Convergence analysis of generalized serial message-passing schedules

Eran Sharon*, Noam Presman, Simon Litsyn

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

Schedule is the order of passing messages between vertices of the bipartite graph defining an LDPC code in the process of decoding. Schedules affect the rate of decoding convergence. New efficient generalized serial schedules are described and analyzed, exhibiting significantly faster convergence compared to previously known schedules. For the proposed schedules, combinatorial and probabilistic analysis is presented, explaining the fast convergence observed in simulations. Using it, LDPC ensembles for which significantly better convergence rates can be achieved are identified. Specific code constructions from lifted graphs are further proposed, efficiently supporting the schedules. Examples based on regular LDPC codes are provided, in which the schedules achieve convergence speedup factors of up to 6 in comparison with the flooding schedule. Higher speedup factors are predicted by the analysis for irregular codes.

Original languageEnglish
Article number5174530
Pages (from-to)1013-1024
Number of pages12
JournalIEEE Journal on Selected Areas in Communications
Volume27
Issue number6
DOIs
StatePublished - Aug 2009

Keywords

  • Belief propagation
  • Density evolution
  • Iterative decoding
  • LDPC codes

Fingerprint

Dive into the research topics of 'Convergence analysis of generalized serial message-passing schedules'. Together they form a unique fingerprint.

Cite this