Uniformly reweighted APP decoder for memory efficient decoding of LDPC Codes

Velimir Ilic, Elsa Dupraz, David Declercq, Bane V Vasic

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

In this paper we propose a uniformly reweighted a posteriori probability (APP) decoder. The APP decoder is well-known to be suboptimal compared to the BP decoder. Here, we derive the APP decoder as an algorithm of approximate Bayesian inference on the LDPC code graph and introduce a correction parameter to overcome the suboptimaly of the APP decoder. We optimize numerically the correction parameter and show that it improves the BER performance of the APP decoder compared to its non-corrected version. In addition, the original APP decoder requires memory that is linear in the number of edges in the code graph. Here, we propose a memory efficient implementation of the algorithm that requires memory that is linear only in the codeword length.

Original languageEnglish (US)
Title of host publication2014 52nd Annual Allerton Conference on Communication, Control, and Computing, Allerton 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1228-1232
Number of pages5
ISBN (Electronic)9781479980093
DOIs
StatePublished - Jan 30 2014
Event2014 52nd Annual Allerton Conference on Communication, Control, and Computing, Allerton 2014 - Monticello, United States
Duration: Sep 30 2014Oct 3 2014

Publication series

Name2014 52nd Annual Allerton Conference on Communication, Control, and Computing, Allerton 2014

Other

Other2014 52nd Annual Allerton Conference on Communication, Control, and Computing, Allerton 2014
Country/TerritoryUnited States
CityMonticello
Period9/30/1410/3/14

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications

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