• DocumentCode
    1158104
  • Title

    Distributed source coding using syndromes (DISCUS): design and construction

  • Author

    Pradhan, S. Sandeep ; Ramchandran, Kannan

  • Author_Institution
    Electr. Eng. & Comput. Sci. Dept., Univ. of Michigan, Ann Arbor, MI, USA
  • Volume
    49
  • Issue
    3
  • fYear
    2003
  • fDate
    3/1/2003 12:00:00 AM
  • Firstpage
    626
  • Lastpage
    643
  • Abstract
    We address the problem of compressing correlated distributed sources, i.e., correlated sources which are not co-located or which cannot cooperate to directly exploit their correlation. We consider the related problem of compressing a source which is correlated with another source that is available only at the decoder. This problem has been studied in the information theory literature under the name of the Slepian-Wolf (1973) source coding problem for the lossless coding case, and as "rate-distortion with side information" for the lossy coding case. We provide a constructive practical framework based on algebraic trellis codes dubbed as DIstributed Source Coding Using Syndromes (DISCUS), that can be applicable in a variety of settings. Simulation results are presented for source coding of independent and identically distributed (i.i.d.) Gaussian sources with side information available at the decoder in the form of a noisy version of the source to be coded. Our results reveal the promise of this approach: using trellis-based quantization and coset construction, the performance of the proposed approach is 2-5 dB from the Wyner-Ziv (1976) bound.
  • Keywords
    Gaussian processes; algebraic codes; correlation methods; decoding; quantisation (signal); rate distortion theory; source coding; trellis codes; algebraic trellis codes; correlated distributed source compression; coset construction; decoder; distributed source coding using syndromes; i.i.d. Gaussian sources; independent identically distributed sources; information theory; lossless coding; lossy coding; noisy source; rate-distortion; side information; simulation results; trellis-based quantization; Convolutional codes; Decoding; Gaussian noise; Image sensors; Information theory; Layout; Quantization; Sensor arrays; Sensor phenomena and characterization; Source coding;
  • fLanguage
    English
  • Journal_Title
    Information Theory, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9448
  • Type

    jour

  • DOI
    10.1109/TIT.2002.808103
  • Filename
    1184140