• DocumentCode
    2506597
  • Title

    Performance of statistical inference methods for the energy estimation of multiple sources

  • Author

    Couillet, Romain ; Guillaud, Maxime

  • Author_Institution
    Syst. Sci. & the Energy Challenge, Supelec, France
  • fYear
    2011
  • fDate
    28-30 June 2011
  • Firstpage
    673
  • Lastpage
    676
  • Abstract
    This article considers statistical inference of the transmit powers of multiple signal sources by a sensor network. Using random matrix methods, an exact expression of the posterior probability of the joint transmit powers is derived. This expression is used to implement the associated ML and MMSE detectors of the joint powers. These are compared for small system sizes against an asymptotically unbiased estimator obtained from large dimensional random matrix theory.
  • Keywords
    inference mechanisms; least mean squares methods; matrix algebra; maximum likelihood detection; probability; sensors; statistical analysis; ML detectors; MMSE detectors; asymptotic unbiased estimator; energy estimation; joint transmit powers; large dimensional random matrix theory; multiple signal sources; posterior probability; sensor network; statistical inference methods; Arrays; Eigenvalues and eigenfunctions; Joints; Maximum likelihood estimation; Mean square error methods; Tin;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Statistical Signal Processing Workshop (SSP), 2011 IEEE
  • Conference_Location
    Nice
  • ISSN
    pending
  • Print_ISBN
    978-1-4577-0569-4
  • Type

    conf

  • DOI
    10.1109/SSP.2011.5967791
  • Filename
    5967791