Efficiency of energy detection for spectrum sensing in a Poisson field of interferers

A U Makarfi, K A Hamdi

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

    Abstract

    Spectrum sensing is arguably the most important task expected of a cognitive radio. An effective spectrum sensing algorithm enables the cognitive radio to transmit without causing harmful interference to the licensed user. However, in a multi-user environment, the aggregate interference to the sensing node may adversely affect its sensing performance. In this paper, we investigate the performance of a sensing node in the presence of unlicensed user interference in a non-cooperating secondary network. We model the interference as a Poisson point process in the two dimensional plane and characterize the effect of various factors such as the sensing time and density of interferers on the overall performance of the spectrum sensor. To this end, novel expressions have been developed to calculate the false alarm and detection probabilities of an energy detection sensor in an interference environment. The results obtained were verified using Monte Carlo simulation techniques.
    Original languageEnglish
    Title of host publicationWireless Communications and Networking Conference (WCNC), 2012 IEEE
    Pages1023-1028
    Number of pages6
    DOIs
    Publication statusPublished - Apr 2012
    Event2012 IEEE Wireless Communications and Networking Conference, WCNC 2012 - Paris
    Duration: 1 Jul 2012 → …

    Conference

    Conference2012 IEEE Wireless Communications and Networking Conference, WCNC 2012
    CityParis
    Period1/07/12 → …

    Keywords

    • Monte Carlo methods
    • cognitive radio
    • probability
    • radiofrequency interference
    • stochastic processes
    • Monte Carlo simulation techniques
    • Poisson field of interferers
    • Poisson point process
    • detection probability
    • effective spectrum sensing algorithm
    • energy detection efficiency
    • energy detection sensor
    • false alarm probability
    • interference environment
    • multiuser environment
    • noncooperating secondary network
    • sensing node
    • spectrum sensor
    • unlicensed user interference
    • Aggregates
    • Analytical models
    • Error probability
    • Handheld computers
    • Interference
    • Sensors

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