Joint Source–Channel Communication for Distributed Estimation in Sensor Networks

Power and bandwidth are scarce resources in dense wireless sensor networks and it is widely recognized that joint optimization of the operations of sensing, processing and communication can result in significant savings in the use of network resources. In this paper, a distributed joint source-channel communication architecture is proposed for energy-efficient estimation of sensor field data at a distant destination and the corresponding relationships between power, distortion, and latency are analyzed as a function of number of sensor nodes. The approach is applicable to a broad class of sensed signal fields and is based on distributed computation of appropriately chosen projections of sensor data at the destination - phase-coherent transmissions from the sensor nodes enable exploitation of the distributed beamforming gain for energy efficiency. Random projections are used when little or no prior knowledge is available about the signal field. Distinct features of the proposed scheme include: (1) processing and communication are combined into one distributed projection operation; (2) it virtually eliminates the need for in-network processing and communication; (3) given sufficient prior knowledge about the sensed data, consistent estimation is possible with increasing sensor density even with vanishing total network power; and (4) consistent signal estimation is possible with power and latency requirements growing at most sublinearly with the number of sensor nodes even when little or no prior knowledge about the sensed data is assumed at the sensor nodes.     

Joint Source–Channel Codes for MIMO Block-Fading Channels

We consider transmission of a continuous amplitude source over an L-block Rayleigh-fading M_t x M_r multiple-input multiple-output (MIMO) channel when the channel state information is only available at the receiver. Since the channel is not ergodic, Shannon's source-channel separation theorem becomes obsolete and the optimal performance requires a joint source-channel approach. Our goal is to minimize the expected end-to-end distortion, particularly in the high signal-to-noise ratio (SNR) regime. The figure of merit is the distortion exponent, defined as the exponential decay rate of the expected distortion with increasing SNR. We provide an upper bound and lower bounds for the distortion exponent with respect to the bandwidth ratio among the channel and source bandwidths. For the lower bounds, we analyze three different strategies based on layered source coding concatenated with progressive superposition or hybrid digital/analog transmission. In each case, by adjusting the system parameters we optimize the distortion exponent as a function of the bandwidth ratio. We prove that the distortion exponent upper bound can be achieved when the channel has only one degree of freedom, that is L = 1, and min{M_t ,M_r} =1. When we have more degrees of freedom, our achievable distortion exponents meet the upper bound for only certain ranges of the bandwidth ratio. We demonstrate that our results, which were derived for a complex Gaussian source, can be extended to more general source distributions as well.     

Joint Source–Channel Turbo Techniques for Discrete-Valued Sources: From Theory to Practice

The principles which have been prevailing so far for designing communication systems rely on Shannon's source and channel coding separation theorem. This theorem states that source and channel optimum performance bounds can be approached as close as desired by designing independently the source and channel coding strategies. However, this theorem holds only under asymptotic conditions, where both codes are allowed infinite length and complexity. If the design of the system is constrained in terms of delay and complexity, if the sources are not stationary, or if the channels are nonergodic, separate design and optimization of the source and channel coders can be largely suboptimal. For practical systems, joint source-channel (de)coding may reduce the end-to-end distortion. It is one of the aspects covered by the term cross-layer design, meaning a rethinking of the layer separation principle. This article focuses on recent developments of joint source-channel turbo coding and decoding techniques, which are described in the framework of normal factor graphs. The scope is restricted to lossless compression and discrete-valued sources. The presented techniques can be applied to the quantized values of a lossy source codec but the quantizer itself and its impact are not considered.     

Error Exponents for Channel Coding With Application to Signal Constellation Design

This paper concerns error exponents and the structure of input distributions maximizing the random coding exponent for a stochastic channel model. The following conclusions are obtained under general assumptions on the channel statistics. 1) The optimal distribution has a finite number of mass points, or in the case of a complex channel, the amplitude has finite support. 2) A new class of algorithms is introduced based on the cutting-plane method to construct an optimal input distribution. The algorithm constructs a sequence of discrete distributions, along with upper and lower bounds on the random coding exponent at each iteration. 3) In some numerical example considered, the resulting code significantly outperforms traditional signal constellation schemes such as quadrature amplitude modulation and phase-shift keying for all rates below the capacity.     

Random-Coding Lower Bounds for the Error Exponent of Joint Quantization and Watermarking Systems

We establish random-coding lower bounds to the error exponent of discrete and Gaussian joint quantization and private watermarking systems. In the discrete system, both the covertext and the attack channel are memoryless and have finite alphabets. In the Gaussian system, the covertext is memoryless Gaussian and the attack channel has additive memoryless Gaussian noise. In both cases, our bounds on the error exponent are positive in the interior of the achievable quantization and watermarking rate region.     

