• DocumentCode
    3226576
  • Title

    Distributed Source Coding Using Raptor Codes for Hidden Markov Sources

  • Author

    Fresia, M. ; Vandendorpe, L. ; Poor, H.V.

  • Author_Institution
    Princeton Univ., Princeton
  • fYear
    2008
  • fDate
    25-27 March 2008
  • Firstpage
    517
  • Lastpage
    517
  • Abstract
    Interest in distributed source coding (DSC) has increased in recent years due to the development of wireless networks. In this paper we propose a solution based on a new rateless class of codes, the Raptor codes. In real applications (where the data source length and the correlation between the sources may vary), rateless codes can be naturally adapted by generating just a single codeword with suitable length. Raptor codes were already considered by Caire et al. (2005) for the lossless compression of a single source.
  • Keywords
    codes; hidden Markov models; source coding; Raptor codes; codeword; data source length; distributed source coding; hidden Markov sources; lossless compression; source correlation; wireless networks; Bit error rate; Data compression; Entropy; Hidden Markov models; Iterative algorithms; Iterative decoding; Message passing; Redundancy; Source coding; Wireless networks; Distributed Source coding; Hidden Markov model; Raptor codes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Compression Conference, 2008. DCC 2008
  • Conference_Location
    Snowbird, UT
  • ISSN
    1068-0314
  • Print_ISBN
    978-0-7695-3121-2
  • Type

    conf

  • DOI
    10.1109/DCC.2008.89
  • Filename
    4483344