• DocumentCode
    2607617
  • Title

    Distributed encoding of sensor data

  • Author

    Neuhoff, David L. ; Marco, Daniel

  • Author_Institution
    Electr. Eng. & Comput. Sci., Michigan Univ., Ann Arbor, MI, USA
  • fYear
    2002
  • fDate
    20-25 Oct. 2002
  • Firstpage
    108
  • Lastpage
    110
  • Abstract
    In this paper, we ignore transmission issues and focus on the total number of bits to transmit to the collector to form a reconstruction of the field with a given MSE. We assume that all sensors can transmit bits to the collector without error. With this assumption, with total number of bits as the cost measure, and with the style of coding, it can be argued that sensor-to-sensor relaying offers no advantages. This problem is similar to image coding and transmission, except that the quantization, encoding and transmission are constrained to take place separately at each sensor (pixel location), in contrast to traditional image coding and transmission, wherein the entire image is available for quantization, encoding, and transmission. Due to the need to separately encode values from separate sensors, we pursue a Slepian-Wolf style coding approach.
  • Keywords
    mean square error methods; rate distortion theory; sensor fusion; source coding; Distributed Encoding; MSE; Slepian-Wolf style coding; continuous-time sources; mean squared error distortion; rate-distortion function; sensor data; sensor networks; separate sensors; source coding; Computer science; Costs; Decoding; Encoding; Image coding; Image reconstruction; Quantization; Random processes; Temperature sensors; Wireless sensor networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Theory Workshop, 2002. Proceedings of the 2002 IEEE
  • Print_ISBN
    0-7803-7629-3
  • Type

    conf

  • DOI
    10.1109/ITW.2002.1115429
  • Filename
    1115429