Joint Signal Detection and Classification Based on First-Order Cyclostationarity For Cognitive Radios

  • O. A. Dobre1Email author,

    Affiliated with

    • S. Rajan2 and

      Affiliated with

      • R. Inkol2

        Affiliated with

        EURASIP Journal on Advances in Signal Processing20092009:656719

        DOI: 10.1155/2009/656719

        Received: 15 February 2009

        Accepted: 8 July 2009

        Published: 2 September 2009

        Abstract

        The sensing of the radio frequency environment has important commercial and military applications and is fundamental to the concept of cognitive radio. The detection and classification of low signal-to-noise ratio signals with relaxed a priori information on their parameters are essential prerequisites to the demodulation of an intercepted signal. This paper proposes an algorithm based on first-order cyclostationarity for the joint detection and classification of frequency shift keying (FSK) and amplitude-modulated (AM) signals. A theoretical analysis of the algorithm performance is also presented and the results compared against a performance benchmark based on the use of limited assumed a priori information on signal parameters at the receive-side. The proposed algorithm has the advantage that it avoids the need for carrier and timing recovery and the estimation of signal and noise powers.

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        Authors’ Affiliations

        (1)
        Faculty of Engineering and Applied Science, Memorial University of Newfoundland
        (2)
        Defence Research and Development Canada

        Copyright

        © O. A. Dobre et al. 2009

        This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.