channel estimation for indoor visible light communication system
Institute of Scientific and Technical Information of China (English)
WANG Jun-bo; JIAO Yuan; DANG Xiao-yu; CHEN Ming; XIE Xiu-xiu; CAO Ling-ling
2011-01-01
Channel estimation is a key technology in indoor wireless visible light communications (VLCs). Using the training se- quence (TS), this paper investigates the channel estimation in indoor wireless visible light communications. Based on the propagation and signal modulation characteristics of visible light, a link model for the indoor wireless visible light commu- nications is established. Using the model, three channel estimation methods, i.e., the correlation method, the least square (LS) method and the minimum mean square error (MMSE) method, are proposed. Moreover, the performances of the proposed three methods are evaluated by computer simulation. The results show that the performance of the correlation method is the worst, the LS method is suitable for higher signal to noise ratio (SNR), and the MMSE method obtains the best performance at the expense of highest complexity.
Preamble and pilot symbol design for channel estimation in OFDM systems with null subcarriers
Directory of Open Access Journals (Sweden)
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.
Directory of Open Access Journals (Sweden)
Ko ChiChung
2009-01-01
Full Text Available This paper proposes a turbo joint channel estimation, synchronization, and decoding scheme for coded multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM systems. The effects of carrier frequency offset (CFO, sampling frequency offset (SFO, and channel impulse responses (CIRs on the received samples are analyzed and explored to develop the turbo decoding process and vector recursive least squares (RLSs algorithm for joint CIR, CFO, and SFO tracking. For burst transmission, with initial estimates derived from the preamble, the proposed scheme can operate without the need of pilot tones during the data segment. Simulation results show that the proposed turbo joint channel estimation, synchronization, and decoding scheme offers fast convergence and low mean squared error (MSE performance over quasistatic Rayleigh multipath fading channels. The proposed scheme can be used in a coded MIMO-OFDM transceiver in the presence of multipath fading, carrier frequency offset, and sampling frequency offset to provide a bit error rate (BER performance comparable to that in an ideal case of perfect synchronization and channel estimation over a wide range of SFO values.
Directory of Open Access Journals (Sweden)
2009-03-01
Full Text Available This paper proposes a turbo joint channel estimation, synchronization, and decoding scheme for coded multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM systems. The effects of carrier frequency offset (CFO, sampling frequency offset (SFO, and channel impulse responses (CIRs on the received samples are analyzed and explored to develop the turbo decoding process and vector recursive least squares (RLSs algorithm for joint CIR, CFO, and SFO tracking. For burst transmission, with initial estimates derived from the preamble, the proposed scheme can operate without the need of pilot tones during the data segment. Simulation results show that the proposed turbo joint channel estimation, synchronization, and decoding scheme offers fast convergence and low mean squared error (MSE performance over quasistatic Rayleigh multipath fading channels. The proposed scheme can be used in a coded MIMO-OFDM transceiver in the presence of multipath fading, carrier frequency offset, and sampling frequency offset to provide a bit error rate (BER performance comparable to that in an ideal case of perfect synchronization and channel estimation over a wide range of SFO values.
Directory of Open Access Journals (Sweden)
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.
Directory of Open Access Journals (Sweden)
Zhang Han
2009-01-01
Full Text Available We address the problem of superimposed trainings- (STs- based linearly time-varying (LTV channel estimation and symbol detection for orthogonal frequency-division multiplexing access (OFDMA systems at the uplink receiver. The LTV channel coefficients are modeled by truncated discrete Fourier bases (DFBs. By judiciously designing the superimposed pilot symbols, we estimate the LTV channel transfer functions over the whole frequency band by using a weighted average procedure, thereby providing validity for adaptive resource allocation. We also present a performance analysis of the channel estimation approach to derive a closed-form expression for the channel estimation variances. In addition, an iterative symbol detector is presented to mitigate the superimposed training effects on information sequence recovery. By the iterative mitigation procedure, the demodulator achieves a considerable gain in signal-interference ratio and exhibits a nearly indistinguishable symbol error rate (SER performance from that of frequency-division multiplexed trainings. Compared to existing frequency-division multiplexed training schemes, the proposed algorithm does not entail any additional bandwidth while with the advantage for system adaptive resource allocation.
A Simulation Study on Channel Estimation for MIMO-OFDM Based Beyond 3G Mobile Systems
Institute of Scientific and Technical Information of China (English)
YIN Chang-chuan; ZHAO Xue-yuan; HOU Xiao-lin; YUE Guang-xin
2005-01-01
Multi-Input Multi-Output antennas based Orthogonal Frequency-Division Multiplexing (MIMO-OFDM) has been chosen as the air interface technology for China's beyond 3G Time-Division Duplex (TDD) mobile system in the FuTURE research project. Channel estimation plays a key role on the performance of the MIMO-OFDM receiver. In this paper, we present five channel estimation algorithms and study their performance in a simulated beyond 3G TDD mobile system. Simulation results show that the adaptive 2D-LMS algorithm we proposed recently has the best performance when the signal to noise ratio is lower than 8 dB.
Rank-defective millimeter-wave channel estimation based on subspace-compressive sensing
Directory of Open Access Journals (Sweden)
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.
On the capacity of nakagami-m fading Channels with full channel state information at low SNR
Rezki, Zouheir
2012-06-01
The capacity of flat Rayleigh fading channels with full channel state information (CSI) at the transmitter and at the receiver at asymptotically low SNR has been recently shown to scale essentially as SNR log(1/SNR)}. In this paper, we investigate the Nakagami-m fading channel capacity with full CSI, and show that the capacity of this channel scales essentially as m/ Omega SNR log(1/SNR), where m is the Nakagami-m fading parameter and where Ω is the channel mean-square. We also show that one-bit CSI at the transmitter is enough to achieve this asymptotic capacity using an On-Off power control scheme. Our framework may be seen as a generalization of previous works as it captures the Rayleigh fading channel as a special case by taking m=1. © 2012 IEEE.
Constrained model predictive control, state estimation and coordination
Yan, Jun
guarantee local stability or convergence to a target state. If these conditions are met for all subsystems, then this stability is inherited by the overall system. For the case when each subsystem suffers from disturbances in the dynamics, own self-measurement noises, and quantization errors on neighbors' information due to the finite-bit-rate channels, the constrained MPC strategy developed in Part (i) is appropriate to apply. In Part (iii), we discuss the local predictor design and bandwidth assignment problem in a coordinated vehicle formation context. The MPC controller used in Part (ii) relates the formation control performance and the information quality in the way that large standoff implies conservative performance. We first develop an LMI (Linear Matrix Inequality) formulation for cross-estimator design in a simple two-vehicle scenario with non-standard information: one vehicle does not have access to the other's exact control value applied at each sampling time, but to its known, pre-computed, coupling linear feedback control law. Then a similar LMI problem is formulated for the bandwidth assignment problem that minimizes the total number of bits by adjusting the prediction gain matrices and the number of bits assigned to each variable. (Abstract shortened by UMI.)
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
A novel discrete-time digital inter-symbol interference (ISI) channel blind estimation sub-optimal algorithm is proposed. This algorithm reduces the complexity of the optimal maximum likelihood sequence estimation(MLSE) considerably based on the one-step branch transition rules in trellises, and is suitable for the estimation of the channels with small lengths of ISI.
Stonestrom, David A.; Prudic, David E.; Laczniak, Randell J.; Akstin, Katherine C.; Boyd, Robert A.; Henkelman, Katherine K.
2003-01-01
The presence and approximate rates of deep percolation beneath areas of native vegetation, irrigated fields, and the Amargosa-River channel in the Amargosa Desert of southern Nevada were evaluated using the chloride mass-balance method and inferred downward velocities of chloride and nitrate peaks. Estimates of deep-percolation rates in the Amargosa Desert are needed for the analysis of regional ground-water flow and transport. An understanding of regional flow patterns is important because ground water originating on the Nevada Test Site may pass through the area before discharging from springs at lower elevations in the Amargosa Desert and in Death Valley. Nine boreholes 10 to 16 meters deep were cored nearly continuously using a hollow-stem auger designed for gravelly sediments. Two boreholes were drilled in each of three irrigated fields in the Amargosa-Farms area, two in the Amargosa-River channel, and one in an undisturbed area of native vegetation. Data from previously cored boreholes beneath undisturbed, native vegetation were compared with the new data to further assess deep percolation under current climatic conditions and provide information on spatial variability. The profiles beneath native vegetation were characterized by large amounts of accumulated chloride just below the root zone with almost no further accumulation at greater depths. This pattern is typical of profiles beneath interfluvial areas in arid alluvial basins of the southwestern United States, where salts have been accumulating since the end of the Pleistocene. The profiles beneath irrigated fields and the Amargosa-River channel contained more than twice the volume of water compared to profiles beneath native vegetation, consistent with active deep percolation beneath these sites. Chloride profiles beneath two older fields (cultivated since the 1960?s) as well as the upstream Amargosa-River site were indicative of long-term, quasi-steady deep percolation. Chloride profiles beneath the
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.
New developments in state estimation for Nonlinear Systems
DEFF Research Database (Denmark)
Nørgård, Peter Magnus; Poulsen, Niels Kjølstad; Ravn, Ole
2000-01-01
Based on an interpolation formula, accurate state estimators for nonlinear systems can be derived. The estimators do not require derivative information which makes them simple to implement.; State estimators for nonlinear systems are derived based on polynomial approximations obtained with a multi......-dimensional interpolation formula. It is shown that under certain assumptions the estimators perform better than estimators based on Taylor approximations. Nevertheless, the implementation is significantly simpler as no derivatives are required. Thus, it is believed that the new state estimators can replace well...
On Frequency Offset Estimation Using the iNET Preamble in Frequency Selective Fading Channels
2014-03-01
ASM fields; (bottom) the relationship between the indexes of the received samples r(n), the signal samples s(n), the preamble samples p (n) and the short...frequency offset estimators for SOQPSK-TG equipped with the iNET preamble and operating in ISI channels. Four of the five estimators exam - ined here are...sync marker ( ASM ), and data bits (an LDPC codeword). The availability of a preamble introduces the possibility of data-aided synchro- nization in
Sparsity-constraint LMS Algorithms for Time-varying UWB Channel Estimation
Directory of Open Access Journals (Sweden)
Solomon Nunoo
2014-12-01
Full Text Available Sparsity constraint channel estimation using compressive sensing approach has gained widespread interest in recent times. Mostly, the approach utilizes either the l1-norm or l0-norm relaxation to improve the performance of LMS-type algorithms. In this study, we present the adaptive channel estimation of time-varying ultra wideband channels, which have shown to be sparse, in an indoor environment using sparsity-constraint LMS and NLMS algorithms for different sparsity measures. For a less sparse CIR, higher weightings are allocated to the sparse penalty term. Simulation results show improved performance of the sparsity-constraint algorithms in terms of convergence speed and mean square error performance.
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.
New developments in state estimation for Nonlinear Systems
DEFF Research Database (Denmark)
Nørgård, Peter Magnus; Poulsen, Niels Kjølstad; Ravn, Ole
2000-01-01
Based on an interpolation formula, accurate state estimators for nonlinear systems can be derived. The estimators do not require derivative information which makes them simple to implement.; State estimators for nonlinear systems are derived based on polynomial approximations obtained with a multi...
Optimal State Estimation of Pure Qubits on Circles
Institute of Scientific and Technical Information of China (English)
A. Ugulava; ZHANG Li-Hua; L. Chotorlishvili; SONG Wei; V. Skrinnikov; CAO Zhuo-Liang; G. Mchedlishvili
2008-01-01
We consider the problem of state estimation of qubits chosen from circles. It is shown that any qubit encoded in pairs chosen from a fixed circle parallel to the x-y equator with different phases contains the same information. We also investigate the problem of state estimation of qubits from three circles. The optimal estimation fidelity is derived.
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.
Decentralized estimation of sensor systematic error andtarget state vector
Institute of Scientific and Technical Information of China (English)
贺明科; 王正明; 朱炬波
2003-01-01
An accurate estimation of the sensor systematic error is significant for improving the performance of target tracking system. The existing methods usually append the bias states directly to the variable states to form augmented state vectors and utilize the conventional Kalman estimator to achieve state vectors estimate. So doing is expensive in computation, and much work is devoted to decoupling variable states and systematic error. But the decentralied estimation of systematic errors and reduction of the amount of computation as well as decentralied track fusion are far from being realized. This paper addresses distributed track fusion problem in multi-sensor tracking system in the presence of sensor bias. By this method, variable states and systematic error is decoupled. Decentralized systematic error estimation and track fusion are achieved. Simulation results verify that this method can get accurate estimation of systematic error and state vector.
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...
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...
Message-Passing Algorithms for Channel Estimation and Decoding Using Approximate Inference
DEFF Research Database (Denmark)
Badiu, Mihai Alin; Kirkelund, Gunvor Elisabeth; Manchón, Carles Navarro
2012-01-01
We design iterative receiver schemes for a generic communication system by treating channel estimation and information decoding as an inference problem in graphical models. We introduce a recently proposed inference framework that combines belief propagation (BP) and the mean field (MF) approxima...
2005-09-01
Sandell , S. K. Wilson, and P. O. Börjesson, “On Channel Estimation in OFDM Systems,” in Proc. 45th IEEE Vehicular Technology Conf., pp. 815-819...Transactions on Wireless Communications, Vol. 1, No. 1, pp. 67-75, January 2002. [10] Michel C. Jeruchim, Philip Balaban and K. Sam Shanmugan, Simulation
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....
Performance Limits of Energy Harvesting Communications under Imperfect Channel State Information
Zenaidi, Mohamed Ridah
2015-01-07
In energy harvesting communications, the transmitters have to adapt transmission to availability of energy harvested during the course of communication. The performance of the transmission depends on the channel conditions which vary randomly due to mobility and environmental changes. In this work, we consider the problem of power allocation taking into account the energy arrivals over time and the degree of channel state information (CSI) available at the transmitter, in order to maximize the throughput. In this work, the CSI at the transmitter is not perfect and may include estimation errors. We solve this problem with respect to the causality and energy storage constraints. We determine the optimal offline policy in the case where the channel is assumed to be perfectly known at the receiver. Different cases of CSI availability are studied for the transmitter. We obtain the power policy when the transmitter has either perfect CSI or no CSI. We also investigate of utmost interest the case of fading channels with imperfect CSI. Furthermore, we analyze the asymptotic average throughput in a system where the average recharge rate goes asymptotically to zero and when it is very high.
Vision Aided State Estimation for Helicopter Slung Load System
DEFF Research Database (Denmark)
Bisgaard, Morten; Bendtsen, Jan Dimon; la Cour-Harbo, Anders
2007-01-01
This paper presents the design and verification of a state estimator for a helicopter based slung load system. The estimator is designed to augment the IMU driven estimator found in many helicopter UAV s and uses vision based updates only. The process model used for the estimator is a simple 4 st...
Optimal state estimation for d-dimensional quantum systems
Bruss, D
1999-01-01
We establish a connection between optimal quantum cloning and optimal state estimation for d-dimensional quantum systems. In this way we derive an upper limit on the fidelity of state estimation for d-dimensional pure quantum states and, furthermore, for generalized inputs supported on the symmetric subspace.
Hydraulic flow through a channel contraction: multiple steady states
Akers, B.; Bokhove, O.
2008-01-01
We have investigated shallow water flows through a channel with a contraction by experimental and theoretical means. The horizontal channel consists of a sluice gate and an upstream channel of constant width $b_0$ ending in a linear contraction of minimum width $b_c$. Experimentally, we observe upst
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.
Performance Analysis of LS and LMMSE Channel Estimation Techniques for LTE Downlink Systems
Khlifi, Abdelhakim; 10.5121/ijwmn.2011.3511
2011-01-01
The main purpose of this paper is to study the performance of two linear channel estimators for LTE Downlink systems, the Least Square Error (LSE) and the Linear Minimum Mean Square Error (LMMSE). As LTE is a MIMO-OFDM based system, a cyclic prefix is inserted at the beginning of each transmitted OFDM symbol in order to completely suppress both inter-carrier interference (ICI) and inter-symbol interference (ISI). Usually, the cyclic prefix is equal to or longer than the channel length but in some cases and because of some unforeseen channel behaviour, the cyclic prefix can be shorter. Therefore, we propose to study the performance of the two linear estimators under the effect of the channel length. Computer simulations show that, in the case where the cyclic prefix is equal to or longer than the channel length,LMMSE performs better than LSE but at the cost of computational complexity.In the other case, LMMSE continue to improve its performance only for low SNR values but it degrades for high SNR values in whi...
Accurate quantum state estimation via "Keeping the experimentalist honest"
Blume-Kohout, R; Blume-Kohout, Robin; Hayden, Patrick
2006-01-01
In this article, we derive a unique procedure for quantum state estimation from a simple, self-evident principle: an experimentalist's estimate of the quantum state generated by an apparatus should be constrained by honesty. A skeptical observer should subject the estimate to a test that guarantees that a self-interested experimentalist will report the true state as accurately as possible. We also find a non-asymptotic, operational interpretation of the quantum relative entropy function.
Mathematical model of transmission network static state estimation
Directory of Open Access Journals (Sweden)
Ivanov Aleksandar
2012-01-01
Full Text Available In this paper the characteristics and capabilities of the power transmission network static state estimator are presented. The solving process of the mathematical model containing the measurement errors and their processing is developed. To evaluate difference between the general model of state estimation and the fast decoupled state estimation model, the both models are applied to an example, and so derived results are compared.
On Comparison of DFT-Based and DCT-Based Channel Estimation for OFDM System
Directory of Open Access Journals (Sweden)
Saqib Saleem
2011-05-01
Full Text Available For high data rate communication with the required Quality of Service (QoS in 3G and 4G systems, Orthogonal Frequency Division Multiplexing (OFDM is proposed, which is capable to resist the channel impairments caused by high mobility conditions, by dividing the frequency-selective fading channel into narrowband flat fading channels. In this paper two time-domain channel estimation techniques, Discrete Fourier Transform (DFT and Discrete Cosine Transform (DCT, are compared based on the time-domain channel impulse response (CIR energy characteristics and they have less complexity and efficient performance than Linear Minimum Mean Square Error (LMMSE and Least Square Error (LSE. The effect of power limitation in terms of SNR and the number of multipaths for a wireless channel is determined to compare these transform approaches. Two well known performance criteria: Mean Square Error (MSE and Symbol Error Rate (SER are used for comparison by using Monte Carlo Simulations for Quadrature Phase Shift Keying (QPSK modulation.
OFDM通信系统信道估计的新方法%New method for OFDM communication channel estimation
Institute of Scientific and Technical Information of China (English)
武广; 端木春江; 赵伟
2015-01-01
正交频分复用(OFDM)技术是现在4G通信和即将到来的5G中的关键技术。对其信道进行估计的准确性直接影响到系统的误码率(bit error rate BER)。文章提出了一种新自适应分块错位和周期性的导频插入模式。此模式能更准确地估计OFDM的各子信道状况。其利用线性插值法估计出未插入导频信号的子信道上的频率响应。仿真结果显示，所提出的方法能在同样的误码率要求时，大幅度地减少发送端的发送功率（信噪比增益在4dB以上）。%The OFDM is the key technology in the 4G and the upcoming 5G communication systems. The accurate estimation of the channel conditions has a direct influence on the bit error rate of the systems. This paper proposes a new adaptive and periodic pilot sub-channel insertion method. This method can estimate the sub-channels' state of the OFDM in a more accurate way, and the frequency responses of the non-pilot sub-channels are estimated by the method of linear interpolation. Simulation results have demonstrated that the proposed method can greatly reduce the transmission power under the same bit error rate requirement(The SNR gain is more than 4dB).
