• DocumentCode
    2060603
  • Title

    Analysis of convolutional codes on the erasure channel

  • Author

    Kurkoski, Brian M. ; Siegel, Paul H. ; Wolf, Jack K.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., California Univ., San Diego, La Jolla, CA, USA
  • fYear
    2004
  • fDate
    27 June-2 July 2004
  • Firstpage
    460
  • Abstract
    This paper describes the analysis of convolutional codes on the erasure channel. We compare the maximum likelihood (ML) sequence decision and the maximum a posteriori (MAP) symbol decision for codes, which are transmitted over the erasure channel. When a codeword from a linear error correcting code with elements from the field GF is transmitted over a q-ary erasure channel, the symbol error rate of the maximum likelihood (ML) sequence decision is the same as that of the symbol maximum a posteriori (MAP) probability decision. When decoding convolutional codes transmitted over an AWGN channel, it is widely known that the probability of symbol error for the Viterbi algorithm (which is a sequence ML decoder) is generally higher than that for the more complex BCJR algorithm (which is a symbol MAP decoder).
  • Keywords
    AWGN channels; Galois fields; Viterbi decoding; convolutional codes; error correction codes; error statistics; linear codes; maximum likelihood decoding; maximum likelihood sequence estimation; AWGN channel; GF filed; MAP probability decision; ML decoder; Viterbi algorithm; codeword; convolutional code; decoding; error probability symbol; linear error correcting code; maximum a posteriori symbol decision; maximum likelihood sequence decision; q-ary erasure channel; symbol error rate; AWGN channels; Communication channels; Convolutional codes; Electronic mail; Error analysis; Error correction codes; Lifting equipment; Linear code; Maximum likelihood decoding; Viterbi algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Theory, 2004. ISIT 2004. Proceedings. International Symposium on
  • Print_ISBN
    0-7803-8280-3
  • Type

    conf

  • DOI
    10.1109/ISIT.2004.1365495
  • Filename
    1365495