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Informationen zum Autor Rolf Johannesson is Professor Emeritus of Information Theory at Lund University, Sweden, and a Fellow of the IEEE. He was awarded the honor of Professor, honoris causa , from the Institute for Information Transmission Problems, Russian Academy of Sciences, and elected member of the Royal Swedish Academy of Engineering Sciences. Dr. Johannesson's research interests include information theory, coding theory, and cryptography. Kamil Sh. Zigangirov is Professor Emeritus of Telecommunication Theory at Lund University, Sweden, and a Fellow of the IEEE. He is widely published in the areas of information theory, coding theory, mathematical statistics, and detection theory. Dr. Zigangirov is the inventor of the stack algorithm for sequential decoding and the co-inventor of the LDPC convolutional codes. Klappentext Fundamentals of Convolutional Coding, Second Edition, regarded as a bible of convolutional coding brings you a clear and comprehensive discussion of the basic principles of this field. This edition has been expanded to reflect the developments in modern coding theory, including new chapters on low-density parity-check convolutional codes and turbo codes. Since these types of codes are now appearing in industry standards, application engineers and scientists will also find this book essential to obtaining a basic understanding of the theory behind these new techniques. Written by two leading authorities in coding and information theory, it is unmatched in the field for its accessible analysis of the structural properties of convolutional encoders. Other essentials covered include: Viterbi, BCJR, BEAST, list, and sequential decoding Low-density parity-check (LDPC) codes and iterative decoding Turbo codes and iterative coding An extensive set of practice problems The authors draw on their own research and more than 40 years of teaching experience to present the fundamentals needed to understand the codes used in a variety of applications today. The book can be used as a textbook for graduate-level electrical engineering students. Zusammenfassung Fundamentals of Convolutional Coding is unmatched in the field for its accessible analysis of the structural properties of convolutional encoders. Inhaltsverzeichnis Preface xi Acknowledgement xiv 1 Introduction 1 1.1 Why error control? 1 1.2 Block codes-a primer 8 1.3 Codes on graphs 21 1.4 A first encounter with convolutional codes 28 1.5 Block codes versus convolutional codes 35 1.6 Capacity limits and potential coding gain revisited 36 1.7 Comments 39 Problems 41 2 Convolutional encoders-Structural properties 49 2.1 Convolutional codes and their encoders 49 2.2 The Smith form of polynomial convolutional generator matrices 58 2.3 Encoder inverses 67 2.4 Encoder and code equivalences 76 2.5 Basic encoding matrices 79 2.6 Minimalbasic encoding matrices 82 2.7 Minimal encoding matrices and minimal encoders 90 2.8 Canonical encoding matrices* 109 2.9 Minimality via the invariantfactor theorem* 127 2.10 Syndrome formers and dual encoders 131 2.11 Systematic convolutional encoders 139 2.12 Some properties of generator matrices-an overview 150 2.13 Comments 150 Problems 152 3 Distance properties of convolutional codes 161 3.1 Distance measures-a first encounter 161 3.2 Active distances 171 3.3 Properties of convolutional codes via the active distances 179 3.4 Lower bound on the distance profile 181 3.5 Upper bounds on the free distance 186 3.6 Timevarying convolutional codes 191 3.7 Lower bound on the free distance 195 3.8 Lower bounds on the active distances* 200 3.9 Distances of casc...
