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    Enhanced energy detection based spectrum sensing in cognitive radio networks using Random Matrix Theory

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    Publication date
    2014
    Author
    Ahmed, A.
    Hu, Yim Fun
    Noras, James M.
    Keyword
    White space; Spectrum sensing; Cognitive radio networks; Eigen space analysis; Random matrix theory
    Peer-Reviewed
    Yes
    
    Metadata
    Show full item record
    Abstract
    Opportunistic secondary usage of underutilised radio spectrum is currently of great interest and the use of TV White Spaces (TVWS) has been considered for Long Term Evolution (LTE) broadband services. However, wireless microphones operating in TV bands pose a challenge to TVWS opportunistic access. Efficient and proactive spectrum sensing could prevent harmful interference between collocated devices, but existing spectrum sensing schemes such as energy detection and schemes based on Random Matrix Theory (RMT) have performance limitations. We propose a new blind spectrum sensing scheme with higher performance based on RMT supported by a new formula for the estimation of noise variance. The performance of the proposed scheme has been evaluated through extensive simulations on wireless microphone signals. The proposed scheme has also been compared to energy detection schemes, and shows higher performance in terms of the probability of false alarm (Pfa) and probability of detection (Pd).
    URI
    http://hdl.handle.net/10454/10576
    Version
    No full-text available in the repository
    Citation
    Ahmed A, Hu YF and Noras JM (2014) Noise Variance Estimation for Spectrum Sensing in Cognitive Radio Networks. Aasri Conference on Circuit and Signal Processing (Csp 2014) 23-25 Jul 2014, Manchester, UK: 37-43.
    Link to publisher’s version
    https://doi.org/10.1109/CSNDSP.2014.6923859
    Type
    Conference Paper
    Collections
    Engineering and Informatics Publications

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