Check-hybrid GLDPC codes: Systematic elimination of trapping sets by super checks

Vida Ravanmehr, David Declercq, Bane Vasic

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

2 Scopus citations

Abstract

In this paper, we propose a new approach to constructing a class of check-hybrid generalized low-density parity-check (GLDPC) codes which are free of small trapping sets. This approach is based on converting selected checks of an LDPC code involving a trapping set to super checks corresponding to a shorter error correcting component code. In particular, we follow two goals in constructing the check-hybrid GLDPC codes: First, the super checks are replaced based on the knowledge of trapping sets of the global LDPC code. We show that by converting only some single checks to super checks the decoder corrects the errors on a trapping set and hence eliminates the trapping set. Second, the number of super checks required for eliminating certain trapping sets is minimized to reduce the rate-loss. We first give an algorithm to find a set of critical checks in a trapping set of an LDPC code and then we provide some upper bounds on the minimum number of critical checks needed to eliminate certain trapping sets in the parity-check matrix of an LDPC code. A possible fixed set for a class of check-hybrid codes is also given.

Original languageEnglish (US)
Title of host publication2014 IEEE International Symposium on Information Theory, ISIT 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages701-705
Number of pages5
ISBN (Print)9781479951864
DOIs
StatePublished - 2014
Event2014 IEEE International Symposium on Information Theory, ISIT 2014 - Honolulu, HI, United States
Duration: Jun 29 2014Jul 4 2014

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
ISSN (Print)2157-8095

Other

Other2014 IEEE International Symposium on Information Theory, ISIT 2014
Country/TerritoryUnited States
CityHonolulu, HI
Period6/29/147/4/14

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Information Systems
  • Modeling and Simulation
  • Applied Mathematics

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