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

Jun Asatani, Takuya Kusaka, Kenichi Tomita, Tadao Kasami

Research output: Contribution to journalArticle

Abstract

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
VolumeE86-A
Issue number10
Publication statusPublished - Oct 2003
Externally publishedYes

Fingerprint

Iterative Decoding
Iterative decoding
Minimum Distance
Decoding
Reed-Muller Codes
Optimality Conditions
Termination
Degradation
Iteration
Simulation

Keywords

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

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Hardware and Architecture
  • Information Systems

Cite this

Reduced Complexity Iterative Decoding Using a Sub-Optimum Minimum Distance Search. / Asatani, Jun; Kusaka, Takuya; Tomita, Kenichi; Kasami, Tadao.

In: IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, Vol. E86-A, No. 10, 10.2003, p. 2596-2600.

Research output: Contribution to journalArticle

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