• DocumentCode
    2517729
  • Title

    The slope scaling parameter for general channels, decoders, and ensembles

  • Author

    Ezri, Jeremie ; Montanari, Andrea ; Oh, Sewoong ; Urbanke, Ruediger

  • Author_Institution
    Sch. of Comput. & Commun. Sci., EPFL, Lausanne
  • fYear
    2008
  • fDate
    6-11 July 2008
  • Firstpage
    1443
  • Lastpage
    1447
  • Abstract
    Scaling laws are a powerful way to analyze the performance of moderately sized iteratively decoded sparse graph codes. Our aim is to provide an easily usable finite-length optimization tool that is applicable to the wide variety of channels, blocklengths, error probability requirements, and decoders that one encounters for practical systems. The tool is aimed at non-experts in the field, who need to quickly find code designs that are comparable with the best known codes available today but do not have the luxury of spending months in doing so. In previous work we have shown how to compute scaling parameters for transmission over the binary erasure channel, as well as general channels and general quantized message-passing decoders when applied to regular ensembles. In this paper we show how to compute the message variance for a fixed number of iterations for irregular low-density parity-check ensembles. From these calculations the basic scaling parameter alpha can be deduced by determining the leading term of the limiting expression when the number of iterations tends to infinity and the channel parameter approaches the density evolution threshold.
  • Keywords
    error statistics; iterative decoding; optimisation; parity check codes; binary erasure channel; error probability; finite-length optimization; iterative decoding; low-density parity-check codes; quantized message-passing decoders; scaling laws; slope scaling parameter; sparse graph codes; Convergence; Differential equations; Error probability; H infinity control; Iterative decoding; Lead; Parity check codes; Performance analysis; Power engineering computing; Statistical analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Theory, 2008. ISIT 2008. IEEE International Symposium on
  • Conference_Location
    Toronto, ON
  • Print_ISBN
    978-1-4244-2256-2
  • Electronic_ISBN
    978-1-4244-2257-9
  • Type

    conf

  • DOI
    10.1109/ISIT.2008.4595226
  • Filename
    4595226