Modern Coding Theory by Tom Richardson (PDF)

Description

Having trouble deciding which coding scheme to employ, how to design a new scheme, or how to improve an existing system? This summary of the state-of-the-art in iterative coding makes this decision more straightforward. With emphasis on the underlying theory, techniques to analyse and design practical iterative coding systems are presented. Using Gallager’s original ensemble of LDPC codes, the basic concepts are extended for several general codes, including the practically important class of turbo codes. The simplicity of the binary erasure channel is exploited to develop analytical techniques and intuition, which are then applied to general channel models. A chapter on factor graphs helps to unify the important topics of information theory, coding and communication theory. Covering the most recent advances, this text is ideal for graduate students in electrical engineering and computer science, and practitioners. Additional resources, including instructor’s solutions and figures, available online: www.cambridge.org/9780521852296.

User’s Reviews

Reviews from Amazon users which were colected at the time this book was published on the website:

⭐This book is your “one stop shop” to learn all about low-density parity-check (LDPC) codes and iterative decoding. This seems to be the primary intention of the authors since they don’t talk about anything that isn’t related to LDPC codes or iterative decoding. This book is not meant as an introductory course in coding theory. It is very good for an advanced course in iterative decoding and as a good reference material for research.Pros:1) The material is self contained.2) Detailed references to technical papers.3) A complete picture of the material is provided (including all the “fine print” mathematics and stuff).4) Rigorous proofs are provided for most of the important results.Cons:1) Slightly cumbersome notation (especially in chapter 4). E.g., there are four different functions denoted by the letter ‘a’ in four different scripts (fonts) in one section!2) The ebook version (not the Kindle version) has DRM and is intended to be viewed only with Adobe Digital Editions. Digital Editions does not render the mathematical expressions correctly, making the DRM version unusable.

⭐As a graduate student in electrical engineering, I find this book very useful for my research. In particular it goes in depth on how to calculate thresholds for density evolution. I find it as a good complement to Error Control Coding, by Lin and Costello.

⭐The second to worst engineering books I bought so far. The worst one is the “Digital Transmission Engineering” that has its trade-in values gone from close to $2 to not eligible for trade-in anymore. This Modern Coding Theory is neither close to textbook quality since it lacks progressive and rigid buildup of the “theory” nor close to reference book quality since its purpose is to write something “modern” that is still being researched (so instead of reference it is more like introduction). I bought this book because of its attractive table of content that looks like more being focused, not like the very well written “Channel Codes” and “Error Control Coding” that collect almost all recent research outcomes for modern codes most of them are useless in the real word. That said, this book does not contain and explain methods well as those in the “Channel Codes” and “Error Control Coding”. Especially for LDPC, as the “Error Control Coding” states, virtually all practical LDPC codes are QC-LDPC. I am still looking for a good book focusing on the QC-LDPC in theory level. I am not looking for any book that can provide the optimal real world solution as even in the “Channel Codes” and “Error Control Coding” and others I have discovered that some solutions for classic codes are not good.

⭐The book arrived as good as Brand new.. Perfectly happy with the product

⭐Dr. Richardson and Urbanke have made some important controbutions on the theorical analysis of message-passing decoding on LDPC code in special, code on graph in general. I read this book with the hope to pick up some analysis skills on iterative decoding. In general, I understand that experts in an area does not necessary the best persons to write a good and worthy textbook, especially one with hot topic and title like “‘Modern’ Coding Theory” … if you know what I mean.To my surprise, this is a well-written book that provides me a lot of background on the topics far beyond my expectation. Allow me to use many nice approaches of introduction chapter to explain why I like this book.1. After warmup defintions and exmaples, the authors bring in Gilbert-Varshamov lower bound and Elias upper bound for minimum Hamming distance of code. Then they use Chebyshev’s inequality, the concept of theshold decoding and Gilbert-Varshamov bound to prove the existence of non-zero rate code of zero error probability. (Initially I was quite surprised by assigning those fundamental bounds as problems, but after few hour’s effort on the problems to make myself feel comfortable with the results, I started to appreciate author’s approach to stay on their main themes, anaysis of capacity approaching codes, and let you learn by working out your parts. Anyway all the proofs can be found from several excellent classical coding textbooks or even Google).2. Another neat approach by define Shannon’s random ensemble, define MAP (maximum a-posteriori), ML (Maximum likeihood) and APP (a-posterior probability) use Baye’s rule to show their relations. Then use random ensemble’s uniform code and statistic independent codewords properties, helped again by Chebyshev’s inequality and theshold decoding to prove Shannon’s channel coding theorem under binary symmtric channel. This is the cleanest proof of channel coding theorem I ever see. The authors again use “threshold” to prove capacity. The concept of threshold is introduced by Gallager in LDPC decoding, can be extended to Turbo code decoding.3. Use Elias upper bound to prove that opitimal minimum Hamming distance code is bound away from channel capacity, used to argue bounded distance decoder is not sufficient.4. Introduce Elias generator ensemble and Gallager’s parity ensemble, prove binary linear code achieve channel capacity.5. Use error exponent bounds of block code and convolutional code to quantify decoding complexity and delay. Comment that a similar theorem for iterative decoding is the most needed open question.6. Use Hamming code over binary erase channel and Venn diagram to preview iterative (local) encode and decode. Show iterative decoding is not optimal in some case. However argues iterative decoding is a low-complexity (inverse of coding gap) decoding scheme to approaching capacity.In general,7. This book has a good balance on teaching coding knowledge and conveying core work (proofs of theorems), and good balance of work by author and reader.8. Label figures, definitions, examples, theorems and key equations by one sequence, which are a flow of important results. Proof throughout text without explicit treatment. Proof as core text to read through.9. Many quided problems as integrated part of the textbook.10. Every chapter ended with an extensive historic note on related topics.In summary, this book is an outstanding work by two experts on the topic. Highly recommended to anyone who feel serious on the topic.

⭐This book was required reading for my graduate level advanced coding topics course. My first issue with the text is its clunky notation. Expressions and equations are written in unusual fonts. Super and sub scripts appear awkward, and the authors seem to introduce their own notation for convolution. Besides the cumbersome typesetting, the book has a somewhat scatterbrained approach for organizing material.This book is essentially about LDPC codes, almost exclusively. The book is good as a side reference, perhaps to supplement a more organized and clearly written text such as Lin & Costello, but not as an introductory text, or a text one would use for clarifying concepts. The text by Todd Moon is a far superior reference.Overall, I do not recommend this book. I’ve not gotten much use out of it all semester.

⭐Vale la pena comprarlo se interessati alla teoria dei codici.Gli autori si sono prodigati al fine di semplificare il piùpossibilee i temi trattati pur mantenendo il rigore logiconel flusso espositivo.Very very nice book to understand modern coding theory.

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