• DocumentCode
    2498584
  • Title

    New Approach to Order Statistics Decoding of Long Linear Block Codes

  • Author

    Kabat, Andrzej ; Guilloud, Frederic ; Pyndiah, Ramesh

  • Author_Institution
    CNRS TAMCIC, Brest
  • fYear
    2007
  • fDate
    26-30 Nov. 2007
  • Firstpage
    1467
  • Lastpage
    1471
  • Abstract
    In this paper we propose the Arranged List of the Most a priori Likely Tests (ALMLT) algorithm, which is an efficient algorithm for reliability-based soft-decision decoding of long linear block codes. Based on order statistics, we define the mean bit reliabilities and use them to estimate the a priori weight of an error pattern. Each error pattern is represented by a test vector. All the test vectors are sorted according to the increasing order of their weights and saved in a list. Since these weights only depend on the channel SNR, the generation of the list is performed off the transmission. The list of test vectors is then used to decode the received binary sequence similarly as in the Ordered Statistic Decoding (OSD) algorithm. The ALMLT algorithm outperforms the OSD(2) algorithm as illustrated by decoding the binary image of the (255, 239,17) RS code and has a lower mean number of tests, while using the same stopping criterion.
  • Keywords
    binary sequences; block codes; decoding; error statistics; linear codes; arranged list of the most a priori likely tests algorithm; error pattern; long linear block codes; mean bit reliabilities; order statistics decoding; received binary sequence; soft-decision decoding; Binary sequences; Block codes; Error analysis; Iterative algorithms; Iterative decoding; Maximum likelihood decoding; Statistical analysis; Statistics; Testing; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Global Telecommunications Conference, 2007. GLOBECOM '07. IEEE
  • Conference_Location
    Washington, DC
  • Print_ISBN
    978-1-4244-1042-2
  • Electronic_ISBN
    978-1-4244-1043-9
  • Type

    conf

  • DOI
    10.1109/GLOCOM.2007.282
  • Filename
    4411192