• DocumentCode
    3035018
  • Title

    Reduced-search BCJR algorithms

  • Author

    Franz, V. ; Anderson, J.B.

  • Author_Institution
    Lehrstuhl fur Nachrichtentech., Tech. Univ. Munchen, Germany
  • fYear
    1997
  • fDate
    29 Jun-4 Jul 1997
  • Firstpage
    230
  • Abstract
    Summary form only given. There is great interest in coding systems that employ various kinds of code concatenation. In all of these schemes, an important element in the decoder is the MAP decoder, a device that puts out the probability of trellis states or data bits, rather than simply the most likely state or bit. For trellis encoding and Markov data, the MAP decoder is a special scheme, the BCJR algorithm. Unfortunately, the BCJR algorithm is computationally intensive. The purpose of this paper is to present a strong simplification of it that does not sacrifice the decoder error performance. Our algorithms exploit the fact that most working probabilities in the BCJR algorithm are very small, and with a little care can be ignored without losing performance. We find that the most successful strategy is to ignore working probabilities that fall below a certain threshold
  • Keywords
    Markov processes; concatenated codes; decoding; maximum likelihood estimation; probability; search problems; trellis codes; BCJR algorithm; MAP decoder; Markov data; code concatenation; coding systems; data bits; error performance; reduced-search BCJR algorithms; simplification; trellis encoding; trellis states; working probabilities; Concatenated codes; Encoding; Error probability; Iterative decoding; Noise reduction; USA Councils;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Theory. 1997. Proceedings., 1997 IEEE International Symposium on
  • Conference_Location
    Ulm
  • Print_ISBN
    0-7803-3956-8
  • Type

    conf

  • DOI
    10.1109/ISIT.1997.613145
  • Filename
    613145