Duality theorems for joint source-channel coding

We consider joint source-channel coding for a memoryless Gaussian source and an additive white Gaussian noise (AWGN) channel. For a given code defined by an encoder-decoder pair (α, β), its dual code is obtained by interchanging the encoder and decoder: (β, α). It is shown that if a code (α, β) is optimal at rate p channel uses per source sample and if it satisfies a certain uniform continuity condition, then its dual code (β, α) is optimal for rate 1/ρ channel uses per source sample. Further, it is demonstrated that there is a code which is optimal but its dual code is not optimal. Finally, using random coding, we show that there is an optimal code which has an optimal dual. The duality concept is also presented for the cases of (i) binary memoryless equiprobable source and binary-symmetric channel (BSC), and (ii) colored Gaussian source and additive colored Gaussian noise (ACGN) channel     

基于深度学习的信源信道联合编码方法综述

信息论的经典结果表明,信源信道分离编码是渐进最优的。但现代通信系统对时延、带宽等愈发敏感,分离设计对解码具有无限计算能力这一假设难以成立。带宽有限时,相对于信源信道联合编码,分离编码已被证明是次优的。传统的联合信源信道编码需要复杂的编码方案,相较之下,数据驱动的深度学习技术则带来了新的设计思路。适时地对相关研究成果进行总结,有助于进一步明确深度学习方法解决信源信道联合编码问题的方式,为研究新的研究方向提供依据。首先介绍了基于深度学习的信源压缩方案和端对端收发信机模型,随后分析不同信源类型下的两种联合编码设计思路,最后探讨了基于深度学习的信源信道联合编码的潜在问题和未来的工作方向。     

A low-complexity rate allocation algorithm for joint source-channel video coding

The problem of enabling robust video transmission over lossy networks has become increasingly important because of the growing interest in video delivery over unreliable channels such as wireless networks. The more the coding process relies on an intensive use of prediction to improve the coding gain, the more the reconstructed sequence proves to be sensitive to information losses. As a matter of fact, it is necessary to introduce some redundant data in order to increase the robustness of the coded bit stream. A possible solution can be found filling a matrix structure with RTP packets and applying a Forward Error Correction (FEC) code on its rows. However, the matrix size and the chosen FEC code affect the performance of the coding system. The paper proposes a novel adaptation technique that tunes the amount of redundant information included in the packet stream and differs from previously proposed solutions since it relies on the percentage of null quantized transform coefficients in place of the activity or the Mean Square Error (MSE). This strategy is then integrated in a joint source-channel coder rate allocation algorithm that shares the available bits between the H.264/AVC coder and the channel coder according to the significance of the frame in the decoding process. Experimental results show that the presented approach significantly improves the quality of the reconstructed sequences at the decoder with respect to activity-based strategies and requires a low computational complexity.     

Robust image transmission over energy-constrained time-varyingchannels using multiresolution joint source-channel coding

We explore joint source-channel coding (JSCC) for time-varying channels using a multiresolution framework for both source coding and transmission via novel multiresolution modulation constellations. We consider the problem of still image transmission over time-varying channels with the channel state information (CSI) available at (1) receiver only and (2) both transmitter and receiver being informed about the state of the channel, and we quantify the effect of CSI availability on the performance. Our source model is based on the wavelet image decomposition, which generates a collection of subbands modeled by the family of generalized Gaussian distributions. We describe an algorithm that jointly optimizes the design of the multiresolution source codebook, the multiresolution constellation, and the decoding strategy of optimally matching the source resolution and signal constellation resolution “trees” in accordance with the time-varying channel and show how this leads to improved performance over existing methods. The real-time operation needs only table lookups. Our results based on a wavelet image representation show that our multiresolution-based optimized system attains gains on the order of 2 dB in the reconstructed image quality over single-resolution systems using channel optimized source coding     

On the joint source-channel coding error exponent for discrete memoryless systems

