• DocumentCode
    610080
  • Title

    Multiterminal Source Coding for Many Sensors with Entropy Coding and Gaussian Process Regression

  • Author

    Cheng, Shukang

  • Author_Institution
    Sch. of Electr. & Comput. Eng., Univ. of Oklahoma, Tulsa, OK, USA
  • fYear
    2013
  • fDate
    20-22 March 2013
  • Firstpage
    480
  • Lastpage
    480
  • Abstract
    Summary form only given. In this paper, we take a different approach from the coding community. Instead of taking the usual route of quantization plus Slepian-Wolf coding, we do not perform any Slepian-Wolf coding on the transmitter side. We simply perform quantization on the sensor readings, compress the quantization indexes with conventional entropy coding, and send the compressed indexes to the receiver. On the decoder side, we simply perform entropy decoding and Gaussian process regression to reconstruct the joint source. To reduce the sum rate over all sensors, some sensors are censored and do not transmit anything to the decoder.
  • Keywords
    Gaussian processes; data compression; decoding; distributed sensors; entropy codes; quantisation (signal); regression analysis; source coding; telecommunication network routing; transmitters; Gaussian process regression; Slepian-Wolf coding; distributed sensor reading; entropy coding; entropy decoding; joint source reconstruction; multiterminal source coding; quantization index compression; quantization routing; receiver compression index; sum rate reduction; transmitter side; Correlation; Decoding; Entropy coding; Quantization (signal); Sensors; Source coding;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Data Compression Conference (DCC), 2013
  • Conference_Location
    Snowbird, UT
  • ISSN
    1068-0314
  • Print_ISBN
    978-1-4673-6037-1
  • Type

    conf

  • DOI
    10.1109/DCC.2013.62
  • Filename
    6543090