• DocumentCode
    768979
  • Title

    Canonical detection in spherically invariant noise

  • Author

    Conte, E. ; Di Bisceglie, M. ; Longo, Maurizio ; Lops, M.

  • Author_Institution
    Dipartimento di Ingegneria Elettronica, Naples Univ., Italy
  • Volume
    43
  • Issue
    38020
  • fYear
    1995
  • Firstpage
    347
  • Lastpage
    353
  • Abstract
    The paper deals with the detection of signals with unknown parameters in impulsive noise, modeled as a spherically symmetric random process. The proposed model subsumes several interesting families of noise amplitude distributions: generalized Cauchy, generalized Laplace, generalized Gaussian, contaminated normal. It also allows handling of the case of correlated noise by a whitening approach. The generalized maximum likelihood decision strategy is adopted, resulting in a canonical detector, which is independent of the amplitude distribution of the noise. A general method for performance evaluation is outlined, and a comprehensive performance analysis is carried out for the case of M-ary equal-energy orthogonal signals under several distributional assumptions for the noise. The performance is contrasted with that of the maximum likelihood receiver for completely known signals, so as to assess the loss due to the a-priori uncertainty as to the signal parameters.<>
  • Keywords
    Gaussian distribution; correlation methods; maximum likelihood detection; maximum likelihood estimation; noise; normal distribution; parameter estimation; performance evaluation; probability; random processes; receivers; M-ary equal-energy orthogonal signals; a-priori uncertainty; canonical detection; contaminated normal distribution; correlated noise; generalized Cauchy distribution; generalized Gaussian distribution; generalized Laplace distribution; generalized maximum likelihood decision; impulsive noise; maximum likelihood receiver; noise amplitude distributions; performance analysis; performance evaluation; signal detection; signal parameters; spherically invariant noise; spherically symmetric random process; whitening approach; Detectors; Gaussian noise; Maximum likelihood detection; Noise level; Performance analysis; Performance loss; Random processes; Signal detection; Signal processing; Uncertainty;
  • fLanguage
    English
  • Journal_Title
    Communications, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0090-6778
  • Type

    jour

  • DOI
    10.1109/26.380053
  • Filename
    380053