BLIND CHANNEL AND SYMBOL JOINT ESTIMATION IN COOPERATIVE MIMO FOR WIRELESS SENSOR NETWORK
Institute of Scientific and Technical Information of China (English)
Yan Zhenya; Zheng Baoyu
2008-01-01
In this paper, application of Sequential Quasi Monte Carlo (SQMC) to blind channel and symbol joint estimation in cooperative Multiple-Input Multiple-Output (MIMO) system is proposed, which does not need to transmit training symbol and can save the power and channel bandwidth. Additionally, an improved version of SQMC algorithm by taking advantage of current received signal is discussed. Simulation results show that the SQMC method outperforms the Sequential Monte Carlo (SMC) methods, and the incorporation of current received signal improves the performance of the SQMC obviously.
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.
Rezki, Zouheir
2014-01-01
We study the throughput capacity region of the Gaussian multi-access (MAC) fading channel with perfect channel state information (CSI) at the receiver and at the transmitters, at low power regime. We show that it has a multidimensional rectangle structure and thus is simply characterized by single user capacity points.More specifically, we show that at low power regime, the boundary surface of the capacity region shrinks to a single point corresponding to the sum rate maximizer and that the coordinates of this point coincide with single user capacity bounds. Inspired from this result, we propose an on-off scheme, compute its achievable rate, and show that this scheme achieves single user capacity bounds of the MAC channel for a wide class of fading channels at asymptotically low power regime. We argue that this class of fading encompasses all known wireless channels for which the capacity region of the MAC channel has even a simpler expression in terms of users\\' average power constraints only. Using the duality of Gaussian MAC and broadcast channels (BC), we deduce a simple characterization of the BC capacity region at low power regime and show that for a class of fading channels (including Rayleigh fading), time-sharing is asymptotically optimal. © 2014 IEEE.
Directory of Open Access Journals (Sweden)
Jan Bajcsy
2005-07-01
Full Text Available This paper considers the problem of uplink transmission over multiple-input multiple-output (MIMO channels affected by slow frequency-nonselective uncorrelated and correlated Rayleigh fading. We consider the case when channel state information, corrupted by estimation errors, is available at the receiver only. In this setting, we generalize the derivation of our previously proposed linear-complexity MIMO signal detector and derive closed-form expressions for the distribution of its soft outputs and the approximate symbol error probability. Based on this soft decision detector, we consider a turbo-coded MIMO uplink architecture with iterative processing, which enables performance within 1.6 to 2.8 dB of the ergodic capacity limit and outperforms the T-BLAST (turbo-Bell Laboratories layered space-time system by about 10 dB at bit error rates of 10Ã¢ÂˆÂ’5. The presented results illustrate that this linear-complexity MIMO signal detector is highly robust to channel estimation errors.
Enhanced signal-to-noise ratio estimation for tropospheric lidar channels
Saeed, Umar; Barragan, Rubén; Rocadenbosch, Francesc
2016-04-01
This works combines the fields of tropospheric lidar remote sensing and signal processing to come up with a robust signal-to-noise ratio (SNR) estimator apt for elastic and Raman channels. The estimator uses a combined low-pass / high-pass filtering scheme along with high-order statistics (kurtosis) to estimate the range-dependent signal and noise components with minimum distortion. While low-pass filtering is used to estimate the range-dependent signal level, high-pass filtering is used to estimate the noise component with minimum distortion. From this noise component estimate (a random realization) the noise level (e.g., variance) is computed as a function of range along with error bars. The minimum-distortion specification determines the optimal cut-off de-noising filter frequency and, in turn, the spatial resolution of the SNR estimation algorithm. The proposed SNR estimator has a much wider dynamic range of operation than well-known classic SNR estimation techniques, in which the SNR is directly computed from the mean and standard deviation of the measured noise-corrupted lidar signal along successive adjacent range intervals and where the spatial resolution is just a subjective input from the user's side. Aligned with ACTRIS (http://www.actris.net) WP on "optimization of the processing chain and Single-Calculus Chain (SCC)" the proposed topic is of application to assess lidar reception channel performance and confidence on the detected atmospheric morphology (e.g., cloud base and top, and location of aerosol layers). The SNR algorithm is tested against the classic SNR estimation approach using test-bed synthetic lidar data modelling the UPC multi-spectral lidar. Towards this end, the Nd:YAG UPC elastic-Raman lidar provides aerosol channels in the near-infrared (1064 nm), visible (532 nm), and ultra-violet (355 nm) as well as aerosol Raman and water-vapour channels with fairly varying SNR levels. The SNR estimator is also used to compare SNR levels between
Directory of Open Access Journals (Sweden)
Jong-Seob Baek
2008-01-01
Full Text Available This paper presents a new block iterative/adaptive frequency-domain channel estimation scheme, in which a channel frequency response (CFR is estimated iteratively by the proposed weighted element-wise block adaptive frequency-domain channel estimation (WEB-CE scheme using the soft information obtained by a soft-input soft-output (SISO decoder. In the WEB-CE, an equalizer coefficient is calculated by minimizing a weighted conditional squared-norm of the a posteriori error vector with respect to its correction term. Simulation results verify the superiority of the WEB-CE in a time-varying typical urban (TU channel.
Energy Technology Data Exchange (ETDEWEB)
Baumgartner, S. [Axpo AG, Parkstrasse 23, CH-5401 Baden (Switzerland); Bieli, R. [Kernkraftwerk Leibstadt AG, CH-5325 Leibstadt (Switzerland); Bergmann, U. C. [Westinghouse Electric Sweden AB, SE-721 63 Vaesteraas (Sweden)
2012-07-01
An overview is given of existing CPR design criteria and the methods used in BWR reload analysis to evaluate the impact of channel bow on CPR margins. Potential weaknesses in today's methodologies are discussed. Westinghouse in collaboration with KKL and Axpo - operator and owner of the Leibstadt NPP - has developed an optimized CPR methodology based on a new criterion to protect against dryout during normal operation and with a more rigorous treatment of channel bow. The new steady-state criterion is expressed in terms of an upper limit of 0.01 for the dryout failure probability per year. This is considered a meaningful and appropriate criterion that can be directly related to the probabilistic criteria set-up for the analyses of Anticipated Operation Occurrences (AOOs) and accidents. In the Monte Carlo approach a statistical modeling of channel bow and an accurate evaluation of CPR response functions allow the associated CPR penalties to be included directly in the plant SLMCPR and OLMCPR in a best-estimate manner. In this way, the treatment of channel bow is equivalent to all other uncertainties affecting CPR. Emphasis is put on quantifying the statistical distribution of channel bow throughout the core using measurement data. The optimized CPR methodology has been implemented in the Westinghouse Monte Carlo code, McSLAP. The methodology improves the quality of dryout safety assessments by supplying more valuable information and better control of conservatisms in establishing operational limits for CPR. The methodology is demonstrated with application examples from the introduction at KKL. (authors)
State estimation for a hexapod robot
CSIR Research Space (South Africa)
Lubbe, Estelle
2015-09-01
Full Text Available on a quadruped. The EKF fuses the kinematic model with on-board IMU measurements to estimate the pose of the robot. The methodology was tested with experiments using a physical hexapod robot and validated with independent ground truth measurements....
Improving quantum state estimation with mutually unbiased bases.
Adamson, R B A; Steinberg, A M
2010-07-16
When used in quantum state estimation, projections onto mutually unbiased bases have the ability to maximize information extraction per measurement and to minimize redundancy. We present the first experimental demonstration of quantum state tomography of two-qubit polarization states to take advantage of mutually unbiased bases. We demonstrate improved state estimation as compared to standard measurement strategies and discuss how this can be understood from the structure of the measurements we use. We experimentally compared our method to the standard state estimation method for three different states and observe that the infidelity was up to 1.84 ± 0.06 times lower by using our technique than it was by using standard state estimation methods.
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.
Cognitive relaying and power allocation under channel state uncertainties
Pandarakkottilil, Ubaidulla
2013-04-01
In this paper, we present robust joint relay precoder designs and transceiver power allocations for a cognitive radio network under imperfect channel state information (CSI). The secondary (or cognitive) network consists of a pair of single-antenna transceiver nodes and a non-regenerative two-way relay with multiple antennas which aids the communication process between the transceiver pair. The secondary nodes share the spectrum with a licensed primary user (PU) while guaranteeing that the interference to the PU receiver is maintained below a specified threshold. We consider two robust designs: the first is based on the minimization of the total transmit power of the secondary relay node required to provide the minimum quality of service, measured in terms of mean-square error (MSE) of the transceiver nodes, and the second is based on the minimization of the sum-MSE of the transceiver nodes. The robust designs are based on worst-case optimization and take into account known parameters of the error in the CSI to render the performance immune to the presence of errors in the CSI. Though the original problem is non-convex, we show that the proposed designs can be reformulated as tractable convex optimization problems that can be solved efficiently. We illustrate the performance of the proposed designs through some selected numerical simulations. © 2013 IEEE.
Estimating equations for biomarker based exposure estimation under non-steady-state conditions.
Bartell, Scott M; Johnson, Wesley O
2011-06-13
Unrealistic steady-state assumptions are often used to estimate toxicant exposure rates from biomarkers. A biomarker may instead be modeled as a weighted sum of historical time-varying exposures. Estimating equations are derived for a zero-inflated gamma distribution for daily exposures with a known exposure frequency. Simulation studies suggest that the estimating equations can provide accurate estimates of exposure magnitude at any reasonable sample size, and reasonable estimates of the exposure variance at larger sample sizes.
Lagrangian Multi-Class Traffic State Estimation
Yuan, Y.
2013-01-01
Road traffic is important to everybody in the world. People travel and commute everyday. For those who travel by cars (or other types of road vehicles), traffic congestion is a daily experience. One essential goal of traffic researchers is to reduce traffic congestion and to improve the whole traffic system operation and the environment. To achieve this goal, we have to first understand prevailing traffic situations, then perform pro-active traffic control and management. The estimation of tr...
Artificial Neural Network Based State Estimators Integrated into Kalmtool
DEFF Research Database (Denmark)
Bayramoglu, Enis; Ravn, Ole; Poulsen, Niels Kjølstad
2012-01-01
In this paper we present a toolbox enabling easy evaluation and comparison of dierent ltering algorithms. The toolbox is called Kalmtool and is a set of MATLAB tools for state estimation of nonlinear systems. The toolbox now contains functions for Articial Neural Network Based State Estimation...
Probabilistic approach to estimating the effects of channel reaches on flood frequencies
Guo, Yiping; Hansen, David; Li, Chuan
2009-08-01
A host of physical parameters and characteristics of catchments and channel reaches are normally needed in watershed planning and stormwater management studies. Some of these are also design variables, such as channel cross-section size, shape, roughness, and (to a lesser extent) bed slope. Conventional channel routing techniques employ continuity and some form of the momentum equation to determine the downstream impacts of individual flood events. With the introduction of the concept of storage-induced delay time, a probabilistic approach is developed wherein the role of a given channel reach on the frequency distribution of floods from the catchment upstream can be directly determined. The approach uses the same kinds of channel-reach parameters as are typically used by many conventional flood routing algorithms. Its physically based nature makes it suitable for watershed planning and stormwater management studies wherein little or no flow data are available for parameter estimation or flow frequency analysis. The validity of this probabilistic approach is demonstrated by comparing its outcomes with the results of a suite of conventional continuous simulations using rainfall data from Halifax, Canada.
Evaluation of Preamble Based Channel Estimation for MIMO-FBMC Systems
Institute of Scientific and Technical Information of China (English)
Sohail Taheri; Mir Ghoraishi; XIAO Pei; CAO Aijun; GAO Yonghong
2016-01-01
Filter⁃bank multicarrier (FBMC) with offset quadrature amplitude modulation (OQAM) is a candidate waveform for future wireless communications due to its advantages over orthogonal frequency division multiplexing (OFDM) systems. However, because of or⁃thogonality in real field and the presence of imaginary intrinsic interference, channel estimation in FBMC is not as straightforward as OFDM systems especially in multiple antenna scenarios. In this paper, we propose a channel estimation method which employs intrinsic interference cancellation at the transmitter side. The simulation results show that this method has less pilot overhead, less peak to average power ratio (PAPR), better bit error rate (BER), and better mean square error (MSE) performance compared to the well⁃known intrinsic approximation methods (IAM).
A Modified Nonparametric Message Passing Algorithm for Soft Iterative Channel Estimation
Directory of Open Access Journals (Sweden)
Linlin Duan
2013-08-01
Full Text Available Based on the factor graph framework, we derived a Modified Nonparametric Message Passing Algorithm (MNMPA for soft iterative channel estimation in a Low Density Parity-Check (LDPC coded Bit-Interleaved Coded Modulation (BICM system. The algorithm combines ideas from Particle Filtering (PF with popular factor graph techniques. A Markov Chain Monte Carlo (MCMC move step is added after typical sequential Important Sampling (SIS -resampling to prevent particle impoverishment and to improve channel estimation precision. To reduce complexity, a new max-sum rule for updating particle based messages is reformulated and two proper update schedules are designed. Simulation results illustrate the effectiveness of MNMPA and its comparison with other sum-product algorithms in a Gaussian or non-Gaussian noise environment. We also studied the effect of the particle number, pilot symbol spacing and different schedules on BER performance.
Jin, T.; Qiu, X.; Hu, D.; Ding, C.
2017-09-01
Multichannel synthetic aperture radar (SAR) is a significant breakthrough to the inherent limitation between high-resolution and wide-swath (HRWS) faced with conventional SAR. Error estimation and unambiguous reconstruction are two crucial techniques for obtaining high-quality imagery. This paper demonstrates the experimental results of the two techniques for Chinese first dualchannel spaceborne SAR imaging. The model of Chinese Gaofen-3 dual-channel mode is established and the mechanism of channel mismatches is first discussed. Particularly, we propose a digital beamforming (DBF) process composed of the subspace-based error estimation algorithm and the reconstruction algorithm before imaging. The results exhibit the effective suppression of azimuth ambiguities with the proposed DBF process, and indicate the feasibility of this technique for future HRWS SAR systems.
Advances in Derivative-Free State Estimation for Nonlinear Systems
DEFF Research Database (Denmark)
Nørgaard, Magnus; Poulsen, Niels Kjølstad; Ravn, Ole
In this paper we show that it involves considerable advantages to use polynomial approximations obtained with an interpolation formula for derivation of state estimators for nonlinear systems. The estimators become more accurate than estimators based on Taylor approximations, and yet the implemen......In this paper we show that it involves considerable advantages to use polynomial approximations obtained with an interpolation formula for derivation of state estimators for nonlinear systems. The estimators become more accurate than estimators based on Taylor approximations, and yet...... the implementation is significantly simpler as no derivatives are required. Thus, it is believed that estimators derived in this way can replace well-known filters, such as the extended Kalman filter (EKF) and its higher order relatives, in most practical applications. In addition to proposing a new set of state...
Efficient Quantum State Estimation with Over-complete Tomography
Zhang, Chi; Xiang, Guo-Yong; Zhang, Yong-Sheng; Li, Chuan-Feng; Guo, Guang-Can
2011-01-01
It is widely accepted that the selection of measurement bases can affect the efficiency of quantum state estimation methods, precision of estimating an unknown state can be improved significantly by simply introduce a set of symmetrical measurement bases. Here we compare the efficiencies of estimations with different numbers of measurement bases by numerical simulation and experiment in optical system. The advantages of using a complete set of symmetrical measurement bases are illustrated mor...
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.
An Off-Grid Turbo Channel Estimation Algorithm for Millimeter Wave Communications.
Han, Lingyi; Peng, Yuexing; Wang, Peng; Li, Yonghui
2016-09-22
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 detection
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.
Methods for accurate estimation of net discharge in a tidal channel
Simpson, M.R.; Bland, R.
2000-01-01
Accurate estimates of net residual discharge in tidally affected rivers and estuaries are possible because of recently developed ultrasonic discharge measurement techniques. Previous discharge estimates using conventional mechanical current meters and methods based on stage/discharge relations or water slope measurements often yielded errors that were as great as or greater than the computed residual discharge. Ultrasonic measurement methods consist of: 1) the use of ultrasonic instruments for the measurement of a representative 'index' velocity used for in situ estimation of mean water velocity and 2) the use of the acoustic Doppler current discharge measurement system to calibrate the index velocity measurement data. Methods used to calibrate (rate) the index velocity to the channel velocity measured using the Acoustic Doppler Current Profiler are the most critical factors affecting the accuracy of net discharge estimation. The index velocity first must be related to mean channel velocity and then used to calculate instantaneous channel discharge. Finally, discharge is low-pass filtered to remove the effects of the tides. An ultrasonic velocity meter discharge-measurement site in a tidally affected region of the Sacramento-San Joaquin Rivers was used to study the accuracy of the index velocity calibration procedure. Calibration data consisting of ultrasonic velocity meter index velocity and concurrent acoustic Doppler discharge measurement data were collected during three time periods. Two sets of data were collected during a spring tide (monthly maximum tidal current) and one of data collected during a neap tide (monthly minimum tidal current). The relative magnitude of instrumental errors, acoustic Doppler discharge measurement errors, and calibration errors were evaluated. Calibration error was found to be the most significant source of error in estimating net discharge. Using a comprehensive calibration method, net discharge estimates developed from the three
Ergodic Capacity of Cognitive Radio Under Imperfect Channel-State Information
Rezki, Zouheir
2012-09-08
A spectrum-sharing communication system where the secondary user is aware of the instantaneous channel-state information (CSI) of the secondary link but knows only the statistics and an estimated version of the secondary transmitter-primary receiver link is investigated. The optimum power profile and the ergodic capacity of the secondary link are derived for general fading channels [with a continuous probability density function (pdf)] under the average and peak transmit power constraints and with respect to the following two different interference constraints: 1) an interference outage constraint and 2) a signal-to-interference outage constraint. When applied to Rayleigh fading channels, our results show, for example, that the interference constraint is harmful at the high-power regime, because the capacity does not increase with the power, whereas at the low-power regime, it has a marginal impact and no-interference performance, which corresponds to the ergodic capacity under average or peak transmit power constraint in the absence of the primary user, may be achieved. © 2012 IEEE.
Benkhelifa, Fatma
2013-04-01
In this letter, we study the ergodic capacity of a maximum ratio combining (MRC) Rician fading channel with full channel state information (CSI) at the transmitter and at the receiver. We focus on the low Signal-to-Noise Ratio (SNR) regime and we show that the capacity scales as L ΩK+L SNRx log(1SNR), where Ω is the expected channel gain per branch, K is the Rician fading factor, and L is the number of diversity branches. We show that one-bit CSI feedback at the transmitter is enough to achieve this capacity using an on-off power control scheme. Our framework can be seen as a generalization of recently established results regarding the fading-channels capacity characterization in the low-SNR regime. © 2012 IEEE.
