Spectrum Sensing Using Weighted Covariance Matrix in Rayleigh Fading Channels

M. Jin, Q. Guo, J. Xi, Y. Li, Y. Yu, David Huang

    Research output: Contribution to journalArticlepeer-review

    35 Citations (Scopus)


    © 1967-2012 IEEE. Covariance-based detection is a low-complexity blind spectrum sensing scheme that exploits spatial and/or temporal correlations of primary signals. However, its performance severely degrades with the decrease of signal correlations. In this work, a weighted-covariance-based detector is proposed by introducing data-aided weights to the covariance matrix. The false alarm probability, decision threshold, and detection probability are analyzed in the low signal-to-noise ratio (SNR) regime, and their approximate analytical expressions are derived based on the central limit theorem. The analyses are verified through simulations. Experiments with simulated multiple-antenna signals and field measurement digital television signals show that the proposed weighted detection can significantly outperform the original covariance-based detection.
    Original languageEnglish
    Pages (from-to)5137-5148
    Number of pages12
    JournalIEEE Transactions on Vehicular Technology
    Issue number11
    Publication statusPublished - 10 Nov 2015


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