• DocumentCode
    1549977
  • Title

    An improved method to compute lists of binary vectors that optimize a given weight function with application to soft-decision decoding

  • Author

    Valembois, Antoine ; Fossorier, Marc

  • Author_Institution
    Dept. of Electr. Eng., Hawaii Univ., Honolulu, HI, USA
  • Volume
    5
  • Issue
    11
  • fYear
    2001
  • Firstpage
    456
  • Lastpage
    458
  • Abstract
    Many algorithms, tree-searching and decoding algorithms in particular, need to generate some lists of binary vectors by increasing value of a given weight function and without omission. To this end, there are not many alternatives to the Dijkstra and the Viterbi algorithm. In this letter a technique suggested by Battail in 1986 to perform this task is reviewed. Then a new technique is deduced from it, that proves to be more efficient than all the others. As an illustration of its good performance we compare a maximum-likelihood-decoding (MLD) algorithm that can be derived from it, with current state-of-the-art complete MLD algorithms for general binary linear codes.
  • Keywords
    binary codes; linear codes; maximum likelihood decoding; optimisation; tree searching; binary linear codes; binary vectors; maximum-likelihood-decoding algorithm; soft-decision decoding; tree-searching; weight function optimization; Convolutional codes; Decision trees; Hamming weight; Linear code; Maximum likelihood decoding; Optimization methods; Search methods; Vectors; Viterbi algorithm;
  • fLanguage
    English
  • Journal_Title
    Communications Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1089-7798
  • Type

    jour

  • DOI
    10.1109/4234.966032
  • Filename
    966032