Directory of Open Access Journals (Sweden)
Vandendorpe Luc
2010-01-01
Full Text Available The problem of jointly optimizing the source precoder, relay transceiver, and destination equalizer has been considered in this paper for a multiple-input-multiple-output (MIMO amplify-and-forward (AF relay channel, where the channel estimates of all links are assumed to be imperfect. The considered joint optimization problem is nonconvex and does not offer closed-form solutions. However, it has been shown that the optimization of one variable when others are fixed is a convex optimization problem which can be efficiently solved using interior-point algorithms. In this context, an iterative technique with the guaranteed convergence has been proposed for the AF MIMO relay channel that includes the direct link. It has been also shown that, for the double-hop relay case without the receive-side antenna correlations in each hop, the global optimality can be confirmed since the structures of the source precoder, relay transceiver, and destination equalizer have closed forms and the remaining joint power allocation can be solved using Geometric Programming (GP technique under high signal-to-noise ratio (SNR approximation. In the latter case, the performance of the iterative technique and the GP method has been compared with simulations to ensure that the iterative approach gives reasonably good solutions with an acceptable complexity. Moreover, simulation results verify the robustness of the proposed design when compared to the nonrobust design that assumes estimated channels as actual channels.
Chalise, Batu K.; Vandendorpe, Luc
2010-12-01
The problem of jointly optimizing the source precoder, relay transceiver, and destination equalizer has been considered in this paper for a multiple-input-multiple-output (MIMO) amplify-and-forward (AF) relay channel, where the channel estimates of all links are assumed to be imperfect. The considered joint optimization problem is nonconvex and does not offer closed-form solutions. However, it has been shown that the optimization of one variable when others are fixed is a convex optimization problem which can be efficiently solved using interior-point algorithms. In this context, an iterative technique with the guaranteed convergence has been proposed for the AF MIMO relay channel that includes the direct link. It has been also shown that, for the double-hop relay case without the receive-side antenna correlations in each hop, the global optimality can be confirmed since the structures of the source precoder, relay transceiver, and destination equalizer have closed forms and the remaining joint power allocation can be solved using Geometric Programming (GP) technique under high signal-to-noise ratio (SNR) approximation. In the latter case, the performance of the iterative technique and the GP method has been compared with simulations to ensure that the iterative approach gives reasonably good solutions with an acceptable complexity. Moreover, simulation results verify the robustness of the proposed design when compared to the nonrobust design that assumes estimated channels as actual channels.
Channel Capacity Bounds in the Presence of Quantized Channel State Information
Directory of Open Access Journals (Sweden)
Makki Behrooz
2010-01-01
Full Text Available The goal of this paper is to investigate the effect of channel side information on increasing the achievable rates of continuous power-limited non-Gaussian channels. We focus on the case where (1 there is imperfect channel quality information available to the transmitter and the receiver and (2 while the channel gain is continuously varying, there are few cross-region changes, and the noise characteristics remain in each detection region for a long time. The results are presented for two scenarios, namely, reliable and unreliable region detection. Considering short- and long-term power constraints, the capacity bounds are found for log-normal and two different Nakagami-based channel distributions, and for both Max-Lloyd and equal probability quantization approaches. Then, the optimal gain partitioning approach, maximizing the achievable rates, is determined. Finally, general equations for the channel capacity bounds and optimal channel partitioning in the case of unreliable region detection are presented. Interestingly, the results show that, for high SNR's, it is possible to determine a power-independent optimal gain partitioning approach maximizing the capacity lower bound which, in both scenarios, is identical for both short- and long-term power constraints.
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.
Time-domain training sequences design for MIMO OFDM channel estimation
Institute of Scientific and Technical Information of China (English)
Zhen LU; Jian-hua GE
2008-01-01
This paper describes a Least Squares (LS) channel estimation scheme for MIMO OFDM systems based on time-domain training sequence. We first compute the minimum mean square error (MSE) of the LS channel estimation, and then derive the optimal criteria of the training sequence with respect to the minimum MSE. It is shown that optimal time-domain training sequence should satisfy two criteria. First, the autocorrelation of the sequence transmitted from the same antenna is an impulse function in a region longer than the channel maximum delay. Second, the cross-correlation between sequences transmitted from different antennas is zero in this region. Simulation results show that the estimator using optimal time-domain training sequences has better performance than that using optimal frequency training sequence at low signal-to-noise ratio (SNR). To reduce the training overhead, a suboptimal training sequence is also proposed. Comparing with optimal training sequence, it has low computation complexity and high transmission efficiency at the expense of little performance degradation.
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.
Lin, Bangjiang; Li, Yiwei; Zhang, Shihao; Tang, Xuan
2015-10-01
Weighted interframe averaging (WIFA)-based channel estimation (CE) is presented for orthogonal frequency division multiplexing passive optical network (OFDM-PON), in which the CE results of the adjacent frames are directly averaged to increase the estimation accuracy. The effectiveness of WIFA combined with conventional least square, intrasymbol frequency-domain averaging, and minimum mean square error, respectively, is demonstrated through 26.7-km standard single-mode fiber transmission. The experimental results show that the WIFA method with low complexity can significantly enhance transmission performance of OFDM-PON.
Gaussian matrix-product states for coding in bosonic communication channels
Schäfer, Joachim; Karpov, Evgueni; Cerf, Nicolas J.
2012-01-01
The communication capacity of Gaussian bosonic channels with memory has recently attracted much interest. Here, we investigate a method to prepare the multimode entangled input symbol states for encoding classical information into these channels. In particular, we study the usefulness of a Gaussian matrix-product state (GMPS) as an input symbol state, which can be sequentially generated although it remains heavily entangled for an arbitrary number of modes. We show that the GMPS can achieve more than 99.9% of the Gaussian capacity for Gaussian bosonic memory channels with a Markovian or non-Markovian correlated noise model in a large range of noise correlation strengths. Furthermore, we present a noise class for which the GMPS is the exact optimal input symbol state of the corresponding channel. Since GMPS are ground states of particular quadratic Hamiltonians, our results suggest a possible link between the theory of quantum communication channels and quantum many-body physics.
Distributed SNR Estimation using Constant Modulus Signaling over Gaussian Multiple-Access Channels
Banavar, Mahesh K; Spanias, Andreas
2011-01-01
A sensor network is used for distributed joint mean and variance estimation, in a single time snapshot. Sensors observe a signal embedded in noise, which are phase modulated using a constant-modulus scheme and transmitted over a Gaussian multiple-access channel to a fusion center, where the mean and variance are estimated jointly, using an asymptotically minimum-variance estimator, which is shown to decouple into simple individual estimators of the mean and the variance. The constant-modulus phase modulation scheme ensures a fixed transmit power, robust estimation across several sensing noise distributions, as well as an SNR estimate that requires a single set of transmissions from the sensors to the fusion center, unlike the amplify-and-forward approach. The performance of the estimators of the mean and variance are evaluated in terms of asymptotic variance, which is used to evaluate the performance of the SNR estimator in the case of Gaussian, Laplace and Cauchy sensing noise distributions. For each sensing...
Discharge estimation in compound channels with ﬁxed and mobile bed
Indian Academy of Sciences (India)
Galip Seckin; Mustafa Mamak; Serter Atabay; Mazen Omran
2009-12-01
Two-dimensional (2-D) formulae for estimating discharge capacity of straight compound channels are reviewed and applied to overbank ﬂows in straight ﬁxed and mobile bed compound channels. The predictive capabilities of these formulae were evaluated using experimental data obtained from the small-scale University of Birmingham channel. Full details of these data and key references may be found at the following www.ﬂowdata.bham.ac.uk (university website). 2-D formulae generally account for bed shear, lateral shear, and secondary ﬂow effects via 3 coefﬁcients f, and . In this paper, the secondary ﬂow term() used within the 2-D methods analysed here is ignored in all applications. Two different 2-D formulae almost give practically the same results for the same data when the secondary ﬂow term is ignored. For overall test cases, the value of dimensionless eddy viscosity used in 2-D formulae was kept at 0·13 as recommended for open channels. 2-D formulae gave good predictions for most of the data sets studied in comparison with the traditional 1-D methods, namely the Single Channel Method (SCM) and the Divided Channel Method (DCM). The accuracy of predictions of 2-D formulae was increased by calibrating of value where the calibration was needed. For overall data, the average errors for each method were Lateral Division Methods (LDMs), with value of 0·13, 2·8%, DCM 14·3% and SCM $−26·8$%. The average error was 0·5% for LDMs with the calibrated values of .
Generation and protection of steady-state quantum correlations due to quantum channels with memory
Guo, You-neng; Fang, Mao-fa; Wang, Guo-you; Zeng, Ke
2016-12-01
We have proposed a scheme of the generation and preservation of two-qubit steady-state quantum correlations through quantum channels where successive uses of the channels are correlated. Different types of noisy channels with memory, such as amplitude damping, phase damping, and depolarizing channels, have been taken into account. Some analytical or numerical results are presented. The effect of channels with memory on dynamics of quantum correlations has been discussed in detail. The results show that steady-state entanglement between two initial qubits whose initial states are prepared in a specific family states without entanglement subject to amplitude damping channel with memory can be generated. The entanglement creation is related to the memory coefficient of channel μ . The stronger the memory coefficient of channel μ is, the more the entanglement creation is, and the earlier the separable state becomes the entangled state. Besides, we compare the dynamics of entanglement with that of quantum discord when a two-qubit system is initially prepared in an entangled state. We show that entanglement dynamics suddenly disappears, while quantum discord dynamics displays only in the asymptotic limit. Furthermore, two-qubit quantum correlations can be preserved at a long time in the limit of μ → 1.
Generation and protection of steady-state quantum correlations due to quantum channels with memory
Guo, You-neng; Fang, Mao-fa; Wang, Guo-you; Zeng, Ke
2016-09-01
We have proposed a scheme of the generation and preservation of two-qubit steady-state quantum correlations through quantum channels where successive uses of the channels are correlated. Different types of noisy channels with memory, such as amplitude damping, phase damping, and depolarizing channels, have been taken into account. Some analytical or numerical results are presented. The effect of channels with memory on dynamics of quantum correlations has been discussed in detail. The results show that steady-state entanglement between two initial qubits whose initial states are prepared in a specific family states without entanglement subject to amplitude damping channel with memory can be generated. The entanglement creation is related to the memory coefficient of channel μ . The stronger the memory coefficient of channel μ is, the more the entanglement creation is, and the earlier the separable state becomes the entangled state. Besides, we compare the dynamics of entanglement with that of quantum discord when a two-qubit system is initially prepared in an entangled state. We show that entanglement dynamics suddenly disappears, while quantum discord dynamics displays only in the asymptotic limit. Furthermore, two-qubit quantum correlations can be preserved at a long time in the limit of μ → 1.
Space-Time Coded MC-CDMA: Blind Channel Estimation, Identifiability, and Receiver Design
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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.
Rehan, Waqas; Fischer, Stefan; Rehan, Maaz
2016-01-01
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
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
Dynamics of a multi-mode maximum entangled coherent state over an amplitude damping channel
Institute of Scientific and Technical Information of China (English)
A. E1 Allati; Y. Hassouni; N. Metwally
2011-01-01
The dynamics of the maximum entangled coherent state traveling through an amplitude damping channel is investigated.For small values of the transmissivity rate,the traveling state is very fragile to this noise channel,which suffers from the phase flip error with high probability. The entanglement decays smoothly for larger values of the transmissivity rate and speedily for smaller values of this rate.As the number of modes increases,the traveling state over this noise channel quickly loses its entanglement.The odd and even states vanish at the same value of field intensity.
Dynamics of multi-modes maximum entangled coherent state over amplitude damping channel
Allati, A El; Metwally, N
2012-01-01
The dynamics of maximum entangled coherent state travels through an amplitude damping channel is investigated. For small values of the transmissivity rate the travelling state is very fragile to this noise channel, where it suffers from the phase flip error with high probability. The entanglement decays smoothly for larger values of the transmissivity rate and speedily for smaller values of this rate. As the number of modes increases, the travelling state over this noise channel loses its entanglement hastily. The odd and even states vanish at the same value of the field intensity.
Quantum Fisher information of the Greenberg-Horne-Zeilinger state in decoherence channels
Ma, Jian; Huang, Yi-Xiao; Wang, Xiaoguang; Sun, C. P.
2011-08-01
Quantum Fisher information of a parameter characterizes the sensitivity of the state with respect to changes of the parameter. In this article, we study the quantum Fisher information of a state with respect to SU(2) rotations under three decoherence channels: the amplitude-damping, phase-damping, and depolarizing channels. The initial state is chosen to be a Greenberg-Horne-Zeilinger state of which the phase sensitivity can achieve the Heisenberg limit. By using the Kraus operator representation, the quantum Fisher information is obtained analytically. We observe the decay and sudden change of the quantum Fisher information in all three channels.
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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.
Massive-MIMO Sparse Uplink Channel Estimation Using Implicit Training and Compressed Sensing
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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
Abdallah, Saeed; Psaromiligkos, Ioannis N.
2012-03-01
We analyze the mean-squared error (MSE) performance of widely linear (WL) and conventional subspace-based channel estimation for single-input multiple-output (SIMO) flat-fading channels employing binary phase-shift-keying (BPSK) modulation when the covariance matrix is estimated using a finite number of samples. The conventional estimator suffers from a phase ambiguity that reduces to a sign ambiguity for the WL estimator. We derive closed-form expressions for the MSE of the two estimators under four different ambiguity resolution scenarios. The first scenario is optimal resolution, which minimizes the Euclidean distance between the channel estimate and the actual channel. The second scenario assumes that a randomly chosen coefficient of the actual channel is known and the third assumes that the one with the largest magnitude is known. The fourth scenario is the more realistic case where pilot symbols are used to resolve the ambiguities. Our work demonstrates that there is a strong relationship between the accuracy of ambiguity resolution and the relative performance of WL and conventional subspace-based estimators, and shows that the less information available about the actual channel for ambiguity resolution, or the lower the accuracy of this information, the higher the performance gap in favor of the WL estimator.
Precision of channel catfish catch estimates using hoop nets in larger Oklahoma reservoirs
Stewart, David R.; Long, James M.
2012-01-01
Hoop nets are rapidly becoming the preferred gear type used to sample channel catfish Ictalurus punctatus, and many managers have reported that hoop nets effectively sample channel catfish in small impoundments (catfish and the time involved in using 16 tandem hoop net series in larger impoundments (>200 ha). Hoop net series were fished once, set for 3 d; then we used Monte Carlo bootstrapping techniques that allowed us to estimate the number of net series required to achieve two levels of precision (relative standard errors [RSEs] of 15 and 25) at two levels of confidence (80% and 95%). Sixteen hoop net series were effective at obtaining an RSE of 25 with 80% and 95% confidence in all but one reservoir. Achieving an RSE of 15 was often less effective and required 18-96 hoop net series given the desired level of confidence. We estimated that an hour was needed, on average, to deploy and retrieve three hoop net series, which meant that 16 hoop net series per reservoir could be "set" and "retrieved" within a day, respectively. The estimated number of net series to achieve an RSE of 25 or 15 was positively associated with the coefficient of variation (CV) of the sample but not with reservoir surface area or relative abundance. Our results suggest that hoop nets are capable of providing reasonably precise estimates of channel catfish relative abundance and that the relationship with the CV of the sample reported herein can be used to determine the sampling effort for a desired level of precision.
Kaddouri, Samar
The underwater channel poses numerous challenges for acoustic communication. Acoustic waves suffer long propagation delay, multipath, fading, and potentially high spatial and temporal variability. In addition, there is no typical underwater acoustic channel; every body of water exhibits quantifiably different properties. Underwater acoustic modems are traditionally operated at low frequencies. However, the use of broadband, high frequency communication is a good alternative because of the lower background noise compared to low-frequencies, considerably larger bandwidth and better source transducer efficiency. One of the biggest problems in the underwater acoustic communications at high frequencies is time-selective fading, resulting in the Doppler spread. While many Doppler detection, estimation and compensation techniques can be found in literature, the applications are limited to systems operating at low frequencies contained within frequencies ranging from a few hundred Hertz to around 30 kHz. This dissertation proposes two robust channel estimation techniques for simultaneous transmissions using multiple sources and multiple receivers (MIMO) that closely follows the rapidly time-varying nature of the underwater channel. The first method is a trended least square (LS) estimation that combines the traditional LS method with an empirical modal decomposition (EMD) based trend extraction algorithm. This method allows separating the slow fading modes in the MIMO channels from the fast-fading ones and thus achieves a close tracking of the channel impulse response time fluctuations. This dissertation also outlines a time-varying underwater channel estimation method based on the channel sparsity characteristic. The sparsity of the underwater communication channel is exploited by using the MIMO P-iterative greedy orthogonal matching pursuit (MIMO-OMP) algorithm for the channel estimation. Both techniques are demonstrated in a fully controlled environment, using simulated
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.
Directory of Open Access Journals (Sweden)
Ser Javier Del
2005-01-01
Full Text Available We consider the case of two correlated sources, S 1 and S 2 . 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 S 1 over an additive white Gaussian noise (AWGN channel when the output of the other source S 2 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 S 1 . 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.
Coupled Ito equations of continuous quantum state measurement, and estimation
Diósi, L; Konrad, T; Scherer, A; Audretsch, Juergen; Diosi, Lajos; Konrad, Thomas; Scherer, Artur
2006-01-01
We discuss a non-linear stochastic master equation that governs the time-evolution of the estimated quantum state. Its differential evolution corresponds to the infinitesimal updates that depend on the time-continuous measurement of the true quantum state. The new stochastic master equation couples to the two standard stochastic differential equations of time-continuous quantum measurement. For the first time, we can prove that the calculated estimate almost always converges to the true state, also at low-efficiency measurements. We show that our single-state theory can be adapted to weak continuous ensemble measurements as well.
Estimation methods for nonlinear state-space models in ecology
DEFF Research Database (Denmark)
Pedersen, Martin Wæver; Berg, Casper Willestofte; Thygesen, Uffe Høgsbro
2011-01-01
The use of nonlinear state-space models for analyzing ecological systems is increasing. A wide range of estimation methods for such models are available to ecologists, however it is not always clear, which is the appropriate method to choose. To this end, three approaches to estimation in the theta...... logistic model for population dynamics were benchmarked by Wang (2007). Similarly, we examine and compare the estimation performance of three alternative methods using simulated data. The first approach is to partition the state-space into a finite number of states and formulate the problem as a hidden...... Markov model (HMM). The second method uses the mixed effects modeling and fast numerical integration framework of the AD Model Builder (ADMB) open-source software. The third alternative is to use the popular Bayesian framework of BUGS. The study showed that state and parameter estimation performance...
Statistical estimation of the efficiency of quantum state tomography protocols.
Bogdanov, Yu I; Brida, G; Genovese, M; Kulik, S P; Moreva, E V; Shurupov, A P
2010-07-02
A novel operational method for estimating the efficiency of quantum state tomography protocols is suggested. It is based on a priori estimation of the quality of an arbitrary protocol by means of universal asymptotic fidelity distribution and condition number, which takes minimal value for better protocol. We prove the adequacy of the method both with numerical modeling and through the experimental realization of several practically important protocols of quantum state tomography.
Device-to-Device Underlay Cellular Networks with Uncertain Channel State Information
Memmi, Amen
2016-01-06
Device-to-Device (D2D) communications underlying the cellular infrastructure is a technology that has recently been proposed as a promising solution to enhance cellular network capabilities: It improves spectrum utilization, overall throughput and energy efficiency while enabling new peer-to-peer and location-based applications and services. However, interference is the major challenge since the same resources are shared by both systems. Therefore, interference management techniques are required to keep the interference under control. In this work, in order to mitigate interference, we consider centralized and distributed power control algorithms in a one-cell random network model. Differently from previous works, we are assuming that the channel state information (CSI) may be imperfect and include estimation errors. We evaluate how this uncertainty impacts performances.
