Channel Codes: Classical and Modern

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Cambridge University Press, Sep 17, 2009 - Technology & Engineering
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Channel coding lies at the heart of digital communication and data storage, and this detailed introduction describes the core theory as well as decoding algorithms, implementation details, and performance analyses. In this book, Professors Ryan and Lin provide clear information on modern channel codes, including turbo and low-density parity-check (LDPC) codes. They also present detailed coverage of BCH codes, Reed-Solomon codes, convolutional codes, finite geometry codes, and product codes, providing a one-stop resource for both classical and modern coding techniques. Assuming no prior knowledge in the field of channel coding, the opening chapters begin with basic theory to introduce newcomers to the subject. Later chapters then extend to advanced topics such as code ensemble performance analyses and algebraic code design. 250 varied and stimulating end-of-chapter problems are also included to test and enhance learning, making this an essential resource for students and practitioners alike.
 

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Contents

Finite Fields Vector Spaces Finite Geometries and Graphs
28
Linear Block Codes
94
Convolutional Codes
147
LowDensity ParityCheck Codes
201
ComputerBased Design of LDPC Codes
257
Turbo Codes
298
Ensemble Enumerators for Turbo and LDPC Codes
339
Ensemble Enumerators
376
FiniteGeometry LDPC Codes
430
Constructions of LDPC Codes Based on Finite Fields
484
LDPC Codes Based on Combinatorial Designs Graphs and Superposition
523
LDPC Codes for Binary Erasure Channels
561
Nonbinary LDPC Codes
592
LDPC Code Applications and Advanced Topics
636
Index
681
Copyright

Ensemble Decoding Thresholds for LDPC and Turbo Codes
388

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About the author (2009)

William E. Ryan is a Professor in the Department of Electrical and Computer Engineering at the University of Arizona, where he has been a faculty member since 1998. Before moving to academia, he held positions in industry for five years. He has published over 100 technical papers and his research interests include coding and signal processing with applications to data storage and data communications.

Shu Lin is an Adjunct Professor in the Department of Electrical and Computer Engineering, University of California, Davis. He has authored and co-authored numerous technical papers and several books, including the successful Error Control Coding (with Daniel J. Costello). He is an IEEE Life Fellow and has received several awards, including the Alexander von Humboldt Research Prize for U.S. Senior Scientists (1996) and the IEEE Third-Millenium Medal (2000).