On error exponents for a variable size list decoder using the viterbi algorithm with likelihood testing

Toshihiro Niinomi, Toshiyasu Matsushima, Shigeichi Hirasawa

    Research output: Contribution to journalArticle

    Abstract

    The likelihood ratio (LR) decision criterion [3] employed by Yamamoto and Itoh's decision feedback (ARQ) scheme [1] is known to be highly compatible with the Viterbi algorithm (VA) due to the fact that it requires a small amount of computational effort. In addition, Forney has derived an extension of the coding theorem to the variable size list decoder for maximum likelihood decoding of block codes. In this paper we propose an algorithm for extending LR-based variable size list decoding for decoding convolutional codes using the Viterbi algorithm; assuming a discrete memoryless channel we also derive a lower bound on the decoder's error exponents.

    Original languageEnglish
    Pages (from-to)27-36
    Number of pages10
    JournalElectronics and Communications in Japan, Part III: Fundamental Electronic Science (English translation of Denshi Tsushin Gakkai Ronbunshi)
    Volume90
    Issue number6
    DOIs
    Publication statusPublished - 2007 Jun

    Fingerprint

    Viterbi algorithm
    Decoding
    Testing
    Convolutional codes
    Block codes
    Maximum likelihood
    Feedback

    Keywords

    • Decision criterion
    • List decoding method
    • Randomized coding
    • Viterbi algorithm

    ASJC Scopus subject areas

    • Electrical and Electronic Engineering

    Cite this

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    abstract = "The likelihood ratio (LR) decision criterion [3] employed by Yamamoto and Itoh's decision feedback (ARQ) scheme [1] is known to be highly compatible with the Viterbi algorithm (VA) due to the fact that it requires a small amount of computational effort. In addition, Forney has derived an extension of the coding theorem to the variable size list decoder for maximum likelihood decoding of block codes. In this paper we propose an algorithm for extending LR-based variable size list decoding for decoding convolutional codes using the Viterbi algorithm; assuming a discrete memoryless channel we also derive a lower bound on the decoder's error exponents.",
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    AU - Matsushima, Toshiyasu

    AU - Hirasawa, Shigeichi

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