Robust control of robots via linear estimated state feedback
Berghuis, Harry; Nijmeijer, Henk
1994-01-01
In this note we propose a robust tracking controller for robots that requires only position measurements. The controller consists of two parts: a linear observer part that generates an estimated error state from the error on the joint position and a linear feedback part that utilizes this estimated
Rezki, Zouheir
2013-07-01
We study the throughput capacity region of the Gaussian multi-access (MAC) fading channel with perfect channel state information (CSI) at the receiver and at the transmitters (CSI-TR), at low power regime. We show that it has a multidimensional rectangle structure and thus is simply characterized by single user capacity points. More specifically, we show that at low power regime, the boundary surface of the capacity region shrinks to a single point corresponding to the sum-rate maximizer and that the coordinates of this point coincide with single user capacity bounds. Using the duality of Gaussian MAC and broadcast channels (BC), we provide a simple characterization of the BC capacity region at low power regime. © 2013 IEEE.
PAPR Reduction Approach Based on Channel Estimation Pilots for Next Generations Broadcasting Systems
Directory of Open Access Journals (Sweden)
Anh-Tai Ho
2011-01-01
Full Text Available A novel peak-to-average power ratio (PAPR reduction technique for orthogonal frequency division multiplexing (OFDM systems is addressed. Instead of using dedicated pilots for PAPR reduction as with tone reservation (TR method selected by the DVB-T2 standard, we propose to use existing pilots used for channel estimation. In this way, we avoid the use of reserved tone pilots and then improve the spectral efficiency of the system. In order to allow their recovery at the receiver, these pilots have to follow particular laws which permit their blind detection and avoid sending side information. In this work, we propose and investigate a multiplicative law operating in discrete frequency domain. The operation in discrete domain aims at reducing degradation due to detection and estimation error in continuous domain. Simulation results are performed using the new DVB-T2 standard parameters. Its performance is compared to the DVB-T2 PAPR gradient algorithm and to the second-order cone programming (SOCP competitive technique proposed in the literature. We show that the proposed technique is efficient in terms of PAPR reduction value and of spectral efficiency while the channel estimation performance is maintained.
Noorduijn, Saskia L.; Shanafield, Margaret; Trigg, Mark A.; Harrington, Glenn A.; Cook, Peter G.; Peeters, L.
2014-02-01
Seepage flux from ephemeral streams can be an important component of the water balance in arid and semiarid regions. An emerging technique for quantifying this flux involves the measurement and simulation of a flood wave as it moves along an initially dry channel. This study investigates the usefulness of including surface water and groundwater data to improve model calibration when using this technique. We trialed this approach using a controlled flow event along a 1387 m reach of artificial stream channel. Observations were then simulated using a numerical model that combines the diffusion-wave approximation of the Saint-Vénant equations for streamflow routing, with Philip's infiltration equation and the groundwater flow equation. Model estimates of seepage flux for the upstream segments of the study reach, where streambed hydraulic conductivities were approximately 101 m d-1, were on the order of 10-4 m3 d-1 m-2. In the downstream segments, streambed hydraulic conductivities were generally much lower but highly variable (˜10-3 to 10-7 m d-1). A Latin Hypercube Monte Carlo sensitivity analysis showed that the flood front timing, surface water stage, groundwater heads, and the predicted streamflow seepage were most influenced by specific yield. Furthermore, inclusion of groundwater data resulted in a higher estimate of total seepage estimates than if the flood front timing were used alone.
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.
Blind CP-OFDM and ZP-OFDM Parameter Estimation in Frequency Selective Channels
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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.
Hadei, Sayed A
2011-01-01
This paper provides analytical performance of the low-complexity family of affine projection algorithms on the estimation of multipath Rayleigh fading channels in the presence of carrier frequency offsets (CFO) and random channel variations. Our analysis is based on the calculation of the error correlation matrix of the estimation, the mean-square weight error (MSWE) and the mean-square estimation error (MSE) parameters. The analysis does not use strong assumptions like small or large step-size, and explicit closed-form expressions for the MSE of estimation are obtained only from common hypotheses in wireless communication context. In this paper, the optimum stepsize parameters minimizing the MSE of estimation are analytically derived without any simplified assumptions. For the sake of comparison with other analytical approaches, we also investigate the performance of the introduced algorithms by the energy conservation relation. Likewise for exact performance analysis, we evaluate all the moment terms that a...
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Robert Karoly
2010-06-01
Full Text Available Sodium channels are one of the most intensively studied drug targets. Sodium channel inhibitors (e.g., local anesthetics, anticonvulsants, antiarrhythmics and analgesics exert their effect by stabilizing an inactivated conformation of the channels. Besides the fast-inactivated conformation, sodium channels have several distinct slow-inactivated conformational states. Stabilization of a slow-inactivated state has been proposed to be advantageous for certain therapeutic applications. Special voltage protocols are used to evoke slow inactivation of sodium channels. It is assumed that efficacy of a drug in these protocols indicates slow-inactivated state preference. We tested this assumption in simulations using four prototypical drug inhibitory mechanisms (fast or slow-inactivated state preference, with either fast or slow binding kinetics and a kinetic model for sodium channels. Unexpectedly, we found that efficacy in these protocols (e.g., a shift of the "steady-state slow inactivation curve", was not a reliable indicator of slow-inactivated state preference. Slowly associating fast-inactivated state-preferring drugs were indistinguishable from slow-inactivated state-preferring drugs. On the other hand, fast- and slow-inactivated state-preferring drugs tended to preferentially affect onset and recovery, respectively. The robustness of these observations was verified: i by performing a Monte Carlo study on the effects of randomly modifying model parameters, ii by testing the same drugs in a fundamentally different model and iii by an analysis of the effect of systematically changing drug-specific parameters. In patch clamp electrophysiology experiments we tested five sodium channel inhibitor drugs on native sodium channels of cultured hippocampal neurons. For lidocaine, phenytoin and carbamazepine our data indicate a preference for the fast-inactivated state, while the results for fluoxetine and desipramine are inconclusive. We suggest that
MIMO-OFDM channel estimation method utilizing correlation in time domain for B3G-TDD uplink
Institute of Scientific and Technical Information of China (English)
ZHOU Ming-yu; LI Li-hua; JIANG Jun; ZHONG Ming-hua; TAG Xiao-feng
2007-01-01
This article proposes a simple pilot-aided channel estimation method based on correlation in time domain for multiple-input and multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. Pilot symbols in all transmit antennas are generated from different circular shifting of a certain sequence. Through once correlation, the receiver can obtain time-domain pulse responses for channel fading from all transmit antennas to a certain receive antenna, from which channel estimation in frequency domain can be obtained. Beyond 3G time-division duplex (B3G-TDD) uplink is introduced, and the channel estimation method is used in it. Theoretical analysis and simulation are both carried out. Mean square error (MSB) performance shows that the method can exhibit precise estimation. Complexity analysis proves it requires very low complexity. System simulation result shows that it guarantees the performance of B3G-TDD uplink very well.
Identifying transition rates of ionic channels via observations at a single state
Deng Ying Chun; Qian Min Ping; Feng Jian Feng
2003-01-01
We consider how to determine all transition rates of an ion channel when it can be described by a birth-death chain or a Markov chain on a star-graph with continuous time. It is found that all transition rates are uniquely determined by the distribution of its lifetime and death-time histograms at a single state. An algorithm to calculate the transition rates exactly, based on the statistics of the lifetime and death-time of the Markov chain at the state, is provided. Examples to illustrate how an ion channel activity is fully determined by the observation of a single state of the ion channel are included.
Tao, T.; Xie, J; Drumm, M L; Zhao, J.; Davis, P B; Ma, J.
1996-01-01
The cystic fibrosis transmembrane conductance regulator (CFTR) chloride channel exhibits multiple subconductance states. To study the regulation of conductance states of the CFTR channel, we expressed the wild-type CFTR protein in HEK 293 cells, and isolated microsomal membrane vesicles for reconstitution studies in lipid bilayer membranes. A single CFTR channel had a dominant conductance of 7.8 pS (H), plus two sub-open states with conductances of approximately 6 pS (M) and 2.7 pS (L) in 200...
Dynamic State Transitions in the Nervous System: From Ion Channels to Neurons to Networks
Århem, Peter; Braun, Hans A.; Huber, Martin T.; Liljenström, Hans
The following sections are included: * Introduction * Ion channels: The microscopic scale * The variety of ion channels * Channel kinetics * Neurons: The mesoscopic scale * The feedback loops between membrane potential and ion currents * Neuron models: Concepts and examples * Impulse pattern modulation by ion channel densities * Oscillatory patterns * Irregular patterns * Impulse pattern modulation by subthreshold oscillations * The cold receptor model * Deterministic patterns and noise induced state-transitions on temperature scaling * Neuronal networks: The oscopic scale * Random channel events cause network state transitions * A hippocampal neural network model * Simulating noise-induced state transitions * Functional significance of oscopic neurodynamics * Conclusions * Appendix A: Computation of the neuron models * Hippocampal neuron model * The cold receptor model * Appendix B: Neural network model * References
Trap states in AlGaN channel high-electron-mobility transistors
Energy Technology Data Exchange (ETDEWEB)
Zhao, ShengLei; Zhang, Kai; Ha, Wei; Chen, YongHe; Zhang, Peng; Zhang, JinCheng; Hao, Yue, E-mail: yhao@xidian.edu.cn [Key Laboratory of Wide Band Gap Semiconductor Materials and Devices, School of Microelectronics, Xidian University, Xi' an 710071 (China); Ma, XiaoHua, E-mail: xhma@xidian.edu.cn [Key Laboratory of Wide Band Gap Semiconductor Materials and Devices, School of Microelectronics, Xidian University, Xi' an 710071 (China); School of Advanced Materials and Nanotechnology, Xidian University, Xi' an 710071 (China)
2013-11-18
Frequency dependent capacitance and conductance measurements were performed to analyze the trap states in the AlGaN channel high-electron-mobility transistors (HEMTs). The trap state density in the AlGaN channel HEMTs decreases from 1.26 × 10{sup 13} cm{sup −2}eV{sup −1} at the energy of 0.33 eV to 4.35 × 10{sup 11} cm{sup −2}eV{sup −1} at 0.40 eV. Compared with GaN channel HEMTs, the trap states in the AlGaN channel HEMTs have deeper energy levels. The trap with deeper energy levels in the AlGaN channel HEMTs is another reason for the reduction of the reverse gate leakage current besides the higher Schottky barrier height.
Energy Technology Data Exchange (ETDEWEB)
Valle H, J.; Morales S, J. B. [UNAM, DEPFI, Laboratorio de Analisis de Ingenieria de Reactores Nucleares, Campus Morelos en IMTA, Jiutepec, Morelos (Mexico); Espinosa P, G., E-mail: julfi_ig@yahoo.com.m [Universidad Autonoma Metropolitana, Unidad Iztapalapa, Av. San Rafael Atlixco No. 186, Col. Vicentina, 09340 Mexico D. F. (Mexico)
2010-10-15
This work presents the design and implementation of an advanced controller for a reduced order model of a BWR reactor core cooled by natural circulating water, which allows real time estimates of coolant flows through fuel assemblies about standard neutron flux strings. Nuclear power plants with boiling water reactors control individual fuel assembly coolant flows by forced circulation using external or internal water pumps and different core support plate orifices. These two elements reduce flow dependency on local channel pressure drops. In BWR reactors using only natural circulation coolant flows, these two elements are not available and therefore individual channel coolant flows are highly dependent in local conditions, such as power distributions and local pressure drops. Therefore it is expected that grater uncertainties in these variables be used during safety, fuel management and other analysis, which in turns may lead to increased operation penalties, such as tighter operating limits. The objective of this work is to asses by computer simulations means to reduce uncertainties in the measurement of fuel assembly coolant flows and eventually the associated penalties. During coolant phase transitions, pressure drops and local power may alter local natural circulation through fuel assemblies and flow estimates can be helped or not by control rod moves. This work presents the construction of an optimal controller for a core flow estimator based on a reduced order model of the coolant going though the reactor vessel components and nuclear core. This model is to be driven by plant signals from standard BWR instrumentation in order to estimate the coolant flows in selected fuel assemblies about a LPRM string. For this purpose an equivalent electrical model has been mathematically developed and numerically tested. The power-flow maps of typical BRW are used as steady state references for this equivalent model. Once these were fully reproduced for steady state
Coded DS-CDMA Systems with Iterative Channel Estimation and no Pilot Symbols
2010-08-01
the desired user at the kth symbol time with active MAI can be written as y (k) = C ⌊k/nFB⌋ x (k) + nint(k) + n(k), 1 ≤ k ≤ N 2 (3) 4 Demod . Metric...ar X iv :1 00 8. 31 96 v1 [ cs .I T ] 1 9 A ug 2 01 0 1 Coded DS-CDMA Systems with Iterative Channel Estimation and no Pilot Symbols Don...boldface represent matrices. E denotes the statistical expectation, (·)T is the matrix transpose, * is the complex conjugate, and ⌊ x ⌋ is the largest integer
An ICA and EC based approach for blind equalization and channel parameter estimation
Institute of Scientific and Technical Information of China (English)
何振亚; 刘琚; 杨绿溪; 蔚承建
2000-01-01
A new on-line blind equalization approach is proposed. The approach combines over-sampling technique with independent component analysis (ICA) neural network and can give equalized output on-line employing only the received signal. Based on the fourth-order cumulants and the characteristic of the linear system, the parameters of original channel are also estimated using evolutionary computation (EC). Compared to traditional equalization methods, the proposed algorithm is of simple architecture, does not need learning sequences apart from the observation, and can achieve both blind equalization and system identification. Computer simulations show good performance.
An ICA and EC based approach for blind equalization and channel parameter estimation
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
A new on-line blind equalization approach is proposed. The approach combines over-sampling technique with independent component analysis (ICA)neural network and can give equalized output on-line employing only the received signal. Based on the fourth-order cumulants and the characteristic of the linear system, the parameters of original channel are also estimated using evolutionary computation(EC).Compared to traditional equalization methods, the proposed algorithm is of simple architecture, does not need learning sequences apart from the observation, and can achieve both blind equalization and system identification. Computer simulations show good performance.
Blind Channel Estimation for SIMO-OFDM Systems without Cyclic Prefix
Fang, Shih-Hao; Chen, Ju-Ya; Shieh, Ming-Der; Lin, Jing-Shiun
A blind channel estimation algorithm based on the subspace method for single-input multiple-output (SIMO) orthogonal frequency division multiplexing (OFDM) systems is proposed in this letter. With the aid of a repetition index, the conventional algorithm is a special case of our algorithm. Compared with related studies, the proposed algorithm reduces the computational complexity of the SVD operation and is suitable for cyclic-prefix-free systems. In particular, the necessary condition of the proposed signal matrix to be full rank can be satisfied with fewer OFDM blocks. Simulation results demonstrate that the proposed algorithm outperforms conventional methods in normalized mean-square error.
Directory of Open Access Journals (Sweden)
Imed Hadj Kacem
2008-01-01
Full Text Available We consider the problem of optimization of the training sequence length when a turbo-detector composed of a maximum a posteriori (MAP equalizer and a MAP decoder is used. At each iteration of the receiver, the channel is estimated using the hard decisions on the transmitted symbols at the output of the decoder. The optimal length of the training sequence is found by maximizing an effective signal-to-noise ratio (SNR taking into account the data throughput loss due to the use of pilot symbols.
Onboard sea state estimation based on measured ship motions
DEFF Research Database (Denmark)
Nielsen, Ulrik Dam; Stredulinsky, David C.
2011-01-01
It is possible to obtain estimates of the sea state at the specific position of an advancing vessel by processing measurements of the vessel’s wave-induced responses. The analogy to a wave rider buoy is clear, although the situation of an advancing ship is more complex due to forward speed....... The paper studies the ‘wave buoy analogy’, and a large set of full-scale motion measurements is considered. It is shown that the wave buoy analogy gives fairly accurate estimates of sea state parameters when compared to estimates from real wave rider buoys....
A Simplified Estimation of Latent State--Trait Parameters
Hagemann, Dirk; Meyerhoff, David
2008-01-01
The latent state-trait (LST) theory is an extension of the classical test theory that allows one to decompose a test score into a true trait, a true state residual, and an error component. For practical applications, the variances of these latent variables may be estimated with standard methods of structural equation modeling (SEM). These…
Virtual speed sensors based algorithm for expressway traffic state estimation
Institute of Scientific and Technical Information of China (English)
XU DongWei; DONG HongHui; JIA LiMin; QIN Yong
2012-01-01
The accurate estimation of expressway traffic state can provide decision-making for both travelers and traffic managers.The speed is one of the most representative parameter of the traffic state.So the expressway speed spatial distribution can be taken as the expressway traffic state equivalent.In this paper,an algorithm based on virtual speed sensors (VSS) is presented to estimate the expressway traffic state (the speed spatial distribution).To gain the spatial distribution of expressway traffic state,virtual speed sensors are defined between adjacent traffic flow sensors.Then,the speed data extracted from traffic flow sensors in time series are mapped to space series to design virtual speed sensors.Then the speed of virtual speed sensors can be calculated with the weight matrix which is related with the speed of virtual speed sensors and the speed data extracted from traffic flow sensors and the speed data extracted from traffic flow sensors in time series.Finally,the expressway traffic state (the speed spatial distribution) can be gained.The acquisition of average travel speed of the expressway is taken for application of this traffic state estimation algorithm.One typical expressway in Beijing is adopted for the experiment analysis.The results prove that this traffic state estimation approach based on VSS is feasible and can achieve a high accuracy.
F-ETX: a predictive link state estimator for mobile networks
Directory of Open Access Journals (Sweden)
Sébastien Bindel
2016-06-01
Full Text Available Due to their inherent features, Mobile Ad Hoc Networks have proven their efficiency to exchange data between mobile nodes. The main issue in this type of a network is the delivery of data to a destination. Unfortunately, the mobility of nodes and the disturbances of the propagation channel lead to the increase of the loss rate, which undermines routing performances. To address this issue, routing protocols use link quality estimators as a metric. However, current estimators have been designed for static wireless sensor networks and are not suitable in case of mobility. In order to overcome this issue, a novel metric called Fast ETX is suggested, which gives a reliable and accurate link quality assessment. It is setup by four estimators which assess and predict the link state. In addition, we design a framework to integrate this multi-estimator metric into a routing protocol.
Progressive Bayes: a new framework for nonlinear state estimation
Hanebeck, Uwe D.; Briechle, Kai; Rauh, Andreas
2003-04-01
This paper is concerned with recursively estimating the internal state of a nonlinear dynamic system by processing noisy measurements and the known system input. In the case of continuous states, an exact analytic representation of the probability density characterizing the estimate is generally too complex for recursive estimation or even impossible to obtain. Hence, it is replaced by a convenient type of approximate density characterized by a finite set of parameters. Of course, parameters are desired that systematically minimize a given measure of deviation between the (often unknown) exact density and its approximation, which in general leads to a complicated optimization problem. Here, a new framework for state estimation based on progressive processing is proposed. Rather than trying to solve the original problem, it is exactly converted into a corresponding system of explicit ordinary first-order differential equations. Solving this system over a finite "time" interval yields the desired optimal density parameters.