Antenna Selection for MIMO-OFDM Systems With Channel Estimation Error

We study space–time–frequency coded multiple-input–multiple-output (MIMO) orthogonal frequency-division multiplexed (OFDM) systems employing receiver antenna selection (AS), where training has been utilized to perform linear minimum mean square error (LMMSE)-based channel estimation. To minimize the mean square error (MSE) of this estimator, equispaced and equipowered training symbols are used, with the number of training symbols per OFDM symbol equal to the channel length. The maximum received signal power AS rule is proposed, which decouples the AS process from the channel estimation process. By upper bounding the pairwise error probability (PEP) expression, we show that the system with a channel-estimation error (CEE) still achieves maximum spatial and multipath diversity. The performance of the system for the special case of square unitary and orthogonal codes has been analyzed. For the case of orthogonal codes using constant modulus symbols, we also derive the exact bit-error-rate (BER) expression. The degradation in performance, due to the presence of the CEE, is captured by the loss-in-coding-gain (LCG) and loss-in-performance (LP) expressions. To minimize the loss due to the CEE, an optimal power-allocation scheme that distributes the total available power between training symbols and data symbols is defined. Compared with the perfect channel knowledge case, equal power training for the CEE case performs at least 3 dB worse, whereas optimal power training for the CEE case suffers a loss less than 3 dB always. Analytical and simulation results are presented to validate our analysis and results.      

Universal Zero-Delay Joint Source–Channel Coding

We consider zero-delay joint source-channel coding of individual source sequences for a general known channel. Given an arbitrary finite set of schemes with finite-memory (not necessarily time-invariant) decoders, a scheme is devised that does essentially as well as the best in the set on all individual source sequences. Using this scheme, we construct a universal zero-delay joint source-channel coding scheme that is guaranteed to achieve, asymptotically, the performance of the best zero-delay encoding-decoding scheme with a finite-state encoder and a Markov decoder, on all individual sequences. For the case where the channel is a discrete memoryless channel (DMC), we construct an implementable zero-delay joint source-channel coding scheme that is based on the "follow the perturbed leader" scheme of Gyoumlrgy for lossy source coding of individual sequences. Our scheme is guaranteed to attain asymptotically the performance of the best in the set of all encoding-decoding schemes with a "symbol-by-symbol" decoder (and arbitrary encoder), on all individual sequences     

离散马尔可夫跳变系统的降维观测器设计

针对一类含有未知输入和测量噪声的线性离散时间马尔可夫跳变系统,设计了一种降维观测器,可以对系统中的未知输入和测量噪声同时解耦.以线性矩阵不等式的形式给出观测器存在的充分条件,并确保误差系统有限时间随机稳定;之后利用一种代数重构的思想实现了未知输入的估计;最后通过数值仿真验证了所提方法的有效性.     

第四代移动通信系统中的信源信道联合编码技术

本文介绍了未来第四代移动通信系统中可能的联合编码框架,在分析基于小波变换的SPIHT算法和Turbo编 码算法的基础上,给出了一种改进的无线传输系统结构。仿真结果表明,这种利用信源特性进行信道编译码的方法能够有效 地降低时延,提高信道编码的纠错性能,适合于未来多媒体无线传输业务的需求。     

Channel Error Recovery for Transform Image Coding

A method is presented to automatically inspect the block boundaries of a reconstructed two-dimensional transform coded image, to locate blocks which are most likely to contain errors, to approximate the size and type of error in the block, and to eliminate this estimated error from the picture. This method uses redundancy in the source data to provide channel error correction. No additional channel error protection bits or changes to the transmitter are required. It can be used when channel errors are unexpected prior to reception.     

一种新的信源、信道编码和差错隐藏的联合优化方法

本文提出了一种基于广义的率失真函数的信源编码,信道编码和差错隐藏联合优化的方法.这种广义的率失真函数综合反映了视频信源经信源编码,信道编码,差错隐藏后的率失真特性,因此可以用来进行视频通信系统收发端的联合优化.仿真结果表明,和传统的信源信道联合编码算法相比,这种基于广义的率失真特性的联合优化可以取得更好的结果.     

Low Complexity Minimum Mean Square Error Channel Estimation for Adaptive Coding and Modulation Systems

Performance of the Adaptive Cod- ing and Modulation （ACM） strongly depends on the retrieved Channel State Information （CSI）, which can be obtained using the chan- nel estimation techniques relying on pilot sy- mbol transmission. Earlier analysis of methods of pilot-aided channel estimation for ACM systems were relatively little. In this paper, we investigate the performance of CSI prediction using the Minimum Mean Square Error （MMSE） channel estimator for an ACM system. To solve the two problems of MMSE： high compu- tational operations and oversimplified assum- ption, we then propose the Low-Complexity schemes （LC-MMSE and Recursion LC-MMSE （R-LC-MMSE））. Computational complexity and Mean Square Error （MSE） are presented to evaluate the efficiency of the proposed algo- rithm. Both analysis and numerical results sh- ow that LC-MMSE performs close to the well- known MMSE estimator with much lower com- plexity and R-LC-MMSE improves the appli- cation of MMSE estimation to specific cir- cumstances.     

