• DocumentCode
    1112562
  • Title

    Performance Prediction for Energy Detection of Unknown Signals

  • Author

    Salt, J. Eric ; Nguyen, Ha H.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of Saskatchewan, Saskatoon, SK
  • Volume
    57
  • Issue
    6
  • fYear
    2008
  • Firstpage
    3900
  • Lastpage
    3904
  • Abstract
    This paper analyzes the energy detector that is commonly used to detect the presence of unknown information-bearing signals. The algorithm simply compares the energy (or power) in a sliding window to a threshold. The analysis allows for arbitrary spectra of information-bearing signal and noise processes. It yields two equations that relate five variables/parameters: the probability of false detection, the probability of missing a detection, window length, detection threshold, and signal-to-noise ratio (SNR). The probability density function of the detection variable is shown to be approximately Gamma distributed. All of the theoretical expressions and approximations are substantiated with simulation results.
  • Keywords
    gamma distribution; signal detection; Gamma distribution; arbitrary spectra; energy detection; false detection; noise processes; performance prediction; probability density function; signal-to-noise ratio; unknown information-bearing signals; Burst detection; Energy detection algorithm; burst detection; edge detection; energy detection algorithm; sliding window detector;
  • fLanguage
    English
  • Journal_Title
    Vehicular Technology, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9545
  • Type

    jour

  • DOI
    10.1109/TVT.2008.921617
  • Filename
    4476300