Cognitive Radio Oriented Wireless Networks. 10th International Conference, CROWNCOM 2015, Doha, Qatar, April 21–23, 2015, Revised Selected Papers

Research Article

Detection of Temporally Correlated Primary User Signal with Multiple Antennas

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  • @INPROCEEDINGS{10.1007/978-3-319-24540-9_6,
        author={Hadi Hashemi and Sina Fard and Abbas Taherpour and Saeid Sedighi and Tamer Khattab},
        title={Detection of Temporally Correlated Primary User Signal with Multiple Antennas},
        proceedings={Cognitive Radio Oriented Wireless Networks. 10th International Conference, CROWNCOM 2015, Doha, Qatar, April 21--23, 2015, Revised Selected Papers},
        proceedings_a={CROWNCOM},
        year={2015},
        month={10},
        keywords={},
        doi={10.1007/978-3-319-24540-9_6}
    }
    
  • Hadi Hashemi
    Sina Fard
    Abbas Taherpour
    Saeid Sedighi
    Tamer Khattab
    Year: 2015
    Detection of Temporally Correlated Primary User Signal with Multiple Antennas
    CROWNCOM
    Springer
    DOI: 10.1007/978-3-319-24540-9_6
Hadi Hashemi1, Sina Fard1, Abbas Taherpour1, Saeid Sedighi1, Tamer Khattab2,*
  • 1: Imam Khomeini International University
  • 2: Qatar University
*Contact email: tkhattab@ieee.org

Abstract

In this paper, we address the problem of multiple antenna spectrum sensing in cognitive radios (CRs) when the samples of the primary user (PU) signal as well as samples of noise are assumed to be temporally correlated. We model and formulate this multiple antenna spectrum sensing problem as a hypothesis testing problem. First, we derive the optimum Neyman-Pearson (NP) detector for the scenario in which the channel gains, the PU signal and noise correlation matrices are assumed to be known. Then, we derive the sub-optimum generalized likelihood ratio test (GLRT)-based detector for the case when the channel gains and aforementioned matrices are assumed to be unknown. Approximate analytical expressions for the false-alarm probabilities of the proposed detectors are given. Simulation results show that the proposed detectors outperform some recently-purposed algorithms for multiple antenna spectrum sensing.