• DocumentCode
    2045756
  • Title

    Distributed non-parametric estimation in a bandwidth-constrained sensor network

  • Author

    Wang, Pu ; Li, Hongbin ; Fang, Jun

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Stevens Inst. of Technol., Hoboken, NJ
  • fYear
    2008
  • fDate
    19-21 March 2008
  • Firstpage
    1031
  • Lastpage
    1036
  • Abstract
    Non-parametric estimation of an unknown position parameter in a bandwidth-constrained wireless sensor network (WSN) is considered in this paper. Due to bandwidth constraint, each sensor is restricted to send only one bit of information to a fusion center. We propose a non-parametric estimator that employs a recently introduced adaptive quantization (AQ) scheme. Specifically, the position parameter is estimated as the sample mean of the quantization thresholds used in AQ. The proposed non-parametric estimator is based on the fact that the AQ thresholds asymptotically converge (in mean) to the unknown position parameter, under the condition that the position parameter is an integer multiple of the stepsize used in AQ. When the condition is not met, there is a bias which can, however, be made negligible by choosing the stepsize to be small (compared with the position parameter). Numerical results are provided to demonstrate the effectiveness of the proposed non-parametric estimator.
  • Keywords
    bandwidth allocation; estimation theory; quantisation (signal); sensor fusion; wireless sensor networks; adaptive quantization threshold scheme; bandwidth-constrained wireless sensor network; distributed nonparametric estimation; fusion center; sample mean; Bandwidth; Military communication; Parameter estimation; Quantization; Sensor fusion; Signal design; Signal processing; Surveillance; Wireless sensor networks; Working environment noise; Wireless sensor network; distributed estimation; non-parametric estimation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Sciences and Systems, 2008. CISS 2008. 42nd Annual Conference on
  • Conference_Location
    Princeton, NJ
  • Print_ISBN
    978-1-4244-2246-3
  • Electronic_ISBN
    978-1-4244-2247-0
  • Type

    conf

  • DOI
    10.1109/CISS.2008.4558670
  • Filename
    4558670