Lazy scheduling for LDPC decoding

Daniel Levin*, Simon Litsyn, Eran Sharon

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

29 Scopus citations


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
Issue number1
StatePublished - Jan 2007


  • Iterative decoding
  • LDPC codes


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