• DocumentCode
    1114875
  • Title

    Universal Context Based Decoding with Low-Density Parity-Check Codes

  • Author

    Wang, Li ; Shamir, Gil I.

  • Author_Institution
    Univ. of Utah, Salt Lake City
  • Volume
    11
  • Issue
    9
  • fYear
    2007
  • fDate
    9/1/2007 12:00:00 AM
  • Firstpage
    741
  • Lastpage
    743
  • Abstract
    Universal estimation strategies are proposed to improve channel decoding of sequences that contain context based redundancy. The new methods combine techniques from universal compression, such as the Burrows-Wheeler Transform (BWT) and segmentation of piecewise stationary memoryless sources (PSMS´s) with recently proposed methods of discrete denoising. Simulation results with systematic low density parity check (LDPC) codes show significant improvements of the proposed methods on standard decoding, even when the actual sequence context model is unknown in advance. The combined methods inherit advantages of each of the separate methods.
  • Keywords
    channel coding; data compression; decoding; parity check codes; Burrows-Wheeler transform; channel decoding; discrete denoising; low-density parity-check codes; piecewise stationary memoryless sources segmentation; sequence context model; universal compression; universal context based decoding; Code standards; Context modeling; Discrete transforms; Gas insulated transmission lines; Iterative decoding; Maximum likelihood decoding; Maximum likelihood estimation; Noise reduction; Parity check codes; Statistics;
  • fLanguage
    English
  • Journal_Title
    Communications Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1089-7798
  • Type

    jour

  • DOI
    10.1109/LCOMM.2007.070338
  • Filename
    4299421