We investigate the computation of Csisza/spl acute/r's bounds for the joint source-channel coding (JSCC) error exponent E/sub J/ of a communication system consisting of a discrete memoryless source and a discrete memoryless channel. We provide equivalent expressions for these bounds and derive explicit formulas for the rates where the bounds are attained. These equivalent representations can be readily computed for arbitrary source-channel pairs via Arimoto's algorithm. When the channel's distribution satisfies a symmetry property, the bounds admit closed-form parametric expressions. We then use our results to provide a systematic comparison between the JSCC error exponent E/sub J/ and the tandem coding error exponent E/sub T/, which applies if the source and channel are separately coded. It is shown that E/sub T//spl les/E/sub J//spl les/2E/sub T/. We establish conditions for which E/sub J/>E/sub T/ and for which E/sub J/=2E/sub T/. Numerical examples indicate that E/sub J/ is close to 2E/sub T/ for many source-channel pairs. This gain translates into a power saving larger than 2 dB for a binary source transmitted over additive white Gaussian noise (AWGN) channels and Rayleigh-fading channels with finite output quantization. Finally, we study the computation of the lossy JSCC error exponent under the Hamming distortion measure.     

基于纠错算术码的信源信道自适应联合编解码系统

对信源信道自适应联合编码方法进行了研究,提出了一种新的基于纠错算术码的联合信源信道编解码系统。该系统在编码端利用算术码内嵌禁用符号实现信源信道一体式编码,即利用马尔科夫信源模型和根据信道状态信息自适应地调整禁用符号概率大小从而调整编码码率来实现信道自适应;在解码端,推导出了基于MAP的解码测度数学公式并基于此测度公式提出了一种改进的堆栈序列估计算法。与传统的信道自适应编码算法不同,该自适应编码算法只需调整一个参数:禁用符号,且理论上可获得连续可变的编码码率。实验结果表明,与经典的Grangetto联合编码系统以及分离编码系统相比,所提出的编码系统具有明显改善的性能增益。     

On joint source-channel coding for the Wyner-Ziv source and the Gel'fand-Pinsker channel

We consider the problem of lossy joint source-channel coding in a communication system where the encoder has access to channel state information (CSI) and the decoder has access to side information that is correlated to the source. This configuration combines the Wyner-Ziv (1976) model of pure lossy source coding with side information at the decoder and the Shannon/Gel'fand-Pinsker (1958, 1980) model of pure channel coding with CSI at the encoder. We prove a separation theorem for this communication system, which asserts that there is no loss in asymptotic optimality in applying, first, an optimal Wyner-Ziv source code and, then, an optimal Gel'fand-Pinsker channel code. We then derive conditions for the optimality of a symbol-by-symbol (scalar) source-channel code, and demonstrate situations where these conditions are met. Finally, we discuss a few practical applications, including overlaid communication where the model under discussion is useful.     

一种基于JPEG2000的自适应联合信源信道编码方法

针对JPEG2000图像在噪声条件未知的信道上有效和可靠传输问题,本文提出了一种基于反馈的自适应联合信源信道编码方案.首先采用基于子空间的信噪比估计方法实时估计信道的信噪比SNR,进而求得信道的误码率,解决了对信道的自适应问题.其次,充分利用了JPEG2000的码流质量分级特点,建立了实用的目标函数,从而根据数据包对重建图像贡献的不同,实施不同的保护,以低复杂度的运算实现了码率优化分配的自适应过程.仿真结果表明,和现有的联合信源信道编码算法相比,这种自适应联合优化编码方法可以取得较好的效果.     

Combined source-channel coding using turbo-codes

The authors present a new approach to combined source-channel coding based on using the reliability information available from the turbo-code channel decoder. Numerical results are presented for the transmission of the DCT coefficients of still images showing a noticeable improvement with respect to an ordinary, as well as a channel optimised quantiser     

Toward a unified framework for modeling and analysis of diversity in joint source-channel coding

The study of joint source-channel coding (JSCC) systems faces one major challenge in obtaining an analytical expression for the function that links end-to-end distortion with channel signal-to-noise ratio, the D-SNR curve. In this paper, for certain multimedia systems using practical source and channel codes in a JSCC bit rate allocation design, the D-SNR curve is shown to be well approximated by a set of carefully selected points where the relative contribution of channel errors to end-to-end distortion is small. This approach has the potential advantage that it could be applied to represent performance of many practical systems using JSCC bit rate allocation for which it is shown that the D-SNR function is approximately linear in log-log scales. A unified framework for the modeling, analysis and performance measurement of these systems is proposed by considering a view of diversity more general than its usual interpretation. This view extends that of diversity to include redundant information so coding and diversity gain are still used to characterize performance. Furthermore, the proposed approach is applied to study issues arising from using practical source and channel codes, including the effects on performance of channel codes of different strength or source codes with different compression efficiency.     

