• DocumentCode
    795995
  • Title

    Optimal sectionalization of a trellis

  • Author

    Lafourcade, Alec ; Vardy, Alexander

  • Author_Institution
    Coordinated Sci. Lab., Illinois Univ., Urbana, IL, USA
  • Volume
    42
  • Issue
    3
  • fYear
    1996
  • fDate
    5/1/1996 12:00:00 AM
  • Firstpage
    689
  • Lastpage
    703
  • Abstract
    While the complexity of trellis decoding for a given block code is essentially a function of the number of states and branches in its trellis, the decoding complexity may be often reduced by means of an appropriate sectionalization of the trellis. Notwithstanding the many examples of such sectionalizations for particular codes that appeared in the literature, no systematic method for finding the best sectionalization of a given trellis is presently known. We present a polynomial-time algorithm which produces the optimal sectionalization of a given trellis T in time O(n2), where n is the length of the code generated by T. The algorithm is developed in a general setting of certain operations and functions defined on the set of trellises; it therefore applies to both linear and nonlinear codes, and easily accommodates a broad range of optimality criteria. The particular optimality criterion based on minimizing the total number of additions and comparisons required for maximum-likelihood trellis decoding is investigated in detail: several different methods for decoding a given trellis are discussed and compared in a number of examples. Finally, analysis of the dynamical properties of certain optimal sectionalizations is presented
  • Keywords
    block codes; computational complexity; directed graphs; linear codes; maximum likelihood decoding; optimisation; polynomials; additions; block code; code length; dynamical properties; edge labeled directed graph; linear codes; maximum likelihood trellis decoding; nonlinear codes; optimal sectionalization; optimality criterion; polynomial-time algorithm; trellis decoding complexity; Binary codes; Block codes; Engineering profession; Information theory; Maximum likelihood decoding; Viterbi algorithm;
  • fLanguage
    English
  • Journal_Title
    Information Theory, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9448
  • Type

    jour

  • DOI
    10.1109/18.490504
  • Filename
    490504