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Information, Physics, and Computation$
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Marc Mézard and Andrea Montanari

Print publication date: 2009

Print ISBN-13: 9780198570837

Published to Oxford Scholarship Online: September 2009

DOI: 10.1093/acprof:oso/9780198570837.001.0001

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Decoding with belief propagation

Decoding with belief propagation

Chapter:
(p.327) 15 Decoding with belief propagation
Source:
Information, Physics, and Computation
Author(s):

Marc Mézard

Andrea Montanari

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780198570837.003.0015

This chapter revisits the problem of decoding low density parity check (LDPC) codes. The maximum a posteriori probability (MAP) decoding of a bit is described as a statistical inference problem, and belief propagation is applied to its solution. The corresponding message passing procedure is analyzed in details, and the threshold noise level below which this ‘iterative decoding’ achieves perfect decoding is derived. The chapter ends with a general discussion of the relation between message passing and optimal (exact symbol MAP) decoding.

Keywords:   error correcting code, iterative decoding, belief propagation, low density parity check, LDPC, noise threshold, MAP decoding

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