Novel frequency domain cyclic prefix autocorrelation based compressive spectrum sensing for cognitive radio

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

    2 Citations (Scopus)

    Abstract

    Cognitive radio (CR) has received increasing attention and is considered an important solution to the spectral crowding problem. The main idea behind CR technology is to utilize the unused spectral resources which are determined to be available for secondary user by effective spectrum sensing techniques. However, CR technology significantly depends on the spectrum sensing techniques which are applied to detect the presence of primary user (PU) signals. This paper focuses on detecting OFDM primaries using novel frequency-domain cyclic prefix (CP) autocorrelation based compressive spectrum sensing algorithms. To counteract the practical wireless channel effects, frequency domain approaches for PU signal detection are developed. The proposed spectrum sensing method eliminates the effects of both noise uncertainty and frequency selective channels. Using the frequency domain autocorrelation approach results in highly increased flexibility, facilitating robust wideband multi-mode, multi-channel sensing with low complexity. It also allows to sense weak PU signals which are partly overlapped by other strong PU or CR transmissions.

    Original languageEnglish
    Title of host publication2016 IEEE 83rd Vehicular Technology Conference (VTC Spring)
    PublisherIEEE
    ISBN (Electronic)9781509016983
    DOIs
    Publication statusPublished - 5 Jul 2016
    Publication typeA4 Article in a conference publication
    EventIEEE Vehicular Technology Conference -
    Duration: 1 Jan 1900 → …

    Conference

    ConferenceIEEE Vehicular Technology Conference
    Period1/01/00 → …

    Keywords

    • Cognitive radio
    • Energy detector
    • Frequency selective channel and noise uncertainty
    • OFDMVCP
    • Time and/or frequency domain CP autocorrelation based compressive spectrum sensing

    Publication forum classification

    • Publication forum level 1

    ASJC Scopus subject areas

    • Electrical and Electronic Engineering
    • Computer Science Applications
    • Applied Mathematics

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