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Combined Source and Channel Coding Using Permutation Codes

Combined Source and Channel Coding Using Permutation Codes PDF Author: Bhaskarkumar Patel
Publisher:
ISBN:
Category :
Languages : en
Pages : 144

Book Description


Combined Source and Channel Coding Using Permutation Codes

Combined Source and Channel Coding Using Permutation Codes PDF Author: Bhaskarkumar Patel
Publisher:
ISBN:
Category :
Languages : en
Pages : 144

Book Description


Joint Source Channel Coding Using Arithmetic Codes

Joint Source Channel Coding Using Arithmetic Codes PDF Author: Bi Dongsheng
Publisher: Springer Nature
ISBN: 3031016750
Category : Technology & Engineering
Languages : en
Pages : 69

Book Description
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

Source and Channel Coding

Source and Channel Coding PDF Author: John B. Anderson
Publisher: Springer Science & Business Media
ISBN: 1461539986
Category : Technology & Engineering
Languages : en
Pages : 438

Book Description
oW should coded communication be approached? Is it about prob H ability theorems and bounds, or about algorithms and structures? The traditional course in information theory and coding teaches these together in one course in which the Shannon theory, a probabilistic the ory of information, dominates. The theory's predictions and bounds to performance are valuable to the coding engineer, but coding today is mostly about structures and algorithms and their size, speed and error performance. While coding has a theoretical basis, it has a practical side as well, an engineering side in which costs and benefits matter. It is safe to say that most of the recent advances in information theory and coding are in the engineering of coding. These thoughts motivate the present text book: A coded communication book based on methods and algorithms, with information theory in a necessary but supporting role. There has been muchrecent progress in coding, both inthe theory and the practice, and these pages report many new advances. Chapter 2 cov ers traditional source coding, but also the coding ofreal one-dimensional sources like speech and new techniques like vector quantization. Chapter 4 is a unified treatment of trellis codes, beginning with binary convolu tional codes and passing to the new trellis modulation codes.

Joint Source Channel Coding Using Arithmetic Codes

Joint Source Channel Coding Using Arithmetic Codes PDF Author: Dongsheng Bi
Publisher: Morgan & Claypool Publishers
ISBN: 1608451488
Category : Computers
Languages : en
Pages : 78

Book Description
Proposes 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 modelled 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 can be applied directly on the trellis.

Digital Communications 1

Digital Communications 1 PDF Author: Didier Le Ruyet
Publisher: John Wiley & Sons
ISBN: 1848218451
Category : Technology & Engineering
Languages : en
Pages : 404

Book Description
The communication chain is constituted by a source and a recipient, separated by a transmission channel which may represent a portion of cable, an optical fiber, a radio channel, or a satellite link. Whatever the channel, the processing blocks implemented in the communication chain have the same foundation. This book aims to itemize. In this first volume, after having presented the base of the information theory, we will study the source coding techniques with and without loss. Then we analyze the correcting codes for block errors, convutional and concatenated used in current systems.

Channel Coding in Communication Networks

Channel Coding in Communication Networks PDF Author: Alain Glavieux
Publisher: John Wiley & Sons
ISBN: 1118613635
Category : Technology & Engineering
Languages : en
Pages : 323

Book Description
This book provides a comprehensive overview of the subject of channel coding. It starts with a description of information theory, focusing on the quantitative measurement of information and introducing two fundamental theorems on source and channel coding. The basics of channel coding in two chapters, block codes and convolutional codes, are then discussed, and for these the authors introduce weighted input and output decoding algorithms and recursive systematic convolutional codes, which are used in the rest of the book. Trellis coded modulations, which have their primary applications in high spectral efficiency transmissions, are then covered, before the discussion moves on to an advanced coding technique called turbocoding. These codes, invented in the 1990s by C. Berrou and A. Glavieux, show exceptional performance. The differences between convolutional turbocodes and block turbocodes are outlined, and for each family, the authors present the coding and decoding techniques, together with their performances. The book concludes with a chapter on the implementation of turbocodes in circuits. As such, anyone involved in the areas of channel coding and error correcting coding will find this book to be of invaluable assistance.

Joint Source-channel Coding Of Discrete-time Signals With Continuous Amplitudes

Joint Source-channel Coding Of Discrete-time Signals With Continuous Amplitudes PDF Author: Norbert Goertz
Publisher: World Scientific
ISBN: 1908979143
Category : Technology & Engineering
Languages : en
Pages : 207

Book Description
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 — 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 — 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./a

Channel Coding in the Presence of Side Information

Channel Coding in the Presence of Side Information PDF Author: Guy Keshet
Publisher: Now Publishers Inc
ISBN: 1601980485
Category : Computers
Languages : en
Pages : 154

Book Description
Channel Coding in the Presence of Side Information reviews the concepts and methods of communication systems equipped with side information both from the theoretical and practical points of view. It is a comprehensive review that gives the reader an insightful introduction to one of the most important topics in modern communications systems.

Source Coding Theory

Source Coding Theory PDF Author: Robert M. Gray
Publisher: Springer Science & Business Media
ISBN: 146131643X
Category : Technology & Engineering
Languages : en
Pages : 197

Book Description
Source coding theory has as its goal the characterization of the optimal performance achievable in idealized communication systems which must code an information source for transmission over a digital communication or storage channel for transmission to a user. The user must decode the information into a form that is a good approximation to the original. A code is optimal within some class if it achieves the best possible fidelity given whatever constraints are imposed on the code by the available channel. In theory, the primary constraint imposed on a code by the channel is its rate or resolution, the number of bits per second or per input symbol that it can transmit from sender to receiver. In the real world, complexity may be as important as rate. The origins and the basic form of much of the theory date from Shan non's classical development of noiseless source coding and source coding subject to a fidelity criterion (also called rate-distortion theory) [73] [74]. Shannon combined a probabilistic notion of information with limit theo rems from ergodic theory and a random coding technique to describe the optimal performance of systems with a constrained rate but with uncon strained complexity and delay. An alternative approach called asymptotic or high rate quantization theory based on different techniques and approx imations was introduced by Bennett at approximately the same time [4]. This approach constrained the delay but allowed the rate to grow large.

Distributed Source Coding

Distributed Source Coding PDF Author: Shuang Wang
Publisher: John Wiley & Sons
ISBN: 0470688998
Category : Science
Languages : en
Pages : 379

Book Description
Distributed source coding is one of the key enablers for efficient cooperative communication. The potential applications range from wireless sensor networks, ad-hoc networks, and surveillance networks, to robust low-complexity video coding, stereo/Multiview video coding, HDTV, hyper-spectral and multispectral imaging, and biometrics. The book is divided into three sections: theory, algorithms, and applications. Part one covers the background of information theory with an emphasis on DSC; part two discusses designs of algorithmic solutions for DSC problems, covering the three most important DSC problems: Slepian-Wolf, Wyner-Ziv, and MT source coding; and part three is dedicated to a variety of potential DSC applications. Key features: Clear explanation of distributed source coding theory and algorithms including both lossless and lossy designs. Rich applications of distributed source coding, which covers multimedia communication and data security applications. Self-contained content for beginners from basic information theory to practical code implementation. The book provides fundamental knowledge for engineers and computer scientists to access the topic of distributed source coding. It is also suitable for senior undergraduate and first year graduate students in electrical engineering; computer engineering; signal processing; image/video processing; and information theory and communications.