Robust Distributed Estimation over Multiple Access Channels with Constant Modulus Signaling
Tepedelenlioglu, Cihan
2009-01-01
A distributed estimation scheme where the sensors transmit with constant modulus signals over a multiple access channel is considered. The proposed estimator is shown to be strongly consistent for any sensing noise distribution in the i.i.d. case both for a per-sensor power constraint, and a total power constraint. When the distributions of the sensing noise are not identical, a bound on the variances is shown to establish strong consistency. The estimator is shown to be asymptotically normal with a variance (AsV) that depends on the characteristic function of the sensing noise. Optimization of the AsV is considered with respect to a transmission phase parameter for a variety of noise distributions exhibiting differing levels of impulsive behavior. The robustness of the estimator to impulsive sensing noise distributions such as those with positive excess kurtosis, or those that do not have finite moments is shown. The proposed estimator is favorably compared with the amplify and forward scheme under an impuls...
Power system static state estimation using Kalman filter algorithm
Directory of Open Access Journals (Sweden)
Saikia Anupam
2016-01-01
Full Text Available State estimation of power system is an important tool for operation, analysis and forecasting of electric power system. In this paper, a Kalman filter algorithm is presented for static estimation of power system state variables. IEEE 14 bus system is employed to check the accuracy of this method. Newton Raphson load flow study is first carried out on our test system and a set of data from the output of load flow program is taken as measurement input. Measurement inputs are simulated by adding Gaussian noise of zero mean. The results of Kalman estimation are compared with traditional Weight Least Square (WLS method and it is observed that Kalman filter algorithm is numerically more efficient than traditional WLS method. Estimation accuracy is also tested for presence of parametric error in the system. In addition, numerical stability of Kalman filter algorithm is tested by considering inclusion of zero mean errors in the initial estimates.
Nonlinear Filtering Techniques Comparison for Battery State Estimation
Directory of Open Access Journals (Sweden)
Aspasia Papazoglou
2014-09-01
Full Text Available The performance of estimation algorithms is vital for the correct functioning of batteries in electric vehicles, as poor estimates will inevitably jeopardize the operations that rely on un-measurable quantities, such as State of Charge and State of Health. This paper compares the performance of three nonlinear estimation algorithms: the Extended Kalman Filter, the Unscented Kalman Filter and the Particle Filter, where a lithium-ion cell model is considered. The effectiveness of these algorithms is measured by their ability to produce accurate estimates against their computational complexity in terms of number of operations and execution time required. The trade-offs between estimators' performance and their computational complexity are analyzed.
Triangular and Trapezoidal Fuzzy State Estimation with Uncertainty on Measurements
Directory of Open Access Journals (Sweden)
Mohammad Sadeghi Sarcheshmah
2012-01-01
Full Text Available In this paper, a new method for uncertainty analysis in fuzzy state estimation is proposed. The uncertainty is expressed in measurements. Uncertainties in measurements are modelled with different fuzzy membership functions (triangular and trapezoidal. To find the fuzzy distribution of any state variable, the problem is formulated as a constrained linear programming (LP optimization. The viability of the proposed method would be verified with the ones obtained from the weighted least squares (WLS and the fuzzy state estimation (FSE in the 6-bus system and in the IEEE-14 and 30 bus system.
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.
Energy efficiency for cloud-radio access networks with imperfect channel state information
Al-Oquibi, Bayan
2016-12-24
The advent of smartphones and tablets over the past several years has resulted in a drastic increase of global carbon footprint, due to the explosive growth of data traffic. Improving energy efficiency (EE) becomes, therefore, a crucial design metric in next generation wireless systems (5G). Cloud radio access network (C-RAN), a promising 5G network architecture, provides an efficient framework for improving the EE performance, by means of coordinating the transmission across the network. This paper considers a C-RAN system formed by several clusters of remote radio heads (RRHs), each serving a predetermined set of mobile users (MUs), and assumes imperfect channel state information (CSI). The network performance becomes therefore a function of the intra-cluster and inter-cluster interference, as well as the channel estimation error. The paper optimizes the transmit power of each RRH in order to maximize the network global EE subject to MU service rate requirements and RRHs maximum power constraints. The paper proposes solving the optimization problem using a heuristic algorithm based on techniques from optimization theory via a two-stage iterative solution. Simulation results show that the proposed power allocation algorithm provides an appreciable performance improvement as compared to the conventional systems with maximum power transmission strategy. They further highlight the convergence of the proposed algorithm for different networks scenarios.
Zenaidi, Mohamed Ridha
2017-03-01
In energy harvesting communications, the transceivers have to adjust the data transmission to the energy scavenged during the course of communication. The performance of the transmission depends on the channel conditions which vary randomly due to mobility and environmental changes. In this paper, we consider the problem of power allocation taking into account the energy arrivals over time and the quality of channel state information (CSI) measured at the transmitter, in order to maximize the throughput. Differently from previous work, we focus on energy harvesting communications where the CSI at the transmitter is not perfect and may include estimation errors. In the present paper, we introduce a Markov process that models the energy arrival process. Indeed, we solve the throughput maximization problem with respect to energy harvesting constraints. We show that the optimal online power policy can be found using dynamic programming. Furthermore, we study the asymptotic behavior of the communication system at low and high average recharge rate (ARR) regime. Selected numerical results are provided to support our analysis.
Estimating the Burden of Chagas Disease in the United States.
Directory of Open Access Journals (Sweden)
Jennifer Manne-Goehler
2016-11-01
Full Text Available In recent years, there has been growing awareness of the significant burden of Chagas disease in the United States (US. However, epidemiological data on both prevalence and access to care for this disease are limited. The objective of this study is to provide an updated national estimate of Chagas disease prevalence, the first state-level estimates of cases of T. cruzi infection in the US and to analyze these estimates in the context of data on confirmed cases of infection in the US blood supply.In this study, we calculated estimates of the state and national prevalence of Chagas disease. The number of residents originally from Chagas disease endemic countries were computed using data on Foreign-Born Hispanic populations from the American Community Survey, along with recent prevalence estimates for Chagas disease in Latin America from the World Health Organization that were published in 2006 and updated in 2015. We then describe the distribution of estimated cases in each state in relation to the number of infections identified in the donated blood supply per data from the AABB (formerly American Association of Blood Banks.The results of this analysis offer an updated national estimate of 238,091 cases of T. cruzi infection in the United States as of 2012, using the same method as was used by Bern and Montgomery to estimate cases in 2005. This estimate indicates that there are 62,070 cases less than the most recent prior estimate, though it does not include undocumented immigrants who may account for as many as 109,000 additional cases. The state level results show that four states (California, Texas, Florida and New York have over 10,000 cases and an additional seven states have over 5,000 cases. Moreover, since 2007, the AABB has reported 1,908 confirmed cases of T. cruzi infection identified through screening of blood donations.This study demonstrates a substantial burden of Chagas disease in the US, with state variation that reflects the
Estimating the Burden of Chagas Disease in the United States.
Manne-Goehler, Jennifer; Umeh, Chukwuemeka A; Montgomery, Susan P; Wirtz, Veronika J
2016-11-01
In recent years, there has been growing awareness of the significant burden of Chagas disease in the United States (US). However, epidemiological data on both prevalence and access to care for this disease are limited. The objective of this study is to provide an updated national estimate of Chagas disease prevalence, the first state-level estimates of cases of T. cruzi infection in the US and to analyze these estimates in the context of data on confirmed cases of infection in the US blood supply. In this study, we calculated estimates of the state and national prevalence of Chagas disease. The number of residents originally from Chagas disease endemic countries were computed using data on Foreign-Born Hispanic populations from the American Community Survey, along with recent prevalence estimates for Chagas disease in Latin America from the World Health Organization that were published in 2006 and updated in 2015. We then describe the distribution of estimated cases in each state in relation to the number of infections identified in the donated blood supply per data from the AABB (formerly American Association of Blood Banks). The results of this analysis offer an updated national estimate of 238,091 cases of T. cruzi infection in the United States as of 2012, using the same method as was used by Bern and Montgomery to estimate cases in 2005. This estimate indicates that there are 62,070 cases less than the most recent prior estimate, though it does not include undocumented immigrants who may account for as many as 109,000 additional cases. The state level results show that four states (California, Texas, Florida and New York) have over 10,000 cases and an additional seven states have over 5,000 cases. Moreover, since 2007, the AABB has reported 1,908 confirmed cases of T. cruzi infection identified through screening of blood donations. This study demonstrates a substantial burden of Chagas disease in the US, with state variation that reflects the distribution of
Maximum Correntropy Unscented Kalman Filter for Spacecraft Relative State Estimation.
Liu, Xi; Qu, Hua; Zhao, Jihong; Yue, Pengcheng; Wang, Meng
2016-09-20
A new algorithm called maximum correntropy unscented Kalman filter (MCUKF) is proposed and applied to relative state estimation in space communication networks. As is well known, the unscented Kalman filter (UKF) provides an efficient tool to solve the non-linear state estimate problem. However, the UKF usually plays well in Gaussian noises. Its performance may deteriorate substantially in the presence of non-Gaussian noises, especially when the measurements are disturbed by some heavy-tailed impulsive noises. By making use of the maximum correntropy criterion (MCC), the proposed algorithm can enhance the robustness of UKF against impulsive noises. In the MCUKF, the unscented transformation (UT) is applied to obtain a predicted state estimation and covariance matrix, and a nonlinear regression method with the MCC cost is then used to reformulate the measurement information. Finally, the UT is adopted to the measurement equation to obtain the filter state and covariance matrix. Illustrative examples demonstrate the superior performance of the new algorithm.
State-to-state mode selectivity in the HD + OH reaction: Perspectives from two product channels
Zhao, Bin; Sun, Zhigang; Guo, Hua
2016-06-01
The state-to-state quantum dynamics (Jtot = 0) of the HD + OH(υ2 = 0, 1) reaction is studied using a reactant coordinate based method, which allows the analysis of both the H + DOH and D + HOH channels with a single propagation. The stretching vibration of the newly formed bond, namely, the OD bond in DOH and one OH bond in HOH, is excited, thanks to its strong coupling with the reaction coordinate at the transition state. On the other hand, the vibrational energy deposited into the OH reactant (υ2 = 1) is sequestered during the reaction in the spectator OH mode. The combined effect leads to the excitation of both the OD and OH stretching modes in the DOH product, and the dominance of the (002) normal-mode state population in the HOH product, which in the local-mode picture corresponds to the excitation of both OH bonds with one quantum each. The energy flow in this prototypical tetratomic reaction can be understood in terms of the sudden vector projection model.
Quantum ballistic transport by interacting two-electron states in quasi-one-dimensional channels
Energy Technology Data Exchange (ETDEWEB)
Huang, Danhong [Air Force Research Laboratory, Space Vehicles Directorate, Kirtland Air Force Base, New Mexico 87117 (United States); Center for High Technology Materials, University of New Mexico, 1313 Goddard St SE, Albuquerque, New Mexico 87106 (United States); Gumbs, Godfrey [Center for High Technology Materials, University of New Mexico, 1313 Goddard St SE, Albuquerque, New Mexico 87106 (United States); Abranyos, Yonatan [Department of Physics and Astronomy, Hunter College of the City University of New York, 695 Park Avenue, New York, New York 10065 (United States); Pepper, Michael; Kumar, Sanjeev [Department of Electronic and Electrical Engineering, University College London, London, WC1E 7JE (United Kingdom); London Centre for Nanotechnology, 17-19 Gordon Street, London, WC1H 0AH (United Kingdom)
2015-11-15
For quantum ballistic transport of electrons through a short conduction channel, the role of Coulomb interaction may significantly modify the energy levels of two-electron states at low temperatures as the channel becomes wide. In this regime, the Coulomb effect on the two-electron states is calculated and found to lead to four split energy levels, including two anticrossing-level and two crossing-level states. Moreover, due to the interplay of anticrossing and crossing effects, our calculations reveal that the ground two-electron state will switch from one anticrossing state (strong confinement) to a crossing state (intermediate confinement) as the channel width gradually increases and then back to the original anticrossing state (weak confinement) as the channel width becomes larger than a threshold value. This switching behavior leaves a footprint in the ballistic conductance as well as in the diffusion thermoelectric power of electrons. Such a switching is related to the triple spin degeneracy as well as to the Coulomb repulsion in the central region of the channel, which separates two electrons away and pushes them to different channel edges. The conductance reoccurrence region expands from the weak to the intermediate confinement regime with increasing electron density.
DEFF Research Database (Denmark)
Pang, Xiaodan; Zhao, Ying; Deng, Lei
2011-01-01
We propose and demonstrate a 2 × 2 multiple-input multiple-output (MIMO) wireless over fiber transmission system. Seamless translation of two orthogonal frequency division multiplexing (OFDM) signals on dual optical polarization states into wireless MIMO transmission at 795.5 Mbit/s net data rate...... is enabled by using digital training-based channel estimation. A net spectral efficiency of 2.55 bit/s/Hz is achieved....
Steady state, continuity, and the curious behavior of steep channels in layered rocks
Covington, M. D.; Perne, M.; Thaler, E.; Myre, J. M.
2016-12-01
Considerations of landscape steady state have substantially informed our understanding of the relationships between landscapes, tectonics, climate, and lithology. Topographic steady state, where topography is fixed in time, is a particularly important tool in the interpretation of landscape features, such as bedrock channel profiles, within a context of uplift patterns and rock strength. However, topographic steady state cannot strictly be attained in a landscape with layered rocks with non-vertical contacts. We show that an assumption of channel continuity, where channel retreat rates in the direction parallel to a contact are equal above and below the contact, provides a more general description of steady state landscapes in layered rocks, and that topographic steady state is a special case of the steady state derived from continuity. We demonstrate that modeled landscapes approach continuity steady state using 1D simulations and full landscape evolution models. Contrary to common conceptions, continuity predicts that channels will be steeper in weaker rocks in the case of subhorizontal rock layers when the stream power erosion exponent n<1. For subhorizontal layered rocks with different erodibilities, continuity also predicts larger slope contrasts than would be predicted by topographic steady state. Continuity steady state is a type of flux steady state, where uplift is balanced on average by erosion. The differences between topographic steady state and continuity steady state are most pronuced for steep channels in subhorizontal layered rocks. Consequently, cratonic and plateau settings are most likely to produce the effects predicted by continuity steady state. These settings remain relatively underexplored within the bedrock channel literature. Though examples illustrated here utilze the stream power erosion law, continuity steady state provides a general mathematical tool that can be used to explore the development of landscapes in layered rocks using any
Estimating Deaths Attributable to Obesity in the United States
Flegal, Katherine. M.; Williamson, David F.; Pamuk, Elsie R.; Rosenberg, Harry M.
2004-01-01
Estimates of deaths attributable to obesity in the United States rely on estimates from epidemiological cohorts of the relative risk of mortality associated with obesity. However, these relative risk estimates are not necessarily appropriate for the total US population, in part because of exclusions to control for baseline health status and exclusion or underrepresentation of older adults. Most deaths occur among older adults; estimates of deaths attributable to obesity can vary widely depending on the assumptions about the relative risks of mortality associated with obesity among the elderly. Thus, it may be difficult to estimate deaths attributable to obesity with adequate accuracy and precision. We urge efforts to improve the data and methods for estimating this statistic. PMID:15333299
Time-Delay Neural Network for Smart MIMO Channel Estimation in Downlink 4G-LTE-Advance System
Directory of Open Access Journals (Sweden)
Nirmalkumar S. Reshamwala
2014-05-01
Full Text Available Long-Term Evolution (LTE is the next generation of current mobile telecommunication networks. LTE has a new ﬂat radio-network architecture and signiﬁcant increase in spectrum efficiency. In this paper, main focus on throughput performance analysis of robust MIMO channel estimators for Downlink Long Term Evolution-Advance (DL LTE-A-4G system using three Artificial Neural Networks: Feed-forward neural network (FFNN, Cascade-forward neural network (CFNN and Time-Delay neural network (TDNN are adopted to train the constructed neural networks’ models separately using Back-Propagation Algorithm. The methods use the information received by the received reference symbols to estimate the total frequency response of the channel in two important phases. In the first phase, the proposed ANN based method learns to adapt to the channel variations, and in the second phase, it estimates the MIMO channel matrix and try to improve throughput of LTE. The performance of the estimation methods is evaluated by simulations in Vienna LTE-A DL Link Level Simulator. Performance of the proposed channel estimator, Time-Delay neural network (TDNN is compared with traditional Least Square (LS algorithm and ANN based other estimators for Closed Loop Spatial Multiplexing (CLSM - Single User Multi-input Multi-output (MIMO-2×2 and 4×4 in terms of throughput. Simulation result shows TDNN gives better performance than other ANN based estimations methods and LS.
Estimation of pump operational state with model-based methods
Energy Technology Data Exchange (ETDEWEB)
Ahonen, Tero; Tamminen, Jussi; Ahola, Jero; Viholainen, Juha; Aranto, Niina [Institute of Energy Technology, Lappeenranta University of Technology, P.O. Box 20, FI-53851 Lappeenranta (Finland); Kestilae, Juha [ABB Drives, P.O. Box 184, FI-00381 Helsinki (Finland)
2010-06-15
Pumps are widely used in industry, and they account for 20% of the industrial electricity consumption. Since the speed variation is often the most energy-efficient method to control the head and flow rate of a centrifugal pump, frequency converters are used with induction motor-driven pumps. Although a frequency converter can estimate the operational state of an induction motor without external measurements, the state of a centrifugal pump or other load machine is not typically considered. The pump is, however, usually controlled on the basis of the required flow rate or output pressure. As the pump operational state can be estimated with a general model having adjustable parameters, external flow rate or pressure measurements are not necessary to determine the pump flow rate or output pressure. Hence, external measurements could be replaced with an adjustable model for the pump that uses estimates of the motor operational state. Besides control purposes, modelling the pump operation can provide useful information for energy auditing and optimization purposes. In this paper, two model-based methods for pump operation estimation are presented. Factors affecting the accuracy of the estimation methods are analyzed. The applicability of the methods is verified by laboratory measurements and tests in two pilot installations. Test results indicate that the estimation methods can be applied to the analysis and control of pump operation. The accuracy of the methods is sufficient for auditing purposes, and the methods can inform the user if the pump is driven inefficiently. (author)
Estimation of State Transition Probabilities: A Neural Network Model
Saito, Hiroshi; Takiyama, Ken; Okada, Masato
2015-12-01
Humans and animals can predict future states on the basis of acquired knowledge. This prediction of the state transition is important for choosing the best action, and the prediction is only possible if the state transition probability has already been learned. However, how our brains learn the state transition probability is unknown. Here, we propose a simple algorithm for estimating the state transition probability by utilizing the state prediction error. We analytically and numerically confirmed that our algorithm is able to learn the probability completely with an appropriate learning rate. Furthermore, our learning rule reproduced experimentally reported psychometric functions and neural activities in the lateral intraparietal area in a decision-making task. Thus, our algorithm might describe the manner in which our brains learn state transition probabilities and predict future states.
An Achievability Scheme for the Compound Channel with State Noncausally Available at the Encoder
Nair, Chandra; Chia, Yeow-Khiang
2010-01-01
A new achievability scheme for the compound channel with discrete memoryless (DM) state noncausally available at the encoder is established. Achievability is proved using superposition coding, Marton coding, joint typicality encoding, and indirect decoding. The scheme is shown to achieve strictly higher rate than the straightforward extension of the Gelfand-Pinsker coding scheme for a single DMC with DM state, and is optimal for some classes of channels.
