• DocumentCode
    1414574
  • Title

    Reliability-based code-search algorithms for maximum-likelihood decoding of block codes

  • Author

    Gazelle, David ; Snyders, Jakov

  • Author_Institution
    Dept. of Electr. Eng., Tel Aviv Univ., Israel
  • Volume
    43
  • Issue
    1
  • fYear
    1997
  • fDate
    1/1/1997 12:00:00 AM
  • Firstpage
    239
  • Lastpage
    249
  • Abstract
    Efficient code-search maximum-likelihood decoding algorithms, based on reliability information, are presented for binary Linear block codes. The codewords examined are obtained via encoding. The information set utilized for encoding comprises the positions of those columns of a generator matrix G of the code which, for a given received sequence, constitute the most reliable basis for the column space of G. Substantially reduced computational complexity of decoding is achieved by exploiting the ordering of the positions within this information set. The search procedures do not require memory; the codeword to be examined is constructed from the previously examined codeword according to a fixed rule. Consequently, the search algorithms are applicable to codes of relatively large size. They are also conveniently modifiable to achieve efficient nearly optimum decoding of particularly large codes
  • Keywords
    block codes; computational complexity; linear codes; matrix algebra; maximum likelihood decoding; reliability; search problems; binary linear block codes; code-search maximum-likelihood decoding algorithms; codeword; column space; computational complexity; generator matrix; information set; optimum decoding; ordering; received sequence; reliability-based code-search algorithms; search procedures; Block codes; Computational complexity; Convolutional codes; Encoding; Hamming weight; Maximum likelihood decoding; Vectors;
  • fLanguage
    English
  • Journal_Title
    Information Theory, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9448
  • Type

    jour

  • DOI
    10.1109/18.567691
  • Filename
    567691