The title ofthis book， Channel Codes： Classical and Modern，was selected to reflect the fact that this book does indeed cover both classical and modern channel codes，It includes BCH codes， Reed-Solomon codes， convolutional codes， finite-geometry codes， turbo codes， low-density parity-check （LDPC） codes， and product codes.However， the title has a second interpretation. While the majority of this book is on LDPC codes， these can rightly be considered to be both classical （having been first discovered in 1961） and modern （having been rediscovered circa 1996）. This is exemplified by David Forney's statement at his August 1999 IMA talk on codes on graphs，lt feels like the early days. As another example of the classical/modern duality， finite-geometry codes were studied in the 1960s and thus are classical codes. However， they were rediscovered by Shu Lin et a/. circa 2000 as a class of LDPC codes with very appealing features and are thus modern codes as well. The classical and modern incarnations of flnite-geometry codes are distinguished by their decoders： one-step hard-decision decoding （classical） versus iterative soft-decision decoding （modern）.
作者簡(jiǎn)介
威廉·瑞安（William E. Ryan）教授是通信理論和信道編碼領(lǐng)域?qū)＜?，是?guó)際電氣與電子工程師協(xié)會(huì)的杰出會(huì)士（IEEE Fellow）。他本科畢業(yè)于美國(guó)的凱斯西儲(chǔ)大學(xué)，博士畢業(yè)于弗吉尼亞大學(xué)，后在新墨西哥州立大學(xué)和亞利桑那大學(xué)任教近20年，他目前是澤塔聯(lián)合公司（Zeta Associates， Inc.）的高級(jí)合伙人。他的研究興趣主要在編碼和信號(hào)處理及其在數(shù)據(jù)存儲(chǔ)和無線數(shù)據(jù)通信中的應(yīng)用，發(fā)表過100多篇學(xué)術(shù)論文，并曾擔(dān)任IEEE Transactions on Communications的副主編。林舒（Shu Lin）教授是世界知名的編碼理論專家，曾擔(dān)任IEEE信息論學(xué)會(huì)主席。他本科畢業(yè)于臺(tái)灣大學(xué)，博士畢業(yè)于美國(guó)的萊斯大學(xué)，后在夏威夷大學(xué)檀香山分校、得克薩斯農(nóng)工大學(xué)、加州大學(xué)戴維斯分校等大學(xué)任教50余年。他是國(guó)際電氣與電子工程師協(xié)會(huì)的終生杰出會(huì)士（IEEE Life Fellow），獲得過洪堡研究獎(jiǎng)（1996）、 IEEE第三千年獎(jiǎng)?wù)拢?000）、NASA杰出公共成就獎(jiǎng)?wù)拢?014）、馬奎斯世界名人錄終身成就獎(jiǎng)（2019）和IEEE研究生教育獎(jiǎng)（2020）。他在編碼理論領(lǐng)域撰寫過多部著作，“香農(nóng)信息科學(xué)經(jīng)典”系列里已出版了《差錯(cuò)控制編碼 第2版》《信道編碼：經(jīng)典和現(xiàn)代方法》和《低密度奇偶校驗(yàn)碼：設(shè)計(jì)、構(gòu)造與統(tǒng)一框架》。
圖書目錄
Preface 1 Coding and Capacity 1．1 Digital Data Communication and Storage 1．2 Channel-Coding Overview 1．3 Channel-Code Archetype： The (7，4) Hamming Code 1．4 Design Criteria and Performance Measures 1．5 Channel-Capacity Formulas for Common Channel Models 1．5．1 Capacity for Binary-Input Memoryless Channels 1．5．2 Coding Limits for M-ary-Input Memoryless Channels 1．5．3 Coding Limits for Channels with Memory Problems References 2 Finite Fields， Vector Spaces， Finite Geometries， and Graphs 2．1 Sets and Binary Operations 2．2 Groups 2．2．1 Basic Concepts of Groups 2．2．2 Finite Groups 2．2．3 Subgroups and Cosets 2．3 Fields 2．3．1 Definitions and Basic Concepts 2．3．2 Finite Fields 2．4 Vector Spaces 2．4．1 Basic Definitions and Properties 2．4．2 Linear Independence and Dimension 2．4．3 Finite Vector Spaces over Finite Fields 2．4．4 Inner Products and Dual Spaces 2．5 Polynomials over Finite Fields 2．6 Construction and Properties of Galois Fields 2．6．1 Construction of Galois Fields 2．6．2 Some Fundamental Properties of Finite Fields 2．6．3 Additive and Cyclic Subgroups 2．7 Finite Geometries 2．7．1 Euclidean Geometries 2．7．2 Projective Geometries 2．8 Graphs 2．8．1 Basic Concepts 2．8．2 Paths and Cycles 2．8．3 Bipartite Graphs Problems References Appendix A 3 Linear Block Codes 3．1 Introduction to Linear Block Codes 3．1．1 Generator and Parity-Check Matrices 3．1．2 Error Detection with Linear Block Codes 3．1．3 Weight Distribution and Minimum Hamming Distance of a Linear Block Code 3．1．4 Decoding of Linear Block Codes 3．2 Cyclic Codes 3．3 BCH Codes 3．3．1 Code Construction 3．3．2 Decoding 3．4 Nonbinary Linear Block Codes and Reed-Solomon Codes 3．5 Product， Interleaved， and Concatenated Codes 3．5．1 Product Codes 3．5．2 Interleaved Codes 3．5．3 Concatenated Codes 3．6 Quasi-Cyclic Codes 3．7 Repetition and Single-Parity-Check Codes Problems References 4 Convolutional Codes 4．1 The Convolutional Code Archetype 4．2 Algebraic Description of Convolutional Codes 4．3 Encoder Realizations and Classifications 4．3．1 Choice of Encoder Class 4．3．2 Catastrophic Encoders 4．3．3 Minimal Encoders 4．3．4 Design of Convolutional Codes 4．4 Alternative Convolutional Code Representations 4．4．1 Convolutional Codes as Semi-Infinite Linear Codes 4．4．2 Graphical Representations for Convolutional Code Encoders …… 5 Low-Density Parity-Check Codes 6 Computer-Based Design of LDPC Codes 7 Turbo Codes 8 Ensemble Enumerators for Turbo and LDPC Codes 9 Ensemble Decoding Thresholds for LDPC and Turbo Codes 10 Finite-Geometry LDPC Codes 11 Constructions of LDPC Codes Based on Finite Fields 12 LDPC Codes Based on Combinatorial Designs， Graphs， and Superposition 13 LDPC Codes for Binary Erasure Channels 14 Nonbinary LDPC Codes 15 LDPC Code Applications and Advanced Topics
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