• DocumentCode
    1757537
  • Title

    Efficient Energy Detection Methods for Spectrum Sensing Under Non-Flat Spectral Characteristics

  • Author

    Dikmese, Sener ; Sofotasios, Paschalis C. ; Ihalainen, Tero ; Renfors, Markku ; Valkama, Mikko

  • Author_Institution
    Dept. of Electron. & Commun. Eng., Tampere Univ. of Technol., Tampere, Finland
  • Volume
    33
  • Issue
    5
  • fYear
    2015
  • fDate
    42125
  • Firstpage
    755
  • Lastpage
    770
  • Abstract
    Cognitive radio is an emerging wireless technology that is capable of efficiently coordinating the use of the currently scarce spectrum resources, and spectrum sensing constitutes its most crucial operation. This paper proposes wideband multichannel spectrum sensing methods utilizing fast Fourier transform or filter-bank-based methods for spectrum analysis. Fine-grained spectrum analysis facilitates optimal energy detection in practical scenarios where the transmitted signal, channel frequency response, and/or receiver frequency response do not follow the commonly assumed boxcar model, which typically assumes, among other things, narrow-band communications with flat spectral characteristics. Such sensing schemes can be tuned to the spectral characteristics of the target primary user signals, allowing simultaneous sensing of multiple target primary signals with low additional complexity. This model is also extended to accounting for the specific scenario of detecting a reappearing primary user during secondary transmission, as well as in spectrum sensing scenarios where the frequency range of a primary user is unknown. Novel analytic expressions are derived for the corresponding probability of false alarm and probability of detection in each case, while the useful concept of the area under the receiver operating characteristics curve is additionally introduced as a single scalar metric for evaluating the overall performance of the proposed spectrum sensing algorithms and scenarios. The derived expressions have a rather simple algebraic representation, which renders them convenient to handle both analytically and numerically. The offered results are also extensively validated through comparisons with respective results from computer simulations and are subsequently employed in evaluating each technique analytically, which provides meaningful insights that are anticipated to be useful in future deployments of cognitive radio systems.
  • Keywords
    channel bank filters; cognitive radio; computational complexity; fast Fourier transforms; frequency response; probability; radio receivers; radio spectrum management; sensitivity analysis; signal detection; spectral analysis; wireless channels; Fine-grained spectrum analysis; channel frequency response; cognitive radio; energy detection method; false alarm probability; fast Fourier transform; filter bank; narrowband communication; nonflat spectral characteristics; primary user; receiver frequency response; receiver operating characteristic curve; secondary transmission; wideband multichannel spectrum sensing method; wireless technology; Complexity theory; Context; Noise; Receivers; Sensors; Wideband; Wireless communication; AUC; Cognitive radio; multichannel communications; non-flat spectral characteristics; radiometer; signal detection; spectrum sensing; wideband communications;
  • fLanguage
    English
  • Journal_Title
    Selected Areas in Communications, IEEE Journal on
  • Publisher
    ieee
  • ISSN
    0733-8716
  • Type

    jour

  • DOI
    10.1109/JSAC.2014.2361074
  • Filename
    6914542