• DocumentCode
    1087124
  • Title

    Distributed source coding for sensor networks

  • Author

    Xiong, Zixiang ; Liveris, Angelos D. ; Cheng, Samuel

  • Author_Institution
    Dept. of Electr. Eng., Texas A&M Univ., College Station, TX, USA
  • Volume
    21
  • Issue
    5
  • fYear
    2004
  • Firstpage
    80
  • Lastpage
    94
  • Abstract
    In recent years, sensor research has been undergoing a quiet revolution, promising to have a significant impact throughout society that could quite possibly dwarf previous milestones in the information revolution. Realizing the great promise of sensor networks requires more than a mere advance in individual technologies. It relies on many components working together in an efficient, unattended, comprehensible, and trustworthy manner. One of the enabling technologies in sensor networks is the distributed source coding (DSC), which refers to the compression of the multiple correlated sensor outputs that does not communicate with each other. DSC allows a many-to-one video coding paradigm that effectively swaps encoder-decoder complexity with respect to conventional video coding, thereby representing a fundamental concept shift in video processing. This article has presented an intensive discussion on two DSC techniques, namely Slepian-Wolf coding and Wyner-Ziv coding. The Slepian and Wolf coding have theoretically shown that separate encoding is as efficient as joint coding for lossless compression in channel coding.
  • Keywords
    combined source-channel coding; computational complexity; video coding; wireless sensor networks; Slepian-Wolf coding; Wyner-Ziv coding; binary symmetric case; channel coding; distributed source coding; encoder-decoder complexity; lossless compression; many-to-one video coding paradigm; quadratic Gaussian case; sensor networks; video processing; Biosensors; Channel coding; Chemical and biological sensors; Decoding; Source coding; Temperature sensors; Vibration measurement; Video coding; Video compression; Wireless sensor networks;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Magazine, IEEE
  • Publisher
    ieee
  • ISSN
    1053-5888
  • Type

    jour

  • DOI
    10.1109/MSP.2004.1328091
  • Filename
    1328091