Characterizing quantum channels with non-separable states of classical light
Ndagano, Bienvenu; Perez-Garcia, Benjamin; Roux, Filippus S.; McLaren, Melanie; Rosales-Guzman, Carmelo; Zhang, Yingwen; Mouane, Othmane; Hernandez-Aranda, Raul I.; Konrad, Thomas; Forbes, Andrew
2017-04-01
High-dimensional entanglement with spatial modes of light promises increased security and information capacity over quantum channels. Unfortunately, entanglement decays due to perturbations, corrupting quantum links that cannot be repaired without performing quantum tomography on the channel. Paradoxically, the channel tomography itself is not possible without a working link. Here we overcome this problem with a robust approach to characterize quantum channels by means of classical light. Using free-space communication in a turbulent atmosphere as an example, we show that the state evolution of classically entangled degrees of freedom is equivalent to that of quantum entangled photons, thus providing new physical insights into the notion of classical entanglement. The analysis of quantum channels by means of classical light in real time unravels stochastic dynamics in terms of pure state trajectories, and thus enables precise quantum error correction in short- and long-haul optical communication, in both free space and fibre.
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.
Rankings & Estimates: Rankings of the States 2015 and Estimates of School Statistics 2016
National Education Association, 2016
2016-01-01
The data presented in this combined report--"Rankings & Estimates"--provide facts about the extent to which local, state, and national governments commit resources to public education. As one might expect in a nation as diverse as the United States--with respect to economics, geography, and politics--the level of commitment to…
Tao, T; Xie, J; Drumm, M L; Zhao, J; Davis, P B; Ma, J
1996-02-01
The cystic fibrosis transmembrane conductance regulator (CFTR) chloride channel exhibits multiple subconductance states. To study the regulation of conductance states of the CFTR channel, we expressed the wild-type CFTR protein in HEK 293 cells, and isolated microsomal membrane vesicles for reconstitution studies in lipid bilayer membranes. A single CFTR channel had a dominant conductance of 7.8 pS (H), plus two sub-open states with conductances of approximately 6 pS (M) and 2.7 pS (L) in 200 mM KCl with 1 mM MgCl2 (intracellular) and 50 mM KCl with no MgCl2 (extracellular), with pH maintained at 7.4 by 10 mM HEPES-Tris on both sides of the channel. In 200 mM KCl, both H and L states could be measured in stable single-channel recordings, whereas M could not. Spontaneous transitions between H and L were slow; it took 4.5 min for L-->H, and 3.2 min for H-->L. These slow conversions among subconductance states of the CFTR channel were affected by extracellular Mg; in the presence of millimolar Mg, the channel remained stable in the H state. Similar phenomena were also observed with endogenous CFTR channels in T84 cells. In high-salt conditions (1.5 M KCl), all three conductance states of the expressed CFTR channel, 12.1 pS, 8.2 pS, and 3.6 pS, became stable and seemed to gate independently from each other. The existence of multiple stable conductance states associated with the CFTR channel suggests two possibilities: either a single CFTR molecule can exist in multiple configurations with different conductance values, or the CFTR channel may contain multimers of the 170-kDa CFTR protein, and different conductance states are due to different aggregation states of the CFTR protein.
The feature on the posterior conditional probability of finite state Markov channel
Institute of Scientific and Technical Information of China (English)
MU Li-hua; SHEN Ji-hong; YUAN Yan-hua
2005-01-01
The feature of finite state Markov channel probability distribution is discussed on condition that original I/O are known. The probability is called posterior condition probability. It is also proved by Bayes formula that posterior condition probability forms stationary Markov sequence if channel input is independently and identically distributed. On the contrary, Markov property of posterior condition probability isn' t kept if the input isn't independently and identically distributed and a numerical example is utilized to explain this case. The properties of posterior condition probability will aid the study of the numerical calculated recurrence formula of finite state Markov channel capacity.
Quantum state tomography and fidelity estimation via Phaselift
Energy Technology Data Exchange (ETDEWEB)
Lu, Yiping; Liu, Huan; Zhao, Qing, E-mail: qzhaoyuping@bit.edu.cn
2015-09-15
Experiments of multi-photon entanglement have been performed by several groups. Obviously, an increase on the photon number for fidelity estimation and quantum state tomography causes a dramatic increase in the elements of the positive operator valued measures (POVMs), which results in a great consumption of time in measurements. In practice, we wish to obtain a good estimation of fidelity and quantum states through as few measurements as possible for multi-photon entanglement. Phaselift provides such a chance to estimate fidelity for entangling states based on less data. In this paper, we would like to show how the Phaselift works for six qubits in comparison to the data given by Pan’s group, i.e., we use a fraction of the data as input to estimate the rest of the data through the obtained density matrix, and thus goes beyond the simple fidelity analysis. The fidelity bound is also provided for general Schrödinger Cat state. Based on the fidelity bound, we propose an optimal measurement approach which could both reduce the copies and keep the fidelity bound gap small. The results demonstrate that the Phaselift can help decrease the measured elements of POVMs for six qubits. Our conclusion is based on the prior knowledge that a pure state is the target state prepared by experiments.
Most robust and fragile two-qubit entangled states under depolarizing channels
Pang, Chao-Qian; Jiang, Yue; Liang, Mai-Lin
2012-01-01
In the two-qubit system under the local depolarizing channels, the most robust and the most fragile states for a given concurrence or negativity are derived. For the one-sided channel, with the aid of the evolution equation for entanglement given by Konrad \\emph{et al.} [Nat. Phys. 4, 99 (2008)], the pure states are proved to be the most robust. Based on a generalization of the evolution equation, we classify the ansatz states in our investigation by the amount of robustness, and consequently derive the most fragile states. For the two-sided channel, the pure states are proved to be the most robust for a fixed concurrence, but is the most fragile with a given negativity when the channel is uniform. Under the uniform channel, for a given negativity, the most robust states are the ones with the maximal concurrence, which are also the most fragile states when the concurrence is given in the region of [1/2,1]. When the entanglement approaches zero, the most fragile states for a given negativity become the pure st...
Automatic Regionalization Algorithm for Distributed State Estimation in Power Systems
Energy Technology Data Exchange (ETDEWEB)
Wang, Dexin; Yang, Liuqing; Florita, Anthony; Alam, S.M. Shafiul; Elgindy, Tarek; Hodge, Bri-Mathias
2017-04-24
The deregulation of the power system and the incorporation of generation from renewable energy sources recessitates faster state estimation in the smart grid. Distributed state estimation (DSE) has become a promising and scalable solution to this urgent demand. In this paper, we investigate the regionalization algorithms for the power system, a necessary step before distributed state estimation can be performed. To the best of the authors' knowledge, this is the first investigation on automatic regionalization (AR). We propose three spectral clustering based AR algorithms. Simulations show that our proposed algorithms outperform the two investigated manual regionalization cases. With the help of AR algorithms, we also show how the number of regions impacts the accuracy and convergence speed of the DSE and conclude that the number of regions needs to be chosen carefully to improve the convergence speed of DSEs.
Series load induction heating inverter state estimator using Kalman filter
Directory of Open Access Journals (Sweden)
Szelitzky T.
2011-12-01
Full Text Available LQR and H2 controllers require access to the states of the controlled system. The method based on description function with Fourier series results in a model with immeasurable states. For this reason, we proposed a Kalman filter based state estimator, which not only filters the input signals, but also computes the unobservable states of the system. The algorithm of the filter was implemented in LabVIEW v8.6 and tested on recorded data obtained from a 10-40 kHz series load frequency controlled induction heating inverter.
Vehicle State Information Estimation with the Unscented Kalman Filter
Directory of Open Access Journals (Sweden)
Hongbin Ren
2014-01-01
Full Text Available The vehicle state information plays an important role in the vehicle active safety systems; this paper proposed a new concept to estimate the instantaneous vehicle speed, yaw rate, tire forces, and tire kinemics information in real time. The estimator is based on the 3DoF vehicle model combined with the piecewise linear tire model. The estimator is realized using the unscented Kalman filter (UKF, since it is based on the unscented transfer technique and considers high order terms during the measurement and update stage. The numerical simulations are carried out to further investigate the performance of the estimator under high friction and low friction road conditions in the MATLAB/Simulink combined with the Carsim environment. The simulation results are compared with the numerical results from Carsim software, which indicate that UKF can estimate the vehicle state information accurately and in real time; the proposed estimation will provide the necessary and reliable state information to the vehicle controller in the future.
State estimation for anaerobic digesters using the ADM1.
Gaida, D; Wolf, C; Meyer, C; Stuhlsatz, A; Lippel, J; Bäck, T; Bongards, M; McLoone, S
2012-01-01
The optimization of full-scale biogas plant operation is of great importance to make biomass a competitive source of renewable energy. The implementation of innovative control and optimization algorithms, such as Nonlinear Model Predictive Control, requires an online estimation of operating states of biogas plants. This state estimation allows for optimal control and operating decisions according to the actual state of a plant. In this paper such a state estimator is developed using a calibrated simulation model of a full-scale biogas plant, which is based on the Anaerobic Digestion Model No.1. The use of advanced pattern recognition methods shows that model states can be predicted from basic online measurements such as biogas production, CH4 and CO2 content in the biogas, pH value and substrate feed volume of known substrates. The machine learning methods used are trained and evaluated using synthetic data created with the biogas plant model simulating over a wide range of possible plant operating regions. Results show that the operating state vector of the modelled anaerobic digestion process can be predicted with an overall accuracy of about 90%. This facilitates the application of state-based optimization and control algorithms on full-scale biogas plants and therefore fosters the production of eco-friendly energy from biomass.
Efficient sensor placement for state estimation in structural dynamics
Hernandez, Eric M.
2017-02-01
This paper derives a computationally efficient algorithm to determine optimal sequential sensor placement for state estimation in linear structural systems subjected to unmeasured excitations and noise contaminated measurements. The proposed algorithm is developed within the context of the Kalman filter and it minimizes the variance of the state estimate among all possible sequential sensor locations. The paper investigates the effects of measurement type, covariance matrix partition selection, spatial correlation of excitation and model selection on optimal sensor placement. The paper shows that the sequential approach reaches the optimal sensor placement as the number of sensor increases.
Collective vs local measurements in qubit mixed state estimation
Bagán, E; Muñoz-Tàpia, R; Rodríguez, A
2004-01-01
We discuss the problem of estimating a general (mixed) qubit state. We give the optimal guess that can be inferred from any given set of measurements. For collective measurements and for a large number $N$ of copies, we show that the error in the estimation goes as 1/N. For local measurements we focus on the simpler case of states lying on the equatorial plane of the Bloch sphere. We show that standard tomographic techniques lead to an error proportional to $1/N^{1/4}$, while with our optimal data processing it is proportional to $1/N^{3/4}$.
The classical-quantum channel with random state parameters known to the sender
Boche, Holger; Cai, Ning; Nötzel, Janis
2016-05-01
We study an analog of the well-known Gel’fand Pinsker channel which uses quantum states for the transmission of the data. We consider the case where both the sender’s inputs to the channel and the channel states are to be taken from a finite set (the cq-channel with state information at the sender). We distinguish between causal and non-causal channel state information input by the sender. The receiver remains ignorant, throughout. We give a single-letter description of the capacity in the first case. In the second case we present two different regularized expressions for the capacity. It is an astonishing and unexpected result of our work that a simple change from causal to non-causal channel state information by the encoder causes the complexity of a numerical computation of the capacity formula to change from trivial to seemingly difficult. Still, even the non-single letter formula allows one to draw nontrivial conclusions, for example regarding the continuity of the capacity with respect to changes in the system parameters. The direct parts of both coding theorems are based on a special class of positive operator valued measurements (POVMs) which are derived from orthogonal projections onto certain representations of the symmetric groups. This approach supports a reasoning that is inspired by the classical method of types. In combination with the non-commutative union bound these POVMs yield an elegant method of proof for the direct part of the coding theorem in the first case.
Support vector based battery state of charge estimator
Hansen, Terry; Wang, Chia-Jiu
This paper investigates the use of a support vector machine (SVM) to estimate the state-of-charge (SOC) of a large-scale lithium-ion-polymer (LiP) battery pack. The SOC of a battery cannot be measured directly and must be estimated from measurable battery parameters such as current and voltage. The coulomb counting SOC estimator has been used in many applications but it has many drawbacks [S. Piller, M. Perrin, Methods for state-of-charge determination and their application, J. Power Sources 96 (2001) 113-120]. The proposed SVM based solution not only removes the drawbacks of the coulomb counting SOC estimator but also produces accurate SOC estimates, using industry standard US06 [V.H. Johnson, A.A. Pesaran, T. Sack, Temperature-dependent battery models for high-power lithium-ion batteries, in: Presented at the 17th Annual Electric Vehicle Symposium Montreal, Canada, October 15-18, 2000. The paper is downloadable at website http://www.nrel.gov/docs/fy01osti/28716.pdf] aggressive driving cycle test procedures. The proposed SOC estimator extracts support vectors from a battery operation history then uses only these support vectors to estimate SOC, resulting in minimal computation load and suitable for real-time embedded system applications.
Directory of Open Access Journals (Sweden)
Han Wang
2016-06-01
Full Text Available The conventional channel estimation methods based on a preamble for filter bank multicarrier with offset quadrature amplitude modulation (FBMC/OQAM systems in mobile-to-mobile sensor networks are inefficient. By utilizing the intrinsicsparsity of wireless channels, channel estimation is researched as a compressive sensing (CS problem to improve the estimation performance. In this paper, an AdaptiveRegularized Compressive Sampling Matching Pursuit (ARCoSaMP algorithm is proposed. Unlike anterior greedy algorithms, the new algorithm can achieve the accuracy of reconstruction by choosing the support set adaptively, and exploiting the regularization process, which realizes the second selecting of atoms in the support set although the sparsity of the channel is unknown. Simulation results show that CS-based methods obtain significant channel estimation performance improvement compared to that of conventional preamble-based methods. The proposed ARCoSaMP algorithm outperforms the conventional sparse adaptive matching pursuit (SAMP algorithm. ARCoSaMP provides even more interesting results than the mostadvanced greedy compressive sampling matching pursuit (CoSaMP algorithm without a prior sparse knowledge of the channel.
Wang, Han; Du, Wencai; Xu, Lingwei
2016-06-24
The conventional channel estimation methods based on a preamble for filter bank multicarrier with offset quadrature amplitude modulation (FBMC/OQAM) systems in mobile-to-mobile sensor networks are inefficient. By utilizing the intrinsicsparsity of wireless channels, channel estimation is researched as a compressive sensing (CS) problem to improve the estimation performance. In this paper, an AdaptiveRegularized Compressive Sampling Matching Pursuit (ARCoSaMP) algorithm is proposed. Unlike anterior greedy algorithms, the new algorithm can achieve the accuracy of reconstruction by choosing the support set adaptively, and exploiting the regularization process, which realizes the second selecting of atoms in the support set although the sparsity of the channel is unknown. Simulation results show that CS-based methods obtain significant channel estimation performance improvement compared to that of conventional preamble-based methods. The proposed ARCoSaMP algorithm outperforms the conventional sparse adaptive matching pursuit (SAMP) algorithm. ARCoSaMP provides even more interesting results than the mostadvanced greedy compressive sampling matching pursuit (CoSaMP) algorithm without a prior sparse knowledge of the channel.
Breakup channels for C-12 triple-alpha continuum states
Diget, C. Aa; Barker, F. C.; Borge, M. J. G.; Boutami, R.; Dendooven, P.; Eronen, T.; Fox, S. P.; Fulton, B. R.; Fynbo, H. O. U.; Huikari, J.; Hyldegaard, S.; Jeppesen, H. B.; Jokinen, A.; Jonson, B.; Kankainen, A.; Moore, I.; Nieminen, A.; Nyman, G.; Penttila, H.; Pucknell, V. F. E.; Riisager, K.; Rinta-Antila, S.; Tengblad, O.; Wang, Y.; Wilhelmsen, K.; Aysto, J.
The triple-alpha-particle breakup of states in the triple-alpha continuum of C-12 has been investigated by way of coincident detection of all three alpha particles of the breakup. The states have been fed in the beta decay of N-12 and B-12, and the alpha particles measured using a setup that covers
Roscovitine differentially affects CaV2 and Kv channels by binding to the open state.
Buraei, Zafir; Schofield, Geoffrey; Elmslie, Keith S
2007-03-01
Roscovitine potently inhibits cyclin-dependent kinases (CDK) and can independently slow the closing of neuronal (CaV2.2) calcium channels. We were interested if this drug could affect other ion channels similarly. Using whole cell recordings, we found that roscovitine specifically slows deactivation of all CaV2 channels (N, P/Q and R) by binding to the open state. This effect had a rapid onset and EC(50)=54, 120 and 54microM for N-, P/Q-, and R-type channels, respectively. Deactivation of other channel types was not slowed, including L-type calcium channels (CaV1.2, CaV1.3), potassium channels (native, Kv4.2, Kv2.1 and Kv1.3), and native sodium channels. However, most of the channels tested were inhibited by roscovitine. The inhibition was characterized by slow development and a lower affinity (EC(50)=100-300microM). Surprisingly, potassium channels were rapidly inhibited with an EC(50)=23microM, which is similar to the EC(50) for roscovitine block of cell division [Meijer, L., Borgne, A., Mulner, O., Chong, J., Blow, J., Inagaki, N., Inagaki, M., Delcros, J., Moulinoux, J., 1997. Biochemical and cellular effects of roscovitine, a potent and selective inhibitor of the cyclin-dependent kinases cdc2, cdk2 and cdk5. Eur. J. Biochem. 243, 527-536]. Potassium current inhibition seemed to result from open channel block. The high potency of these two rapid onset effects makes them complicating factors for ongoing clinical trials and research using roscovitine. Thus, the physiology and pharmacology of slow CaV2 deactivation and potassium channel block must be explored.
Linsdell, Paul
2014-12-01
Chloride permeation through the cystic fibrosis transmembrane conductance regulator (CFTR) Cl(-) channel is subject to voltage-dependent open-channel block by a diverse range of cytoplasmic anions. However, in most cases the ability of these blocking substances to influence the pore opening and closing process has not been reported. In the present work, patch clamp recording was used to investigate the state-dependent block of CFTR by cytoplasmic Pt(NO2)4(2-) ions. Two major effects of Pt(NO2)4(2-) were identified. First, this anion caused fast, voltage-dependent block of open channels, leading to an apparent decrease in single-channel current amplitude. Secondly, Pt(NO2)4(2-) also decreased channel open probability due to an increase in interburst closed times. Interestingly, mutations in the pore that weakened (K95Q) or strengthened (I344K, V345K) interactions with Pt(NO2)4(2-) altered blocker effects both on Cl(-) permeation and on channel gating, suggesting that both these effects are a consequence of Pt(NO2)4(2-) interaction with a single site within the pore. Experiments at reduced extracellular Cl(-) concentration hinted that Pt(NO2)4(2-) may have a third effect, possibly increasing channel activity by interfering with channel closure. These results suggest that Pt(NO2)4(2-) can enter from the cytoplasm into the pore inner vestibule of both open and closed CFTR channels, and that Pt(NO2)4(2-) bound in the inner vestibule blocks Cl(-) permeation as well as interfering with channel opening and, perhaps, channel closure. Implications for the location of the channel gate in the pore, and the operation of this gate, are discussed.
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.
Campbell, D A; Chkrebtii, O
2013-12-01
Statistical inference for biochemical models often faces a variety of characteristic challenges. In this paper we examine state and parameter estimation for the JAK-STAT intracellular signalling mechanism, which exemplifies the implementation intricacies common in many biochemical inference problems. We introduce an extension to the Generalized Smoothing approach for estimating delay differential equation models, addressing selection of complexity parameters, choice of the basis system, and appropriate optimization strategies. Motivated by the JAK-STAT system, we further extend the generalized smoothing approach to consider a nonlinear observation process with additional unknown parameters, and highlight how the approach handles unobserved states and unevenly spaced observations. The methodology developed is generally applicable to problems of estimation for differential equation models with delays, unobserved states, nonlinear observation processes, and partially observed histories.
