Reduced Complexity Iterative Decoding Using a Sub-Optimum Minimum Distance Search

Jun Asatani, Takuya Koumoto, Kenichi Tomita, Tadao Kasami

Research output: Contribution to journalArticlepeer-review


In this letter, we propose (1) a new sub-optimum minimum distance search (sub-MDS), whose search complexity is reduced considerably compared with optimum MDSs and (2) a termination criterion, called near optimality condition, to reduce the average number of decoding iterations with little degradation of error performance for the proposed decoding using sub-MDS iteratively. Consequently, the decoding algorithm can be applied to longer codes with feasible complexity. Simulation results for several Reed-Muller (RM) codes of lengths 256 and 512 are given.

Original languageEnglish
Pages (from-to)2596-2600
Number of pages5
JournalIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Issue number10
Publication statusPublished - Oct 2003
Externally publishedYes


  • Iterative decoding
  • Minimum distance search
  • Near optimality condition
  • Reed-Muller code

ASJC Scopus subject areas

  • Signal Processing
  • Computer Graphics and Computer-Aided Design
  • Electrical and Electronic Engineering
  • Applied Mathematics


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