Iterative approximate linear programming decoding of LDPC codes with linear complexity

David Burshtein*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Scopus citations

Abstract

The problem of low complexity linear programming (LP) decoding of low-density parity-check (LDPC) codes is considered. An iterative algorithm for efficient approximate solution of this problem was proposed by Vontobel and Koetter. In this paper the convergence rate and computational complexity of this algorithm are studied. In particular we are interested in obtaining a feasible vector in the LP decoding problem, with objective function value whose distance to the minimum, normalized by the block length, can be made arbitrarily small. It is shown that such a feasible vector can be obtained in linear, in the block length, computational complexity. Combined with previous results, that have shown that the LP decoder can correct some fixed fraction of errors, we conclude that this error correction can be achieved with linear computational complexity.

Original languageEnglish
Title of host publicationProceedings - 2008 IEEE International Symposium on Information Theory, ISIT 2008
Pages1498-1502
Number of pages5
DOIs
StatePublished - 2008
Event2008 IEEE International Symposium on Information Theory, ISIT 2008 - Toronto, ON, Canada
Duration: 6 Jul 200811 Jul 2008

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
ISSN (Print)2157-8101

Conference

Conference2008 IEEE International Symposium on Information Theory, ISIT 2008
Country/TerritoryCanada
CityToronto, ON
Period6/07/0811/07/08

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