• DocumentCode
    230807
  • Title

    Optimal observations transmission for distributed estimation under energy constraint

  • Author

    Alkhweldi, Marwan

  • Author_Institution
    Lane Dept. of Comput. Sci. & Electr. Eng., West Virginia Univ., Morgantown, WV, USA
  • fYear
    2014
  • fDate
    9-12 Dec. 2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This paper studies the problem of distributed parameter estimation in wireless sensor network under energy constraints. Optimization formulas that find the optimal sensors´ observations transmission that guarantee the best estimation performance from the available energy are derived. The network consists of sensors that are deployed over an area at random. Sensors´ observations are noisy measurements of an underlying field. Sensors have limited energy for the transmission process. Each sensor processes its observation prior to transmitting it to a fusion center, where a field parameter vector is estimated. Transmission channels between the sensors and the fusion center are assumed to be noisy parallel channels. The sensors´ locations, the noise probability density function, and the field characteristic function are assumed to be known at the fusion center. Simulation results which support the optimization formulas are shown.
  • Keywords
    distributed algorithms; optimisation; parameter estimation; probability; sensor placement; wireless channels; wireless sensor networks; distributed parameter estimation; energy constraint; field parameter vector estimation; fusion center; noise probability density function; noisy parallel channels; optimal sensor observations transmission; sensor location; transmission channels; wireless sensor network; Estimation; Optimization; Quantization (signal); Sensor phenomena and characterization; Vectors; Wireless sensor networks; Wireless sensor network; distributed parameter estimation; energy constraint; maximum-likelihood estimation; mean squared error;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence for Communication Systems and Networks (CIComms), 2014 IEEE Symposium on
  • Conference_Location
    Orlando, FL
  • Type

    conf

  • DOI
    10.1109/CICommS.2014.7014642
  • Filename
    7014642