State estimation of chemical engineering systems tending to multiple solutions
Directory of Open Access Journals (Sweden)
N. P. G. Salau
2014-09-01
Full Text Available A well-evaluated state covariance matrix avoids error propagation due to divergence issues and, thereby, it is crucial for a successful state estimator design. In this paper we investigate the performance of the state covariance matrices used in three unconstrained Extended Kalman Filter (EKF formulations and one constrained EKF formulation (CEKF. As benchmark case studies we have chosen: a a batch chemical reactor with reversible reactions whose system model and measurement are such that multiple states satisfy the equilibrium condition and b a CSTR with exothermic irreversible reactions and cooling jacket energy balance whose nonlinear behavior includes multiple steady-states and limit cycles. The results have shown that CEKF is in general the best choice of EKF formulations (even if they are constrained with an ad hoc clipping strategy which avoids undesired states for such case studies. Contrary to a clipped EKF formulation, CEKF incorporates constraints into an optimization problem, which minimizes the noise in a least square sense preventing a bad noise distribution. It is also shown that, although the Moving Horizon Estimation (MHE provides greater robustness to a poor guess of the initial state, converging in less steps to the actual states, it is not justified for our examples due to the high additional computational effort.
Zhang, Fan; Wang, Dan; Ding, Rui; Chen, Zhangyuan
2014-09-22
We propose a time domain structure of channel estimation for coherent optical communication systems, which employs training sequence based equalizer and is transparent to arbitrary quadrature amplitude modulation (QAM) formats. Enabled with this methodology, 1.02 Tb/s polarization division multiplexed 32 QAM Nyquist pulse shaping signal with a net spectral efficiency of 7.46 b/s/Hz is transmitted over standard single-mode fiber link with Erbium-doped fiber amplifier only amplification. After 1190 km transmission, the average bit-error rate is lower than the 20% hard-decision forward error correction threshold of 1.5 × 10(-2). The transmission distance can be extended to 1428 km by employing intra-subchannel nonlinear compensation with the digital back-propagation method.
Kurosaki, Yuzuru; Ho, Tak-San; Rabitz, Herschel
2016-05-01
The prospect of performing the open → cyclic ozone isomerization has attracted much research attention. Here we explore this consideration theoretically by performing quantum optimal control calculations to demonstrate the important role that excited-state dissociation channels could play in the isomerization transformation. In the calculations we use a three-state, one-dimensional dynamical model constructed from the lowest five 1A‧ potential energy curves obtained with high-level ab initio calculations. Besides the laser field-dipole couplings between all three states, this model also includes the diabatic coupling between the two excited states at an avoided crossing leading to competing dissociation channels that can further hinder the isomerization process. The present three-state optimal control simulations examine two possible control pathways previously considered in a two-state model, and reveal that only one of the pathways is viable, achieving a robust ∼95% yield to the cyclic target in the three-state model. This work represents a step towards an ultimate model for the open → cyclic ozone transformation capable of giving adequate guidance about the necessary experimental control field resources as well as an estimate of the ro-vibronic spectral character of cyclic ozone as a basis for an appropriate probe of its formation.
Time-Frequency Based Channel Estimation for High-Mobility OFDM Systems-Part I: MIMO Case
Önen, Erol; Akan, Aydın; Chaparro, LuisF
2010-12-01
Multiple-input multiple-output (MIMO) systems hold the potential to drastically improve the spectral efficiency and link reliability in future wireless communications systems. A particularly promising candidate for next-generation fixed and mobile wireless systems is the combination of MIMO technology with Orthogonal Frequency Division Multiplexing (OFDM). OFDM has become the standard method because of its advantages over single carrier modulation schemes on multipath, frequency selective fading channels. Doppler frequency shifts are expected in fast-moving environments, causing the channel to vary in time, that degrades the performance of OFDM systems. In this paper, we present a time-varying channel modeling and estimation method based on the Discrete Evolutionary Transform to obtain a complete characterization of MIMO-OFDM channels. Performance of the proposed method is evaluated and compared on different levels of channel noise and Doppler frequency shifts.
Observability estimate and state observation problems for stochastic hyperbolic equations
2013-01-01
In this paper, we derive a boundary and an internal observability inequality for stochastic hyperbolic equations with nonsmooth lower order terms. The required inequalities are obtained by global Carleman estimate for stochastic hyperbolic equations. By these inequalities, we study a state observation problem for stochastic hyperbolic equations. As a consequence, we also establish a unique continuation property for stochastic hyperbolic equations.
Relevant sampling applied to event-based state-estimation
Marck, J.W.; Sijs, J.
2010-01-01
To reduce the amount of data transfer in networked control systems and wireless sensor networks, measurements are usually sampled only when an event occurs, rather than synchronous in time. Today's event sampling methodologies are triggered by the current value of the sensor. State-estimators are de
Estimation of correlation energy for excited-states of atoms
Hemanadhan, M
2014-01-01
The correlation energies of various atoms in their excited-states are estimated by modelling the Coulomb hole following the previous work by Chakravorty and Clementi. The parameter in the model is fixed by making the corresponding Coulomb hole to satisfy the exact constraint of charge neutrality.
Relevant sampling applied to event-based state-estimation
Marck, J.W.; Sijs, J.
2010-01-01
To reduce the amount of data transfer in networked control systems and wireless sensor networks, measurements are usually sampled only when an event occurs, rather than synchronous in time. Today's event sampling methodologies are triggered by the current value of the sensor. State-estimators are de
Quantum Enhanced Phase Estimation with an Amplified Bell State
Sahota, Jaspreet
2013-01-01
We propose a phase estimation protocol for optical interferometry that employs a probe state (containing on average n photons) obtained by squeezing each mode, separately, of a single photon path entangled Bell state. This scheme involves a Mach-Zehnder type interferometer for which each mode is squeezed after the first beam splitter. Information about the differential phase is extracted using a parity detection and the resulting measurement signal is super-resolving and supersensitive, with a minimum phase uncertainty 2/(n+1). This probe state can be generated with current technologies where n is in the order of many thousands of photons.
Institute of Scientific and Technical Information of China (English)
Li Ying; Zhang Jing; Zhang Jun-Xiang; Zhang Tian-Cai
2006-01-01
This paper has investigated quantum teleportation of even and odd coherent states in terms of the EPR entanglement states for continuous variables. It discusses the relationship between the fidelity and the entanglement of EPR states, which is characterized by the degree of squeezing and the gain of classical channels. It shows that the quality of teleporting quantum states also depends on the characteristics of the states themselves. The properties of teleporting even and odd coherent states at different intensities are investigated. The difference of teleporting two such kinds of quantum states are analysed based on the quantum distance function.
State of charge estimation in Ni-MH rechargeable batteries
Energy Technology Data Exchange (ETDEWEB)
Milocco, R.H. [Grupo Control Automatico y Sistemas (GCAyS), Depto. Electrotecnia, Facultad de Ingenieria, Universidad Nacional del Comahue, Buenos Aires 1400, 8300 Neuquen (Argentina); Castro, B.E. [Instituto de Investigaciones Fisicoquimicas Teoricas y Aplicadas (INIFTA), Universidad Nacional de La Plata, Suc 4, CC16 (1900), La Plata (Argentina)
2009-10-20
In this work we estimate the state of charge (SOC) of Ni-MH rechargeable batteries using the Kalman filter based on a simplified electrochemical model. First, we derive the complete electrochemical model of the battery which includes diffusional processes and kinetic reactions in both Ni and MH electrodes. The full model is further reduced in a cascade of two parts, a linear time invariant dynamical sub-model followed by a static nonlinearity. Both parts are identified using the current and potential measured at the terminals of the battery with a simple 1-D minimization procedure. The inverse of the static nonlinearity together with a Kalman filter provide the SOC estimation as a linear estimation problem. Experimental results with commercial batteries are provided to illustrate the estimation procedure and to show the performance. (author)
Hybrid Approach to State Estimation for Bioprocess Control
Directory of Open Access Journals (Sweden)
Rimvydas Simutis
2017-03-01
Full Text Available An improved state estimation technique for bioprocess control applications is proposed where a hybrid version of the Unscented Kalman Filter (UKF is employed. The underlying dynamic system model is formulated as a conventional system of ordinary differential equations based on the mass balances of the state variables biomass, substrate, and product, while the observation model, describing the less established relationship between the state variables and the measurement quantities, is formulated in a data driven way. The latter is formulated by means of a support vector regression (SVR model. The UKF is applied to a recombinant therapeutic protein production process using Escherichia coli bacteria. Additionally, the state vector was extended by the speciﬁc biomass growth rate µ in order to allow for the estimation of this key variable which is crucial for the implementation of innovative control algorithms in recombinant therapeutic protein production processes. The state estimates depict a sufﬁciently low noise level which goes perfectly with different advanced bioprocess control applications.
Hybrid Approach to State Estimation for Bioprocess Control
Directory of Open Access Journals (Sweden)
Rimvydas Simutis
2017-03-01
Full Text Available An improved state estimation technique for bioprocess control applications is proposed where a hybrid version of the Unscented Kalman Filter (UKF is employed. The underlying dynamic system model is formulated as a conventional system of ordinary differential equations based on the mass balances of the state variables biomass, substrate, and product, while the observation model, describing the less established relationship between the state variables and the measurement quantities, is formulated in a data driven way. The latter is formulated by means of a support vector regression (SVR model. The UKF is applied to a recombinant therapeutic protein production process using Escherichia coli bacteria. Additionally, the state vector was extended by the specific biomass growth rate µ in order to allow for the estimation of this key variable which is crucial for the implementation of innovative control algorithms in recombinant therapeutic protein production processes. The state estimates depict a sufficiently low noise level which goes perfectly with different advanced bioprocess control applications.
Quantum Entanglement Channel based on Excited States in a Spin Chain
Institute of Scientific and Technical Information of China (English)
张少良; 杜良辉; 郭光灿; 周幸祥; 周正威
2011-01-01
We study the possibility of using a spin chain to construct a quantum entanglement channel that can be used for quantum state transmission in a solid state system.We analyze the spin chain's states under various z-directional magnetic field and spin interactions to determine the entanglement between Alice and Bob's spins.We derive the conditions under which this entanglement can be distilled,and find that a spin chain of arbitrary length can be used as a quantum channel for quantum state transmission when the number of spin flips in the chain is large.%We study the possibility of using a spin chain to construct a quantum entanglement channel that can be used for quantum state transmission in a solid state system. We analyze the spin chain's states under various z-directional magnetic field and spin interactions to determine the entanglement between Alice and Bob's spins. We derive the conditions under which this entanglement can be distilled, and find that a spin chain of arbitrary length can be used as a quantum channel for quantum state transmission when the number of spin Hips in the chain is large.
Scheme for teleportation of unknown single qubit state via continuous variables entangling channel
Institute of Scientific and Technical Information of China (English)
Wang Zhong-Jie; Zhang Kan; Fan Chao-Yang
2010-01-01
A new scheme for quantum teleportation of single quantum bit state with using continuous variables entangling channel is presented. In our scheme two entangled light fields are employed. An outstanding characteristic of this scheme is that one atomic state is transmitted directly to another atom without using the third atom as the mediate.
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
Estimation of beryllium ground state energy by Monte Carlo simulation
Energy Technology Data Exchange (ETDEWEB)
Kabir, K. M. Ariful [Department of Physical Sciences, School of Engineering and Computer Science, Independent University, Bangladesh (IUB) Dhaka (Bangladesh); Halder, Amal [Department of Mathematics, University of Dhaka Dhaka (Bangladesh)
2015-05-15
Quantum Monte Carlo method represent a powerful and broadly applicable computational tool for finding very accurate solution of the stationary Schrödinger equation for atoms, molecules, solids and a variety of model systems. Using variational Monte Carlo method we have calculated the ground state energy of the Beryllium atom. Our calculation are based on using a modified four parameters trial wave function which leads to good result comparing with the few parameters trial wave functions presented before. Based on random Numbers we can generate a large sample of electron locations to estimate the ground state energy of Beryllium. Our calculation gives good estimation for the ground state energy of the Beryllium atom comparing with the corresponding exact data.
The Capacity of Finite-State Channels in the High-Noise Regime
Pfister, Henry D
2010-01-01
This paper considers the derivative of the entropy rate of a hidden Markov process with respect to the observation probabilities. The main result is a compact formula for the derivative that can be evaluated easily using Monte Carlo methods. It is applied to the problem of computing the capacity of a finite-state channel (FSC) and, in the high-noise regime, the formula has a simple closed-form expression that enables series expansion of the capacity of a FSC. This expansion is evaluated for a binary-symmetric channel under a (0,1) run-length limited constraint and an intersymbol-interference channel with Gaussian noise.
Directory of Open Access Journals (Sweden)
Kisong Lee
2016-01-01
Full Text Available As miniature-sized embedded computing platforms are ubiquitously deployed to our everyday environments, the issue of managing their power usage becomes important, especially when they are used in energy harvesting based self-organizing networks. One way to provide these devices with continuous power is to utilize RF-based energy transfer. Previous research in RF-based information and energy transfer builds up on the assumption that perfect channel estimation is easily achievable. However, as our preliminary experiments and many previous literature in wireless network systems show, making perfect estimations of the wireless channel is extremely challenging due to their quality fluctuations. To better reflect reality, in this work, we introduce an adaptive power allocation and splitting (APAS scheme which takes imperfect channel estimations into consideration. Our evaluation results show that the proposed APAS scheme achieves near-optimal performances for transferring energy and data over a single RF transmission.
Secret-key Agreement with Channel State Information at the Transmitter
Khisti, Ashish; Wornell, Gregory
2010-01-01
We study the capacity of secret-key agreement over a wiretap channel with state parameters. The transmitter communicates to the legitimate receiver and the eavesdropper over a discrete memoryless wiretap channel with a memoryless state sequence. The transmitter and the legitimate receiver generate a shared secret key, that remains secret from the eavesdropper. No public discussion channel is available. The state sequence is known noncausally to the transmitter. We derive lower and upper bounds on the secret-key capacity. The lower bound involves constructing a common state reconstruction sequence at the legitimate terminals and binning the set of reconstruction sequences to obtain the secret-key. For the special case of Gaussian channels with additive interference (secret-keys from dirty paper channel) our bounds differ by 0.5 bit/symbol and coincide in the high signal-to-noise-ratio and high interference-to-noise-ratio regimes. For the case when the legitimate receiver is also revealed the state sequence, we...
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.
Tang, Bo-Hui; Li, Zhao-Liang; Bi, Yuyun
2009-03-01
This work addressed the estimate of the directional emissivity in the mid-infrared (MIR) channel around 4.0 microm from MODIS data. A series of bidirectional reflectances in MODIS channel 22 (3.97 mum) were retrieved using the method developed by Tang and Li (Int. J. Remote Sens. 29, 4907, 2008) and then were used to estimate the directional emissivity in this channel with the aid of the BRDF model modified by Jiang and Li (Opt. Express 16, 19310, 2008). To validate the estimated directional emissivity, a cross-comparison of MODIS derived emissivities in channel 22 using the proposed method were performed with those provided by the MODIS land surface temperature/emissivity product MYD11B1 data. The results show that the proposed method for estimating the directional emissivity in MIR channel gives results comparable to those of MYD11B1 product with a Mean Error of -0.007 and a Root Mean Square Error of 0.024.
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.
Energy Technology Data Exchange (ETDEWEB)
An, Nguyen Ba, E-mail: nban@iop.vast.ac.vn; Bich, Cao Thi
2014-11-14
We construct a quantum circuit to produce a task-oriented partially entangled state and use it as the quantum channel for controlled joint remote state preparation. Unlike most previous works, where the parameters of the quantum channel are given to the receiver who can accomplish the task only probabilistically by consuming auxiliary resource, operation and measurement, here we give them to the supervisor. Thanks to the knowledge of the task-oriented quantum channel parameters, the supervisor can carry out proper complete projective measurement, which, combined with the feed-forward technique adapted by the preparers, not only much economizes (simplifies) the receiver's resource (operation) but also yields unit total success probability. Notably, such apparent perfection does not depend on the entanglement degree of the shared quantum channel. Our protocol is within the reach of current quantum technologies. - Highlights: • Controlled joint remote state preparation is considered. • Quantum circuit is proposed to produce task-oriented partially entangled channel. • The quantum channel parameter is given to the supervisor (not to the receiver). • Unit success probability without additional resource/operations/measurement. • Perfection is achieved regardless of the shared entanglement degree.
Directory of Open Access Journals (Sweden)
K. Rajeswari
2015-04-01
Full Text Available A novel hybrid channel estimator is proposed for multiple-input multiple-output orthogonal frequency- division multiplexing (MIMO-OFDM system with per-subcarrier transmit antenna selection having optimal power allocation among subcarriers. In practice, antenna selection information is transmitted through a binary symmetric control channel with a crossover probability. Linear minimum mean-square error (LMMSE technique is optimal technique for channel estimation in MIMO-OFDM system. Though LMMSE estimator performs well at low signal to noise ratio (SNR, in the presence of antenna-to-subcarrier-assignment error (ATSA, it introduces irreducible error at high SNR. We have proved that relaxed MMSE (RMMSE estimator overcomes the performance degradation at high SNR. The proposed hybrid estimator combines the benefits of LMMSE at low SNR and RMMSE estimator at high SNR. The vector mean square error (MSE expression is modified as scalar expression so that an optimal power allocation can be performed. The convex optimization problem is formulated and solved to allocate optimal power to subcarriers minimizing the MSE, subject to transmit sum power constraint. Further, an analytical expression for SNR threshold at which the hybrid estimator is to be switched from LMMSE to RMMSE is derived. The simulation results show that the proposed hybrid estimator gives robust performance, irrespective of ATSA error.
Inf-sup estimates for the Stokes problem in a periodic channel
Energy Technology Data Exchange (ETDEWEB)
Wilkening, Jon
2008-12-10
We derive estimates of the Babuska-Brezzi inf-sup constant {beta} for two-dimensional incompressible flow in a periodic channel with one flat boundary and the other given by a periodic, Lipschitz continuous function h. If h is a constant function (so the domain is rectangular), we show that periodicity in one direction but not the other leads to an interesting connection between {beta} and the unitary operator mapping the Fourier sine coefficients of a function to its Fourier cosine coefficients. We exploit this connection to determine the dependence of {beta} on the aspect ratio of the rectangle. We then show how to transfer this result to the case that h is C{sup 1,1} or even C{sup 0,1} by a change of variables. We avoid non-constructive theorems of functional analysis in order to explicitly exhibit the dependence of {beta} on features of the geometry such as the aspect ratio, the maximum slope, and the minimum gap thickness (if h passes near the substrate). We give an example to show that our estimates are optimal in their dependence on the minimum gap thickness in the C{sup 1,1} case, and nearly optimal in the Lipschitz case.