基于分布式空频码的协作通信系统的信道估计及优化

该文研究了协作通信中分布式空频码系统的信道估计问题。为使信道可辨识,在中继节点处加入了循环卷积滤波器(CCF)。推导了训练模式中导频序列和中继节点处CCF的准最优设计方案,并由此得到了源节点与中继节点之间功率分配的闭合表达式。计算机仿真验证了本文工作的有效性。     

航空通信系统中信道编码理论及应用分析

一般地,航空通信系统具有功率受限、带宽受限、时延受限的特点。针对航空通信系统对信道编码高增益和低时延的要求,首先理论推导通信系统(特别是二进制通信系统)应用r码率信道编码获得编码增益的香农极限值,并仿真对比分析几类典型信道编码的编码性能,最后结合工程实现考虑的技术指标对几类信道编码的应用范围进行了定性分析,其对航空通信系统的信道编码选取具有工程指导意义。     

Pilot-Based LMMSE Channel Estimation for OFDM Systems With Power–Delay Profile Approximation

In linear-minimum-mean-square-error (LMMSE) channel estimation for multicarrier systems, one needs to know the channel correlation function. This poses a problem for systems with a small number of pilots operating in time-varying channels. We propose to approximate the channel power–delay profile (PDP) with a shape that can completely be described in two parameters, namely, the mean delay and the root-mean-square (RMS) delay spread. Furthermore, we develop a simple technique to estimate these delay parameters. The approximate PDP is then used to generate the LMMSE filter coefficients for data-subcarrier channel estimation. Mathematical expressions are derived that can be used to predict the accuracy of the various estimates, and they are verified by simulation. The proposed technique is applicable to both point-to-point communication and multiaccess communication where different users may experience different channel conditions. As a practical application, we also specialize the proposed technique to Mobile WiMAX signals and investigate the resulting performance.      

Error Rate Estimates in Digital Communication Over a Nonlinear Channel with Memory

The principal representations of Krein are known to provide very tight upper and lower bounds on the error probability in digital communication over a linear channel with intersymbol interference. These bounds depend on the signal-to-noise ratio, the amount of intersymbol interference, and the number of moments of the random interference variable. The same technique can be applied to a nonlinear channel with memory. However, it is difficult to calculate these moments when the channel is nonlinear and has memory. In this paper, we describe a method for computing the moments for the case of an arbitrary nonlinear channel with finite memory. The method of Krein is then used to evaluate the error probability from the moments obtained. We demonstrate the technique with two examples. The model of the nonlinear channel consists of a linear filter in cascade with a memoryless nonlinearity followed by another linear filter. If a sufficient number of moments are used, we obtain accurate estimates of the true error probability.     

Joint Data Detection and Channel Tracking for OFDM Systems With Phase Noise

This paper addresses the problem of data detection in orthogonal frequency division multiplexing (OFDM) systems operating under a time-varying multipath fading channel. Optimal detection in such a scenario is infeasible, which makes the introduction of approximations necessary. The typical joint data-channel estimators are decision directed, that is, assume perfect past data decisions. However, their performance is subject to error propagation phenomena. The variational Bayes method is employed here, which approximates the joint data and channel distribution as a separable one, greatly simplifying the problem. The data detection part of the resulting algorithm provides soft data estimates that are used for channel tracking. The channel itself is modeled as an autoregressive process allowing for a Kalman-like tracking algorithm. According to the developed algorithm, both data and channel estimates are exchanged and updated in an iterative manner. The performance of the proposed algorithm is evaluated by simulations. Furthermore, since OFDM is extremely sensitive to the presence of phase noise, the algorithm is extended to operate under severe phase noise conditions, with moderate performance degradation.      

联合信源信道编码的原理及其在无线通信中的应用

根据香农信源和信道分离编码理论进行的分离信源和信道编码在时变信道时不能充分利用系统资源。正是在这种情况下 ,提出了信源信道联合编码 ,可以跟随信道的变化充分利用通信系统的资源 ,达到最好的端对端的通信效果。本文首先阐述了联合信源信道编码的原理 ,然后介绍了常用的实现方法 ,最后 ,提出了在设计联合信源信道编码系统时的改进方法。     

On the Distortion SNR Exponent of Hybrid Digital–Analog Space–Time Coding

We consider the transmission of a real independent and identically distributed (i.i.d.) "analog" source over a quasi-static M-input N-output multiple-input multiple-output (MIMO) block-fading channel. The relevant performance criterion is end-to-end average quadratic distortion D versus channel signal-to-noise ratio (SNR), for given spectral efficiency eta, defined as the ratio of the source bandwidth over the channel bandwidth. In the limit of high SNR, we define the distortion SNR exponent a*(eta) as the largest a such that D esdot snr^-a, over all possible source-channel coding schemes of spectral efficiency eta. We find a simple upper bound on a*(eta), an achievable lower bound a_sep(eta) achievable by separated (tandem) source-channel coding, and a tighter lower bound a_hybrid(eta) achievable by new hybrid digital analog space-time coding schemes. As a corollary, we have that a*(eta) is completely determined for the scalar case M = N = 1 and for the "bandwidth compression" case eta ges 2 min{M, N}. Expiicit and simple construction of hybrid space-time codes achieving a_hybrid(eta) are also given.