Lattice Coding for Signals and Networks

A Structured Coding Approach to Quantization, Modulation and Multiuser Information Theory

Nonfiction, Science & Nature, Technology, Engineering, Mathematics
Cover of the book Lattice Coding for Signals and Networks by Ram Zamir, Bobak Nazer, Yuval Kochman, Cambridge University Press
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Author: Ram Zamir, Bobak Nazer, Yuval Kochman ISBN: 9781139984652
Publisher: Cambridge University Press Publication: August 7, 2014
Imprint: Cambridge University Press Language: English
Author: Ram Zamir, Bobak Nazer, Yuval Kochman
ISBN: 9781139984652
Publisher: Cambridge University Press
Publication: August 7, 2014
Imprint: Cambridge University Press
Language: English

Unifying information theory and digital communication through the language of lattice codes, this book provides a detailed overview for students, researchers and industry practitioners. It covers classical work by leading researchers in the field of lattice codes and complementary work on dithered quantization and infinite constellations, and then introduces the more recent results on 'algebraic binning' for side-information problems, and linear/lattice codes for networks. It shows how high dimensional lattice codes can close the gap to the optimal information theoretic solution, including the characterisation of error exponents. The solutions presented are based on lattice codes, and are therefore close to practical implementations, with many advanced setups and techniques, such as shaping, entropy-coding, side-information and multi-terminal systems. Moreover, some of the network setups shown demonstrate how lattice codes are potentially more efficient than traditional random-coding solutions, for instance when generalising the framework to Gaussian networks.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Unifying information theory and digital communication through the language of lattice codes, this book provides a detailed overview for students, researchers and industry practitioners. It covers classical work by leading researchers in the field of lattice codes and complementary work on dithered quantization and infinite constellations, and then introduces the more recent results on 'algebraic binning' for side-information problems, and linear/lattice codes for networks. It shows how high dimensional lattice codes can close the gap to the optimal information theoretic solution, including the characterisation of error exponents. The solutions presented are based on lattice codes, and are therefore close to practical implementations, with many advanced setups and techniques, such as shaping, entropy-coding, side-information and multi-terminal systems. Moreover, some of the network setups shown demonstrate how lattice codes are potentially more efficient than traditional random-coding solutions, for instance when generalising the framework to Gaussian networks.

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