Joint Source Channel Decoding

Treats joint source and channel decoding in an integrated way Gives a clear description of the problems in the field together with the mathematical tools for their solution Contains many detailed examples useful for practical applications of the theory to video broadcasting over mobile and wireless networks Traditionally, cross-layer and joint source-channel coding were seen as incompatible with classically structured networks but recent advances in theory changed this situation. Joint source-channel decoding is now seen as a viable alternative to separate decoding of source and channel codes, if the protocol layers are taken into account. A joint source/protocol/channel approach is thus addressed in this book: all levels of the protocol stack are considered, showing how the information in each layer influences the others. This book provides the tools to show how cross-layer and joint source-channel coding and decoding are now compatible with present-day mobile and wireless networks, with a particular application to the key area of video transmission to mobiles. Typical applications are broadcasting, or point-to-point delivery of multimedia contents, which are very timely in the context of the current development of mobile services such as audio (MPEG4 AAC) or video (H263, H264) transmission using recent wireless transmission standards (DVH-H, DVB-SH, WiMAX, LTE). This cross-disciplinary book is ideal for graduate students, researchers, and more generally professionals working either in signal processing for communications or in networking applications, interested in reliable multimedia transmission. This book is also of interest to people involved in cross-layer optimization of mobile networks. Its content may provide them with other points of view on their optimization problem, enlarging the set of tools which they could use. Pierre Duhamel is director of research at CNRS/ LSS and has previously held research positions at Thomson-CSF, CNET, and ENST, where he was head of the Signal and Image Processing Department. He has served as chairman of the DSP committee and associate Editor of the IEEE Transactions on Signal Processing and Signal Processing Letters, as well as acting as a co-chair at MMSP and ICASSP conferences. He was awarded the Grand Prix France Telecom by the French Science Academy in 2000. He is co-author of more than 80 papers in international journals, 250 conference proceedings, and 28 patents. Michel Kieffer is an assistant professor in signal processing for communications at the Université Paris-Sud and a researcher at the Laboratoire des Signaux et Systèmes, Gif-sur-Yvette, France. His research interests are in joint source-channel coding and decoding techniques for the reliable transmission of multimedia contents. He serves as associate editor of Signal Processing (Elsevier). He is co-author of more than 90 contributions to journals, conference proceedings, and book chapters. Treats joint source and channel decoding in an integrated way Gives a clear description of the problems in the field together with the mathematical tools for their solution Contains many detailed examples useful for practical applications of the theory to video broadcasting over mobile and wireless networks

This book provides the first comprehensive and easy-to-read discussion of joint source-channel encoding and decoding for source signals with continuous amplitudes. It is a state-of-the-art presentation of this exciting, thriving field of research, making pioneering contributions to the new concept of source-adaptive modulation. The book starts with the basic theory and the motivation for a joint realization of source and channel coding. Specialized chapters deal with practically relevant scenarios such as iterative source-channel decoding and its optimization for a given encoder, and also improved encoder designs by channel-adaptive quantization or source-adaptive modulation. Although Information Theory is not the main topic of the book OCo in fact, the concept of joint source-channel coding is contradictory to the classical system design motivated by a questionable practical interpretation of the separation theorem OCo this theory still provides the ultimate performance limits for any practical system, whether it uses joint source-channel coding or not. Therefore, the theoretical limits are presented in a self-contained appendix, which is a useful reference also for those not directly interested in the main topic of this book. Sample Chapter(s). Chapter 1: Introduction (98 KB). Contents: Joint Source-Channel Coding: An Overview; Joint Source-Channel Decoding; Channel-Adaptive Scaled Vector Quantization; Index Assignments for Multiple Descriptions Vector Quantizers; Source-Adaptive Modulation; Source-Adaptive Power Allocation; Appendices: Theoretical Performance Limits; Optimal Decoder for a Given Encoder; Symbol Error Probabilities for M-PSK; Derivative of the Expected Distortion for SAM. Readership: Students at advanced undergraduate and graduate level; practitioners and academics in Electrical and Communications Engineering, Information Technology and Computer Science."

