Energy detection-based spectrum sensing over generalized and extreme fading channels

Paschalis Sofotasios, Eric Rebeiz, Li Zhang, Theodoros Tsiftsis, Danijela Cabric, Steven Freear

    Research output: Contribution to journalArticleScientificpeer-review

    136 Citations (Scopus)

    Abstract

    Energy detection (ED) is a simple and popular
    method of spectrum sensing in cognitive radio systems. It is also
    widely known that the performance of sensing techniques is largely
    affected when users experience fading effects. This paper inves-
    tigates the performance of an energy detector over generalized
    κ−μ and κ−μ extreme fading channels, which have been shown
    to provide remarkably accurate fading characterization. Novel
    analytic expressions are firstly derived for the corresponding av-
    erage probability of detection for the case of single-user detection.
    These results are subsequently extended to the case of square-law
    selection (SLS) diversity and for collaborative detection scenarios.
    As expected, the performance of the detector is highly dependent
    upon the severity of fading since even small variations of the fading
    conditions affect significantly the value of the average probability
    of detection. Furthermore, the performance of the detector im-
    proves substantially as the number of branches or collaborating
    users increase in both severe and moderate fading conditions,
    whereas it is shown that the κ−μ extreme model is capable of
    accounting for fading variations even at low signal-to-noise values.
    The offered results are particularly useful in assessing the effect
    of fading in ED-based cognitive radio communication systems;
    therefore, they can be used in quantifying the associated tradeoffs
    between sensing performance and energy efficiency in cognitive
    radio networks.
    Original languageEnglish
    Pages (from-to)1031
    Number of pages1040
    JournalIEEE Transactions on Vehicular Technology
    Volume62
    Issue number3
    DOIs
    Publication statusPublished - Mar 2013
    Publication typeA1 Journal article-refereed

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