• DocumentCode
    711968
  • Title

    Spectrum Sensing Algorithm Based on Estimated Covariance Matrix MME Detection

  • Author

    Shaolin Yao ; Zheng Bao Zhang

  • Author_Institution
    Dept. of Inf. Eng., Ordnance Eng. Coll., Shijiazhuang, China
  • fYear
    2015
  • fDate
    24-26 April 2015
  • Firstpage
    926
  • Lastpage
    930
  • Abstract
    Aiming at the problem that the MME detection algorithm has a poor detection performance while sampling data length is small, a spectrum sensing algorithm based on estimated covariance matrix MME was proposed. Covariance matrix estimation of sampling data was made using the oracle-approximating shrinkage estimator, then taking the ratio of MME of estimated covariance matrix as the detection statistic, obtaining the detection threshold through the computer simulation. The results show that the proposed algorithm has better detection performance compared with MME algorithm.
  • Keywords
    covariance matrices; eigenvalues and eigenfunctions; radio spectrum management; signal detection; covariance matrix estimation; detection statistic; detection threshold; estimated covariance matrix MME detection; maximum-minimum eigenvalue; oracle-approximating shrinkage estimator; spectrum sensing algorithm; Algorithm design and analysis; Covariance matrices; Detection algorithms; Eigenvalues and eigenfunctions; Estimation; Sensors; Signal processing algorithms; cognitive radio; covariance matrix estimation; maximum-minimum eigenvalue; spectrum sensing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science and Control Engineering (ICISCE), 2015 2nd International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4673-6849-0
  • Type

    conf

  • DOI
    10.1109/ICISCE.2015.210
  • Filename
    7120750