Adaptive source-channel subband video coding for wireless channels

This paper presents a general framework for combined source-channel coding within the context of subband coding. The unequal importance of subbands in reconstruction of the source is exploited by an appropriate allocation of source and channel coding rates for the coding and transmission of subbands over a noisy channel. For each subband, the source coding rate as well as the level of protection (quantified by the channel coding rate) are jointly chosen to minimize the total end-to-end mean-squared distortion suffered by the source. This allocation of source and channel coding rates is posed as a constrained optimization problem, and solved using a generalized bit allocation algorithm. The optimal choice of source and channel coding rates depends on the state of the physical channel. These results are extended to transmission over fading channels using a finite state model, where every state corresponds to an additive white Gaussian noise (AWGN) channel. A coding strategy is also developed that minimizes the average distortion when the channel state is unavailable at the transmitter. Experimental results are provided that demonstrate application of these combined source-channel coding strategies on video sequences     

Joint source-channel turbo coding for binary Markov sources

We investigate the construction of joint source-channel (JSC) turbo codes for the reliable communication of binary Markov sources over additive white Gaussian noise and Rayleigh fading channels. To exploit the source Markovian redundancy, the first constituent turbo decoder is designed according to a modified version of Berrou's original decoding algorithm that employs the Gaussian assumption for the extrinsic information. Due to interleaving, the second constituent decoder is unable to adopt the same decoding method; so its extrinsic information is appropriately adjusted via a weighted correction term. The turbo encoder is also optimized according to the Markovian source statistics and by allowing different or asymmetric constituent encoders. Simulation results demonstrate substantial gains over the original (unoptimized) Turbo codes, hence significantly reducing the performance gap to the Shannon limit. Finally, we show that our JSC coding system considerably outperforms tandem coding schemes for bit error rates smaller than 10/sup -4/, while enjoying a lower system complexity.     

Optimized error protection of scalable image bit streams [advances in joint source-channel coding for images]

This article focuses on FEC for scalable image coders. For various channel models, we survey recent progress made in system design and discuss efficient source-channel bit allocation techniques, with emphasis on unequal error protection. This article considered JSCC (joint source-channel coding) at the application layer only. Recent research has studied cross-layer optimization where JSCC is applied to both the application layer and the physical layer. The basic task here is to minimize the average distortion by allocating available power, subcarriers, and bandwidth among users at the physical layer and source-channel symbols at the application layer subject to a total resource constraint. Most of the JSCC systems covered in this article can be readily extended to transmit scalable compressed bit streams of video sequences and 3-D meshes. Due to the stringent delay constraints in video communications and the fact that MPEG is currently exploring a scalable video coding standard, fast JSCC algorithms are expected to play a bigger role and bring more performance gains. This article is also expected to stimulate further research efforts into JSCC and more importantly, prompt the industry to adopt some of these JSCC algorithms in their system designs, thus closing the cycle from algorithm development to implementation.     

噪声信道中基于残留冗余的联合信源信道编码.

对信源编码中的残留冗余在联合编码中的作用进行了研究，提出了一个在噪声信道中对可变长信源编码码流传输提供有效差错保护的联合信源信道编码方法，该方法利用信源编码器输出中的残留冗余为传输码流提供差错保护。与Sayood K提出的系统相比，该方法是基于改进的联合卷积软解码以及采用非霍夫曼码的通用可变长码，更接近于一般的信源和信道编码方法，并且信源符号集的大小也不受限制。仿真表明，所提出的联合编码方法可获得比传统的分离编码方法更高的性能增益。     

