This new edition has been extensively revised to reflect the progress in error control coding over the past few years. Over 60% of the material has been completely reworked, and 30% of the material is original.
* Convolutional, turbo, and low density parity-check (LDPC) coding and polar codes in a unified framework
* Advanced research-related developments such as spatial coupling
* A focus on algorithmic and implementation aspects of error control coding
Autorentext
Christian B. Schlegel currently holds the NSERC Industrial Research Chair in Wireless Information Transmission and Networking at Dalhousie University. He holds PhD and MS degrees from the University of Notre Dame. Dr. Schlegel has authored several books including Trellis Coding (1997, IEEE Press) and Trellis and Turbo Coding (2004 Wiley-IEEE).
Lance C. Pérez is a Professor, Dean of Graduate Studies, and Associate Vice Chancellor for Academic Affairs at the University of Nebraska-Lincoln. He received his PhD and MS in electrical engineering at the University of Notre Dame. He co-authored Trellis and Turbo Coding ( 2004 Wiley-IEEE Press) with Christian Schlegel.
Klappentext
This book discusses the state-of-the-art in error control coding and its decoding algorithms with a strong focus on iterative methods and their standardization.
Trellis and Turbo Coding: Iterative and Graph-Based Error Control Coding examines error control coding from a present day perspective, focusing on the recent developments of turbo coding systems and their algorithmic foundations. The main aspect of the book is error control, which is the discipline that concerns itself with avoiding and correcting errors that can occur during transmissions, processing, or storage of digital data. Historical results are discussed and introduced along the way to present a complete picture of modern error control coding. Many application examples and industry standards are included to illustrate the use of error control coding, in particular the graph-based systems, which dominate error protection in modern communications devices.
This edition includes:
- Trellis, turbo, and low-density parity-check (LDPC) coding and polar codes in a unified framework
- Advanced research-related developments such as spatial coupling
- A focus on algorithmic and implementation aspects of error control coding
The authors offer readers a comprehensive and tutorial review about trellis and turbo coding with applications to modern communications.
Christian B. Schlegel currently holds the NSERC Industrial Research Chair in Wireless Information Transmission and Networking at Dalhousie University. He holds PhD and MS degrees from the University of Notre Dame. Dr. Schlegel has authored several books including Trellis Coding (1997, IEEE Press) and Trellis and Turbo Coding (2004 Wiley-IEEE).
Lance C. Pérez is a Professor, Dean of Graduate Studies, and Associate Vice Chancellor for Academic Affairs at the University of Nebraska-Lincoln. He received his PhD and MS in electrical engineering at the University of Notre Dame. He co-authored Trellis and Turbo Coding ( 2004 Wiley-IEEE Press) with Christian Schlegel.
Inhalt
1 Introduction 1
1.1 Modern Digital Communications 1
1.2 The Rise of Digital Communications 4
1.3 Communication Systems 4
1.4 Error Control Coding 7
1.5 Bandwidth, Power, and Complexity 12
1.6 A Brief History - The Drive Towards Capacity 20
2 Communications Basics 27
2.1 The Probabilistic Viewpoint 27
2.2 Vector Communication Channels 29
2.3 Optimum Receivers 31
2.4 Matched Filters 33
2.5 Message Sequences 35
2.6 The Complex Equivalent Baseband Model 39
2.7 Spectral Behavior 44
2.8 Advanced Modulation Methods 46
2.8.1 OFDM 46
2.8.2 Multiple Antenna Channels (MIMO Channels) 48
2.9 A Communications System Case Study 53
2.10 Appendix 2.A 61
3 Trellis-Coded Modulation 67
3.1 An Introductory Example 67
3.2 Construction of Codes 71
3.3 Lattices 80
3.4 Lattice Formulation of Trellis Codes 86
3.5 Rotational Invariance 92
3.6 V.fast 99
3.7 The IEEE 802.3an Standard 101
3.8 Historical Notes 106
4 Trellis Representations 111
4.1 Preliminaries 111
4.2 The Parity-Check Matrix 112
4.3 Parity-Check Trellis Representations 113
4.4 Convolutional Codes and Their Trellis 115
4.5 Minimal Trellises 120
4.6 Minimum-Span Generator Matrices 124
4.7 Systematic Construction of the PC-Trellis 127
4.8 Tail-Biting Trellises 129
4.9 The Minimal Trellis of Convolutional Codes 133
4.10 Fundamental Theorems from Basic Algebra 139
4.11 Systematic Encoders 149
4.12 Maximum Free-Distance Convolutional Codes 151
4.13 The Squaring Construction and the Trellis of Lattices 154
4.14 The Construction of Reed-Muller Codes 161
4.15 A Decoding Example 163
4.16 Polar Codes and Their Relationship to RM Codes 166
Appendix 4.A 171
5 Trellis and Tree Decoding 179
5.1 Background and Introduction 179
5.2 Tree Decoders 181
5.3 The Stack Algorithm 183
5.4 The Fano Algorithm 185
5.5 The M-Algorithm 186
5.6 Maximum Likelihood Decoding 197
5.7 A Posteriori Probability Symbol Decoding 200
5.8 Log-APP and Approximations 207
5.9 Error Analysis and Distance Spectrum 211
5.10 Random Coding Analysis of Optimal Decoding 222
5.11 Random Coding Analysis of Sequential Decoding 232
5.12 Some Final Remarks 238
6 Low-Density Parity-Check Codes 249
6.1 Introduction 249
6.2 LDPC Codes and Graphs 251
6.3 LDPC Decoding via Message Passing 255
6.4 Analysis Techniques 259
6.4.1 (Error) Probability Evolution for Binary Erasure Channels 259
6.4.2 Error Mechanism of LDPCs on BECs 265
6.4.3 Binary Symmetric Channels and the Gallager Algorithms 266
6.4.4 The AWGN Channel 270
6.5 Code Families and Construction 281
6.5.1 Constructions with Permutation Matrices 281
6.5.2 Cycle Reduction Design 286
6.5.3 RS-based Construction 287
6.5.4 Repeat-Accumulate Codes 289
6.6 Encoding of LDPC Codes 291
6.6.1 Triangular LDPC Codes 292
6.6.2 Specialized LDPC Codes 295
6.6.3 Approximate Triangularization 296
Appendix 6.A 298
7 Error Floors 319
7.1 The Error Floor Problem 319
7.2 Dynamics of the Absorption Sets 323
7.3 Code Design for Low Error Floors 331
7.4 Impact of the Decoding Algorithm 335
7.5 Importance Sampling (IS) 336
7.6 Computing Error Rates via Importance Sampling 340
8 Turbo Coding: Basic Principles 351
8.1 Introduction 351
8.2 Parallel Concatenated Convolutional Codes 353
8.3 Distance Spe...