• DocumentCode
    1415978
  • Title

    Correlation-Based Detection of OFDM Signals in the Angular Domain

  • Author

    Turunen, Vesa ; Kosunen, Marko ; Vääräkangas, Mikko ; Ryynänen, Jussi

  • Author_Institution
    Dept. of Micro- & Nanosci., Aalto Univ., Espoo, Finland
  • Volume
    61
  • Issue
    3
  • fYear
    2012
  • fDate
    3/1/2012 12:00:00 AM
  • Firstpage
    951
  • Lastpage
    958
  • Abstract
    Spectrum sensing is an essential part of future cognitive radios, as the spectrum sensor provides information about the utilization of the surrounding radio spectrum. Several approaches to implementing spectrum sensing have been proposed in the literature, one of them being the class of feature detectors. Cyclostationary feature detectors are, in general, considered to be superior in performance but suffer from high implementation complexity. Therefore, most studies still utilize energy detectors, which may not reach the performance requirements set for practical implementations. This paper presents angular domain feature detection algorithms that are based on cyclostationary properties. Angular domain signal processing is shown to simplify the implementation considerably while preserving comparable performance. Moreover, a new detection algorithm that leads to multiplier-free implementation and reduces the memory requirements, compared with any previous approaches, is proposed.
  • Keywords
    OFDM modulation; correlation methods; radio spectrum management; signal detection; OFDM signals; angular domain; correlation-based detection; cyclostationary feature detectors; energy detectors; signal processing; spectrum sensing; surrounding radio spectrum; Correlation; Detection algorithms; Detectors; Estimation; Feature extraction; OFDM; Vectors; Autocorrelation; cognitive radio; detection algorithms; digital signal processing; field-programmable gate arrays; orthogonal frequency-division multiplex (OFDM);
  • fLanguage
    English
  • Journal_Title
    Vehicular Technology, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9545
  • Type

    jour

  • DOI
    10.1109/TVT.2012.2183009
  • Filename
    6123219