Non-asymptotic analysis of scaled largest eigenvalue based spectrum sensing

Lu Wei*

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

    2 Citations (Scopus)

    Abstract

    In this paper, we analyze the non-asymptotic performance of scaled largest eigenvalue based detection, which is an optimal detector in the presence of a single primary user. Exact distributions of the test statistics have been derived, which lead to finite-dimensional characterizations of the false alarm probability. These results are obtained by taking advantage of the properties of the Mellin transform for products of independent random variables. Simulations are provided to verify the derived results, and to compare with the asymptotic result in literature.

    Original languageEnglish
    Title of host publication4th International Congress on Ultra Modern Telecommunications and Control Systems 2012, ICUMT 2012
    Pages955-958
    Number of pages4
    DOIs
    Publication statusPublished - 2012
    MoE publication typeA4 Conference publication
    EventInternational Congress on Ultra Modern Telecommunications and Control Systems - St. Petersburg, Russian Federation
    Duration: 3 Oct 20125 Oct 2012
    Conference number: 4

    Conference

    ConferenceInternational Congress on Ultra Modern Telecommunications and Control Systems
    Abbreviated titleICUMT
    Country/TerritoryRussian Federation
    CitySt. Petersburg
    Period03/10/201205/10/2012

    Keywords

    • Cognitive radio
    • multi-antenna spectrum sensing
    • multivariate analysis
    • the Mellin transform

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