Lazy scheduling for LDPC decoding

Daniel Levin, Simon Litsyn, Eran Sharon

Research output: Contribution to journalArticlepeer-review

Abstract

A complexity reducing method for iterative message passing decoding algorithms of Low-Density Parity-Check (LDPC) codes is described. It is based on lazy scheduling which involves a partial update of messages in the iterations. A Density Evolution (DE) approach is developed for optimization of the parameters for choice of the messages to be updated. Combined with an efficient serial scheduling, the resulting method reduces the decoding complexity by about 70-75% compared to the classical Belief Propagation (BP) scheme, while maintaining the same performance.

Original languageEnglish
Pages (from-to)70-72
Number of pages3
JournalIEEE Communications Letters
Volume11
Issue number1
DOIs
StatePublished - Jan 2007

Keywords

  • Iterative decoding
  • LDPC codes

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