Correlated sources over wireless channels: cooperative source-channel coding

We consider wireless sensor networks deployed to observe arbitrary random fields. The requirement is to reconstruct an estimate of the random field at a certain collector node. This creates a many-to-one data gathering wireless channel. One of the main challenges in this scenario is that the source/channel separation theorem, proved by Shannon for point-to-point links, does not hold any more. In this paper, we construct novel cooperative source-channel coding schemes that exploit the wireless channel and the correlation between the sources. In particular, we differentiate between two distinct cases. The first case assumes that the sensor nodes are equipped with receivers and, hence, every node can exploit the wireless link to distribute its information to its neighbors. We then devise an efficient deterministic cooperation strategy where the neighboring nodes act as virtual antennas in a beamforming configuration. The second, and more challenging, scenario restricts the capability of sensor nodes to transmit only. In this case, we argue that statistical cooperative source-channel coding techniques still yield significant performance gains in certain relevant scenarios. Specifically, we propose a low complexity cooperative source-channel coding scheme based on the proper use of low-density generator matrix codes. This scheme is shown to outperform the recently proposed joint source-channel coding scheme (Garcia-Frias et al., 2002) in the case of highly correlated sources. In both the deterministic and statistical cooperation scenarios, we develop analytical results that guide the optimization of the proposed schemes and validate the performance gains observed in simulations.     

噪声信道中基于残留冗余的联合信源信道编码

对信源编码中的残留冗余在联合编码中的作用进行了研究,提出了一个在噪声信道中对可变长信源编码码流传输提供有效差错保护的联合信源信道编码方法,该方法利用信源编码器输出中的残留冗余为传输码流提供差错保护。与SayoodK提出的系统相比,该方法是基于改进的联合卷积软解码以及采用非霍夫曼码的通用可变长码,更接近于一般的信源和信道编码方法,并且信源符号集的大小也不受限制。仿真表明,所提出的联合编码方法可获得比传统的分离编码方法更高的性能增益。     

Joint source-channel (de-)coding for mobile communications

Real world source coding algorithms usually leave a certain amount of redundancy within the coded bit stream. Shannon (1948) already mentioned that this redundancy can be exploited at the receiver side to achieve a higher robustness against channel errors. We show how joint source-channel decoding can be performed in a way that is applicable to any mobile communication system standard. Considerable gains in terms of bit error rate or signal-to-noise ratio (SNR) are possible dependent on the amount of redundancy. However, an even better performance can be achieved by changing also the transmitter sided source and channel encoders. We propose an encoding concept employing low-dimensional quantization. Keeping the gross bit rate as well as the clean channel quality the same, it decreases the complexity of the source encoder and the decoder significantly. Finally, we give an application of our methods to spectral coefficient coding in speech transmission over a Rayleigh fading channel resulting in channel SNR gains of about 2 dB as compared to state-of-the-art (de-)coding and bad frame handling methods     

Joint source-channel coding and guessing with application tosequential decoding

We extend our earlier work on guessing subject to distortion to the joint source-channel coding context. We consider a system in which there is a source connected to a destination via a channel and the goal is to reconstruct the source output at the destination within a prescribed distortion level with respect to (w.r.t.) some distortion measure. The decoder is a guessing decoder in the sense that it is allowed to generate successive estimates of the source output until the distortion criterion is met. The problem is to design the encoder and the decoder so as to minimize the average number of estimates until successful reconstruction. We derive estimates on nonnegative moments of the number of guesses, which are asymptotically tight as the length of the source block goes to infinity. Using the close relationship between guessing and sequential decoding, we give a tight lower bound to the complexity of sequential decoding in joint source-channel coding systems, complementing earlier works by Koshelev (1973) and Hellman (1975). Another topic explored here is the probability of error for list decoders with exponential list sizes for joint source-channel coding systems, for which we obtain tight bounds as well. It is noteworthy that optimal performance w.r.t. the performance measures considered here can be achieved in a manner that separates source coding and channel coding     

结合残留冗余信息与MMSE估计的信源信道联合编解码

文中提出一种利用残留冗余的RDPCM信源信道联合编码系统与最小均方误差估计结合的方法.首先,本文针对联合编码系统修正了SOVA算法,在接收端获得利用残留冗余后的比特似然度;然后利用这些后验信息,对信源预测编码器的输出符号值进行最小均方误差重建后再进行信源译码,从而减小了由于硬判决得到符号值所带来的失真.仿真结果显示这种算法在信噪比的低端最大得到了约2dB的增益.