Spectrum sensing algorithms via finite random matrix theory

Giuseppe Thadeu Freitas De Abreu, Wensheng Zhang, Yukitoshi Sanada

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    5 Citations (Scopus)

    Abstract

    We address the Primary User (PU) detection (spectrum sensing) problem, relevant to cognitive radio, from a finite random matrix theoretical (RMT) perspective. Specifically, we employ recently-derived closed-form and exact expressions for the distribution of the standard condition number (SCN) of uncorrelated and semi-correlated random dual Wishart matrices of finite sizes, to design Hypothesis-Testing algorithms to detect the presence of PU signals. An inherent characteristic of the SCN/RMT-based approach, is that no signal-to-noise ratio (SNR) estimation or any other information on the PU signal is required. On top of this property, other attractive advantages of the new techniques are: a) due to the accuracy of the finite SCN distributions, superior performance is achieved under a finite number of samples, compared to asymptotic RMT-based alternatives; b) since expressions to model the SCN statistics both in the absence (H0) and presence (H1) of PU signal are used, the statistics of the spectrum sensing problem in question is completely characterized; c) as a consequence of a) and b), accurate and simple analytical expressions for the receiver operating characteristic (ROC) - both in terms of PD as a function of PF and in terms of PA as a function of PM - are yielded. It is also shown that the proposed finite RMT-based algorithms outperforms all similar alternatives currently known in the literature, at a substantially lower complexity.

    Original languageEnglish
    Title of host publication2011 IEEE International Conference on Communications, ICC 2011
    DOIs
    Publication statusPublished - 2011 Sep 2
    Event2011 IEEE International Conference on Communications, ICC 2011 - Kyoto, Japan
    Duration: 2011 Jun 52011 Jun 9

    Publication series

    NameIEEE International Conference on Communications
    ISSN (Print)0536-1486

    Other

    Other2011 IEEE International Conference on Communications, ICC 2011
    CountryJapan
    CityKyoto
    Period11/6/511/6/9

    ASJC Scopus subject areas

    • Computer Networks and Communications
    • Electrical and Electronic Engineering

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  • Cite this

    De Abreu, G. T. F., Zhang, W., & Sanada, Y. (2011). Spectrum sensing algorithms via finite random matrix theory. In 2011 IEEE International Conference on Communications, ICC 2011 [5963196] (IEEE International Conference on Communications). https://doi.org/10.1109/icc.2011.5963196