Controllability, not chaos, key criterion for ocean state estimation
Gebbie, Geoffrey; Hsieh, Tsung-Lin
2017-07-01
The Lagrange multiplier method for combining observations and models (i.e., the adjoint method or 4D-VAR) has been avoided or approximated when the numerical model is highly nonlinear or chaotic. This approach has been adopted primarily due to difficulties in the initialization of low-dimensional chaotic models, where the search for optimal initial conditions by gradient-descent algorithms is hampered by multiple local minima. Although initialization is an important task for numerical weather prediction, ocean state estimation usually demands an additional task - a solution of the time-dependent surface boundary conditions that result from atmosphere-ocean interaction. Here, we apply the Lagrange multiplier method to an analogous boundary control problem, tracking the trajectory of the forced chaotic pendulum. Contrary to previous assertions, it is demonstrated that the Lagrange multiplier method can track multiple chaotic transitions through time, so long as the boundary conditions render the system controllable. Thus, the nonlinear timescale poses no limit to the time interval for successful Lagrange multiplier-based estimation. That the key criterion is controllability, not a pure measure of dynamical stability or chaos, illustrates the similarities between the Lagrange multiplier method and other state estimation methods. The results with the chaotic pendulum suggest that nonlinearity should not be a fundamental obstacle to ocean state estimation with eddy-resolving models, especially when using an improved first-guess trajectory.
Controllability, not chaos, key criterion for ocean state estimation
Directory of Open Access Journals (Sweden)
G. Gebbie
2017-07-01
Full Text Available The Lagrange multiplier method for combining observations and models (i.e., the adjoint method or 4D-VAR has been avoided or approximated when the numerical model is highly nonlinear or chaotic. This approach has been adopted primarily due to difficulties in the initialization of low-dimensional chaotic models, where the search for optimal initial conditions by gradient-descent algorithms is hampered by multiple local minima. Although initialization is an important task for numerical weather prediction, ocean state estimation usually demands an additional task – a solution of the time-dependent surface boundary conditions that result from atmosphere–ocean interaction. Here, we apply the Lagrange multiplier method to an analogous boundary control problem, tracking the trajectory of the forced chaotic pendulum. Contrary to previous assertions, it is demonstrated that the Lagrange multiplier method can track multiple chaotic transitions through time, so long as the boundary conditions render the system controllable. Thus, the nonlinear timescale poses no limit to the time interval for successful Lagrange multiplier-based estimation. That the key criterion is controllability, not a pure measure of dynamical stability or chaos, illustrates the similarities between the Lagrange multiplier method and other state estimation methods. The results with the chaotic pendulum suggest that nonlinearity should not be a fundamental obstacle to ocean state estimation with eddy-resolving models, especially when using an improved first-guess trajectory.
Pal, Krishnendu; Gangopadhyay, Gautam
2015-01-01
The kinetics and nonequilibrium thermodynamics of open state and inactive state drug binding mechanisms have been studied here using different voltage protocols in sodium ion channel. We have found that for constant voltage protocol, open state block is more efficient in blocking ionic current than inactive state block. Kinetic effect comes through peak current for mexiletine as an open state blocker and in the tail part for lidocaine as an inactive state blocker. Although the inactivation of sodium channel is a free energy driven process, however, the two different kinds of drug affect the inactivation process in a different way as seen from thermodynamic analysis. In presence of open state drug block, the process initially for a long time remains entropy driven and then becomes free energy driven. However in presence of inactive state block, the process remains entirely entropy driven until the equilibrium is attained. For oscillating voltage protocol, the inactive state blocking is more efficient in damping the oscillation of ionic current. From the pulse train analysis it is found that inactive state blocking is less effective in restoring normal repolarisation and blocks peak ionic current. Pulse train protocol also shows that all the inactive states behave differently as one inactive state responds instantly to the test pulse in an opposite manner from the other two states.
State estimation of connected vehicles using a nonlinear ensemble filter
Institute of Scientific and Technical Information of China (English)
刘江; 陈华展; 蔡伯根; 王剑
2015-01-01
The concept of connected vehicles is with great potentials for enhancing the road transportation systems in the future. To support the functions and applications under the connected vehicles frame, the estimation of dynamic states of the vehicles under the cooperative environments is a fundamental issue. By integrating multiple sensors, localization modules in OBUs (on-board units) require effective estimation solutions to cope with various operation conditions. Based on the filtering estimation framework for sensor fusion, an ensemble Kalman filter (EnKF) is introduced to estimate the vehicle’s state with observations from navigation satellites and neighborhood vehicles, and the original EnKF solution is improved by using the cubature transformation to fulfill the requirements of the nonlinearity approximation capability, where the conventional ensemble analysis operation in EnKF is modified to enhance the estimation performance without increasing the computational burden significantly. Simulation results from a nonlinear case and the cooperative vehicle localization scenario illustrate the capability of the proposed filter, which is crucial to realize the active safety of connected vehicles in future intelligent transportation.
Attention control learning in the decision space using state estimation
Gharaee, Zahra; Fatehi, Alireza; Mirian, Maryam S.; Nili Ahmadabadi, Majid
2016-05-01
The main goal of this paper is modelling attention while using it in efficient path planning of mobile robots. The key challenge in concurrently aiming these two goals is how to make an optimal, or near-optimal, decision in spite of time and processing power limitations, which inherently exist in a typical multi-sensor real-world robotic application. To efficiently recognise the environment under these two limitations, attention of an intelligent agent is controlled by employing the reinforcement learning framework. We propose an estimation method using estimated mixture-of-experts task and attention learning in perceptual space. An agent learns how to employ its sensory resources, and when to stop observing, by estimating its perceptual space. In this paper, static estimation of the state space in a learning task problem, which is examined in the WebotsTM simulator, is performed. Simulation results show that a robot learns how to achieve an optimal policy with a controlled cost by estimating the state space instead of continually updating sensory information.
DEFF Research Database (Denmark)
Zhang, Xu; Pang, Xiaodan; Dogadaev, Anton Konstantinovich
2012-01-01
We experimentally demonstrate high spectrum narrowing tolerant 112-Gb/s QPSK polarization multiplex system based on digital adaptive channel estimation method. The proposed algorithm is able to detect severe spectrum-narrowed signal even with 20GHz 3dB bandwidth.......We experimentally demonstrate high spectrum narrowing tolerant 112-Gb/s QPSK polarization multiplex system based on digital adaptive channel estimation method. The proposed algorithm is able to detect severe spectrum-narrowed signal even with 20GHz 3dB bandwidth....
Forward models and state estimation in compensatory eye movements
Directory of Open Access Journals (Sweden)
Maarten A Frens
2009-11-01
Full Text Available The compensatory eye movement system maintains a stable retinal image, integrating information from different sensory modalities to compensate for head movements. Inspired by recent models of physiology of limb movements, we suggest that compensatory eye movements (CEM can be modeled as a control system with three essential building blocks: a forward model that predicts the effects of motor commands; a state estimator that integrates sensory feedback into this prediction; and, a feedback controller that translates a state estimate into motor commands. We propose a specific mapping of nuclei within the CEM system onto these control functions. Specifically, we suggest that the Flocculus is responsible for generating the forward model prediction and that the Vestibular Nuclei integrate sensory feedback to generate an estimate of current state. Finally, the brainstem motor nuclei – in the case of horizontal compensation this means the Abducens Nucleus and the Nucleus Prepositus Hypoglossi – implement a feedback controller, translating state into motor commands. While these efforts to understand the physiological control system as a feedback control system are in their infancy, there is the intriguing possibility that compensatory eye movements and targeted voluntary movements use the same cerebellar circuitry in fundamentally different ways.
Maximum Correntropy Unscented Kalman Filter for Spacecraft Relative State Estimation
Directory of Open Access Journals (Sweden)
Xi Liu
2016-09-01
Full Text Available A new algorithm called maximum correntropy unscented Kalman filter (MCUKF is proposed and applied to relative state estimation in space communication networks. As is well known, the unscented Kalman filter (UKF provides an efficient tool to solve the non-linear state estimate problem. However, the UKF usually plays well in Gaussian noises. Its performance may deteriorate substantially in the presence of non-Gaussian noises, especially when the measurements are disturbed by some heavy-tailed impulsive noises. By making use of the maximum correntropy criterion (MCC, the proposed algorithm can enhance the robustness of UKF against impulsive noises. In the MCUKF, the unscented transformation (UT is applied to obtain a predicted state estimation and covariance matrix, and a nonlinear regression method with the MCC cost is then used to reformulate the measurement information. Finally, the UT is adopted to the measurement equation to obtain the filter state and covariance matrix. Illustrative examples demonstrate the superior performance of the new algorithm.
Directory of Open Access Journals (Sweden)
Nirmalkumar S. Reshamwala
2014-02-01
Full Text Available Long-Term Evolution (LTE is the next generation of current mobile telecommunication networks. LTE has a ?at radio-network architecture and signi?cant increase in spectrum efficiency, throughput and user capacity. In this paper, performance analysis of robust channel estimators for Downlink Long Term Evolution-Advanced (DL LTE-A system using three Artificial Neural Networks: Feed-forward neural network (FFNN, Cascade-forward neural network (CFNN and Layered Recurrent Neural Network (LRN are trained separately using Back-Propagation Algorithm and also ANN is trained by Genetic Algorithm (GA. The methods use the information got by the received reference symbols to estimate the total frequency response of the channel in two important phases. In the first phase, the proposed ANN based method learns to adapt to the channel variations, and in the second phase it estimates the channel matrix to improve performance of LTE. The performance of the estimation methods is evaluated by simulations in Vienna LTE-A DL Link Level Simulator in MATLAB software. Performance of the proposed channel estimator, ANN trained by Genetic Algorithm (ANN-GA is compared with traditional Least Square (LS algorithm and ANN based other estimator like Feed-forward neural network, Layered Recurrent Neural Network and Cascade-forward neural network for Closed Loop Spatial Multiplexing (CLSM-Single User Multi-input Multi-output (MIMO-2×2 and 4×4 in terms of throughput. Simulation result shows proposed ANN-GA gives better performance than other ANN based estimations methods and LS.
Ling, Jun; Yardibi, Tarik; Su, Xiang; He, Hao; Li, Jian
2009-05-01
The need for achieving higher data rates in underwater acoustic communications leverages the use of multi-input multi-output (MIMO) schemes. In this paper two key issues regarding the design of a MIMO communications system, namely, channel estimation and symbol detection, are addressed. To enhance channel estimation performance, a cyclic approach for designing training sequences and a channel estimation algorithm called the iterative adaptive approach (IAA) are presented. Sparse channel estimates can be obtained by combining IAA with the Bayesian information criterion (BIC). Moreover, the RELAX algorithm can be used to improve the IAA with BIC estimates further. Regarding symbol detection, a minimum mean-squared error based detection scheme, called RELAX-BLAST, which is a combination of vertical Bell Labs layered space-time (V-BLAST) algorithm and the cyclic principle of the RELAX algorithm, is presented and it is shown that RELAX-BLAST outperforms V-BLAST. Both simulated and experimental results are provided to validate the proposed MIMO scheme. RACE'08 experimental results employing a 4 x 24 MIMO system show that the proposed scheme enjoys an average uncoded bit error rate of 0.38% at a payload data rate of 31.25 kbps and an average coded bit error rate of 0% at a payload data rate of 15.63 kbps.
Bellili, Faouzi; Meftehi, Rabii; Affes, Sofiene; Stephenne, Alex
2015-01-01
In this paper, we tackle for the first time the problem of maximum likelihood (ML) estimation of the signal-to-noise ratio (SNR) parameter over time-varying single-input multiple-output (SIMO) channels. Both the data-aided (DA) and the non-data-aided (NDA) schemes are investigated. Unlike classical techniques where the channel is assumed to be slowly time-varying and, therefore, considered as constant over the entire observation period, we address the more challenging problem of instantaneous (i.e., short-term or local) SNR estimation over fast time-varying channels. The channel variations are tracked locally using a polynomial-in-time expansion. First, we derive in closed-form expressions the DA ML estimator and its bias. The latter is subsequently subtracted in order to obtain a new unbiased DA estimator whose variance and the corresponding Cram\\'er-Rao lower bound (CRLB) are also derived in closed form. Due to the extreme nonlinearity of the log-likelihood function (LLF) in the NDA case, we resort to the expectation-maximization (EM) technique to iteratively obtain the exact NDA ML SNR estimates within very few iterations. Most remarkably, the new EM-based NDA estimator is applicable to any linearly-modulated signal and provides sufficiently accurate soft estimates (i.e., soft detection) for each of the unknown transmitted symbols. Therefore, hard detection can be easily embedded in the iteration loop in order to improve its performance at low to moderate SNR levels. We show by extensive computer simulations that the new estimators are able to accurately estimate the instantaneous per-antenna SNRs as they coincide with the DA CRLB over a wide range of practical SNRs.
Full State Estimation for Helicopter Slung Load System
DEFF Research Database (Denmark)
Bisgaard, Morten; la Cour-Harbo, Anders; Bendtsen, Jan Dimon
2007-01-01
This paper presents the design of a state estimator system for a generic helicopter based slung load system. The estimator is designed to deliver full rigid body state information for both helicopter and load and is based on the unscented Kalman filter. Two different approaches are investigated......: One based on a parameter free kinematic model and one based on a full aerodynamic helicopter and slung load model. The kinematic model approach uses acceleration and rate information from two Inertial Measurement Units, one on the helicopter and one on the load, to drive a simple kinematic model....... A simple and effective virtual sensor method is developed to maintain the constraints imposed by the wires in the system. The full model based approach uses a complex aerodynamical model to describe the helicopter together with a generic rigid body model. This rigid body model is based on a redundant...
Full State Estimation for Helicopter Slung Load System
DEFF Research Database (Denmark)
Bisgaard, Morten; la Cour-Harbo, Anders; Bendtsen, Jan Dimon
This paper presents the design of a state estimator system for a generic helicopter based slung load system. The estimator is designed to deliver full rigid body state information for both helicopter and load and is based on the unscented Kalman filter. Two different approaches are investigated......: One based on a parameter free kinematic model and one based on a full aerodynamic helicopter and slung load model. The kinematic model approach uses acceleration and rate information from two Inertial Measurement Units, one on the helicopter and one on the load, to drive a simple kinematic model....... A simple and effective virtual sensor method is developed to maintain the constraints imposed by the wires in the system. The full model based approach uses a complex aerodynamical model to describe the helicopter together with a generic rigid body model. This rigid body model is based on a redundant...
Sea State Estimation Using Model-scale DP Measurements
DEFF Research Database (Denmark)
H. Brodtkorb, Astrid; Nielsen, Ulrik D.; J. Sørensen, Asgeir
2015-01-01
Complex marine operations are moving further from shore, into deeper waters, and harsher environments. The operating hours of a vessel are weather dependent, and good knowledge of the prevailing weather conditions may ensure cost-efficient and safe operations. This paper considers the estimation...... of the peak wave frequency of the on-site sea state based on the vessel’s motion in waves. A sea state can be described by significant wave height, peak wave frequency, wave direction, and often wind speed and direction are added as well. The signal-based algorithm presented in this paper is based on Fourier...... transforms of the vessel response in heave, roll and pitch. The measurements are used directly to obtain an estimate of the peak frequency of the waves. Experimental results from model-scale offshore ship runs at the Marine Cybernetics Laboratory (MCLab) at NTNU demonstrate the performance of the proposed...
Estimating ecosystem carbon stocks at Redwood National and State Parks
van Mantgem, Phillip J.; Madej, Mary Ann; Seney, Joseph; Deshais, Janelle
2013-01-01
Accounting for ecosystem carbon is increasingly important for park managers. In this case study we present our efforts to estimate carbon stocks and the effects of management on carbon stocks for Redwood National and State Parks in northern California. Using currently available information, we estimate that on average these parks’ soils contain approximately 89 tons of carbon per acre (200 Mg C per ha), while vegetation contains about 130 tons C per acre (300 Mg C per ha). estoration activities at the parks (logging-road removal, second-growth forest management) were shown to initially reduce ecosystem carbon, but may provide for enhanced ecosystem carbon storage over the long term. We highlight currently available tools that could be used to estimate ecosystem carbon at other units of the National Park System.
Estimated use of water in the United States in 2005
Kenny, Joan F.; Barber, Nancy L.; Hutson, Susan S.; Linsey, Kristin S.; Lovelace, John K.; Maupin, Molly A.
2009-01-01
Estimates of water use in the United States indicate that about 410 billion gallons per day (Bgal/d) were withdrawn in 2005 for all categories summarized in this report. This total is slightly less than the estimate for 2000, and about 5 percent less than total withdrawals in the peak year of 1980. Freshwater withdrawals in 2005 were 349 Bgal/d, or 85 percent of the total freshwater and saline-water withdrawals. Fresh groundwater withdrawals of 79.6 Bgal/day in 2005 were about 5 percent less than in 2000, and fresh surface-water withdrawals of 270 Bgal/day were about the same as in 2000. Withdrawals for thermoelectric-power generation and irrigation, the two largest uses of water, have stabilized or decreased since 1980. Withdrawals for public-supply and domestic uses have increased steadily since estimates began.
The Degrees of Freedom of the Compound MIMO Broadcast Channels with Finite States
Maddah-Ali, Mohammad Ali
2009-01-01
Multiple-antenna broadcast channels with $M$ transmit antennas and $K$ single-antenna receivers is considered, where the channel of receiver $r$ takes one of the $J_r$ finite values. It is assumed that the channel states of each receiver are randomly selected from $\\mathcal{R}^{M\\times 1}$. It is shown that no matter what $J_r$ is, the degrees of freedom (DoF) of $\\frac{MK}{M+K-1}$ is achievable. The achievable scheme relies on the idea of interference alignment at receivers, without exploiting the possibility of cooperation among transmit antennas. It is proven that if $J_r \\geq M$, $r=1,...,K$, this scheme achieves the optimal DoF. This results implies that when the uncertainty of the base station about the channel realization is considerable, the system loses the gain of cooperation. However, it still benefits from the gain of interference alignment. In fact, in this case, the compound broadcast channel is treated as a compound X channel. Moreover, it is shown that when the base station knows the channel s...
Quantum decoherence time scales for ionic superposition states in ion channels
Salari, V.; Moradi, N.; Sajadi, M.; Fazileh, F.; Shahbazi, F.
2015-03-01
There are many controversial and challenging discussions about quantum effects in microscopic structures in neurons of the brain and their role in cognitive processing. In this paper, we focus on a small, nanoscale part of ion channels which is called the "selectivity filter" and plays a key role in the operation of an ion channel. Our results for superposition states of potassium ions indicate that decoherence times are of the order of picoseconds. This decoherence time is not long enough for cognitive processing in the brain, however, it may be adequate for quantum superposition states of ions in the filter to leave their quantum traces on the selectivity filter and action potentials.
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Sacchi Claudio
2011-01-01
Full Text Available The implementation of efficient baseband receivers characterized by affordable computational load is a crucial point in the development of transmission systems exploiting diversity in different domains. This would be a crucial point in the future development of 4G systems, where space, time, and frequency diversity will be combined together in order to increase system throughput. In this framework, a linear multiuser detector for MC-CDMA systems with Alamouti's Space-Time Block Coding (STBC, which is inspired by the concept of Minimum Conditional Bit Error Rate (MCBER, is proposed. The MCBER combiner has been implemented in adaptive way by using Least-Mean-Square (LMS optimization. The estimation of Channel State Information (CSI, necessary to make practically feasible the MCBER detection, is aided by a Genetic Algorithm (GA. The obtained receiver scheme is near-optimal, as both LMS-based MCBER and GA-assisted channel estimation perform closely to optimum in fulfilling their respective tasks. Simulation results evidenced that the proposed receiver always outperforms state-of-the-art receiver schemes based on EGC and MMSE criterion exploiting the same degree of channel knowledge.