Based on the encoding process, arithmetic codes can be viewed as tree codes and current proposals for decoding arithmetic codes with forbidden symbols belong to sequential decoding algorithms and their variants. In this monograph, we propose a new way of looking at arithmetic codes with forbidden symbols. If a limit is imposed on the maximum value of a key parameter in the encoder, this modified arithmetic encoder can also be modeled as a finite state machine and the code generated can be treated as a variable-length trellis code. The number of states used can be reduced and techniques used for decoding convolutional codes, such as the list Viterbi decoding algorithm, can be applied directly on the trellis. The finite state machine interpretation can be easily migrated to Markov source case. We can encode Markov sources without considering the conditional probabilities, while using the list Viterbi decoding algorithm which utilizes the conditional probabilities. We can also use context-based arithmetic coding to exploit the conditional probabilities of the Markov source and apply a finite state machine interpretation to this problem. The finite state machine interpretation also allows us to more systematically understand arithmetic codes with forbidden symbols. It allows us to find the partial distance spectrum of arithmetic codes with forbidden symbols. We also propose arithmetic codes with memories which use high memory but low implementation precision arithmetic codes. The low implementation precision results in a state machine with less complexity. The introduced input memories allow us to switch the probability functions used for arithmetic coding. Combining these two methods give us a huge parameter space of the arithmetic codes with forbidden symbols. Hence we can choose codes with better distance properties while maintaining the encoding efficiency and decoding complexity. A construction and search method is proposed and simulation results show that we can achieve a similar performance as turbo codes when we apply this approach to rate 2/3 arithmetic codes. Table of Contents: Introduction / Arithmetic Codes / Arithmetic Codes with Forbidden Symbols / Distance Property and Code Construction / Conclusion

Consolidating knowledge on Joint Source-Channel Coding (JSCC), this book provides an indispensable resource on a key area of performance enhancement for communications networks Presenting in one volume the key theories, concepts and important developments in the area of Joint Source-Channel Coding (JSCC), this book provides the fundamental material needed to enhance the performance of digital and wireless communication systems and networks. It comprehensively introduces JSCC technologies for communications systems, including coding and decoding algorithms, and emerging applications of JSCC in current wireless communications. The book covers the full range of theoretical and technical areas before concluding with a section considering recent applications and emerging designs for JSCC. A methodical reference for academic and industrial researchers, development engineers, system engineers, system architects and software engineers, this book: Explains how JSCC leads to high performance in communication systems and networks Consolidates key material from multiple disparate sources Is an ideal reference for graduate-level courses on digital or wireless communications, as well as courses on information theory Targets professionals involved with digital and wireless communications and networking systems

Joint Source-Channel Coding Consolidating knowledge on Joint Source-Channel Coding (JSCC), this book provides an indispensable resource on a key area of performance enhancement for communications networks Presenting in one volume the key theories, concepts and important developments in the area of Joint Source-Channel Coding (JSCC), this book provides the fundamental material needed to enhance the performance of digital and wireless communication systems and networks. It comprehensively introduces JSCC technologies for communications systems, including coding and decoding algorithms, and emerging applications of JSCC in current wireless communications. The book covers the full range of theoretical and technical areas before concluding with a section considering recent applications and emerging designs for JSCC. A methodical reference for academic and industrial researchers, development engineers, system engineers, system architects and software engineers, this book: Explains how JSCC leads to high performance in communication systems and networks Consolidates key material from multiple disparate sources Is an ideal reference for graduate-level courses on digital or wireless communications, as well as courses on information theory Targets professionals involved with digital and wireless communications and networking systems

This book deals with the problem of joint source-channel video transmission, i.e., the joint optimal allocation of resources at the application layer and the other network layers, such as data rate adaptation, channel coding, power adaptation in wireless networks, quality of service (QoS) support from the network, and packet scheduling, for efficient video transmission. Real-time video communication applications, such as videoconferencing, video telephony, and on-demand video streaming, have gained increased popularity. However, a key problem in video transmission over the existing Internet and wireless networks is the incompatibility between the nature of the network conditions and the QoS requirements (in terms, for example, of bandwidth, delay, and packet loss) of real-time video applications. To deal with this incompatibility, a natural approach is to adapt the end-system to the network. The joint source-channel coding approach aims to efficiently perform content-aware cross-layer resource allocation, thus increasing the communication efficiency of multiple network layers. Our purpose in this book is to review the basic elements of the state-of-the-art approaches toward joint source-channel video transmission for wired and wireless systems. In this book, we present a general resource-distortion optimization framework, which is used throughout the book to guide our discussions on various techniques of joint source-channel video transmission. In this framework, network resources from multiple layers are assigned to each video packet according to its level of importance. It provides not only an optimization benchmark against which the performance of other sub-optimal systems can be evaluated, but also a useful tool for assessing the effectiveness of different error control components in practical system design. This book is therefore written to be accessible to researchers, expert industrial R&D engineers, and university students who are interested in the cutting edge technologies in joint source-channel video transmission. Contents: Introduction / Elements of a Video Communication System / Joint Source-Channel Coding / Error-Resilient Video Coding / Channel Modeling and Channel Coding / Internet Video Transmission / Wireless Video Transmission / Conclusions