• DocumentCode
    1620486
  • Title

    A parallel Viterbi algorithm for decoding convolutional codes on SIMD machines

  • Author

    Lin, Kuo-Yu ; Krishna, Hari

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Syracuse Univ., NY, USA
  • fYear
    1992
  • Firstpage
    361
  • Abstract
    The parallel implementation aspects of the Viterbi algorithm, which gives the maximum likelihood solution to decoding conventional codes, are studied. The interconnection of the trellis diagram of a binary convolutional code is similar to the shuffle exchange. This similarity is exploited to present a parallel version of the Viterbi algorithm. The proposed algorithm avoids tasks such as appending and exchanging the survivor lists that are considered pragmatic issues to be accommodated in implementing the Viterbi algorithm. This is done by introducing an additional back-tracking procedure which is almost identical to the forward path where branch and path metrics are computed. The parallel Viterbi algorithm is implemented on the connection machine which is a SIMD (single instruction stream and multiple data stream) parallel machine
  • Keywords
    convolutional codes; decoding; maximum likelihood estimation; parallel algorithms; parallel machines; trellis codes; SIMD machines; back-tracking procedure; connection machine; convolutional codes; decoding; interconnection; maximum likelihood solution; parallel Viterbi algorithm; parallel implementation aspects; trellis diagram; Block codes; Carbon capture and storage; Convolutional codes; Delay; Encoding; Joining processes; Maximum likelihood decoding; Parallel machines; Very large scale integration; Viterbi algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Circuits and Systems, 1992., Proceedings of the 35th Midwest Symposium on
  • Conference_Location
    Washington, DC
  • Print_ISBN
    0-7803-0510-8
  • Type

    conf

  • DOI
    10.1109/MWSCAS.1992.271286
  • Filename
    271286