cogcom 17(10): e5

Research Article

On the Performance Analysis and Evaluation of Scaled Largest Eigenvalue in Spectrum Sensing: A Simple Form Approach

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  • @ARTICLE{10.4108/eai.23-2-2017.152193,
        author={Hussein Kobeissi and Amor Nafkha and Youssef Nasser and Oussama Bazzi and Yves Lou\`{\i}t},
        title={On the Performance Analysis and Evaluation of Scaled Largest Eigenvalue in Spectrum Sensing: A Simple Form Approach},
        journal={EAI Endorsed Transactions on Cognitive Communications},
        volume={3},
        number={10},
        publisher={EAI},
        journal_a={COGCOM},
        year={2017},
        month={2},
        keywords={Scaled largest eigenvalue detector, Spectrum sensing, Wishart matrix},
        doi={10.4108/eai.23-2-2017.152193}
    }
    
  • Hussein Kobeissi
    Amor Nafkha
    Youssef Nasser
    Oussama Bazzi
    Yves Louët
    Year: 2017
    On the Performance Analysis and Evaluation of Scaled Largest Eigenvalue in Spectrum Sensing: A Simple Form Approach
    COGCOM
    EAI
    DOI: 10.4108/eai.23-2-2017.152193
Hussein Kobeissi1,*, Amor Nafkha2, Youssef Nasser3, Oussama Bazzi4, Yves Louët2
  • 1: SCEE/IETR, CentraleSupélec - Campus de Rennes, Rennes, France. Department of Physics and Electronics, Faculty of Science 1, Lebanese University, Beirut, Lebanon.
  • 2: SCEE/IETR, CentraleSupélec - Campus de Rennes, Rennes, France.
  • 3: ECE Department, AUB, Bliss Street, Beirut, Lebanon.
  • 4: Department of Physics and Electronics, Faculty of Science 1, Lebanese University, Beirut, Lebanon.
*Contact email: hussein.kobeissi.87@gmail.com

Abstract

Scaled Largest Eigenvalue (SLE) detector stands out as the optimal single-primary-user detector in uncertain noisy environments. In this paper, we consider a multi-antenna cognitive radio system in which we aim at detecting the presence/absence of a Primary User (PU) using the SLE detector. By the exploitation of the distributions of the largest eigenvalue and the trace of the receiver sample covariance matrix, we show that the SLE could be modeled using the standard Gaussian function. Moreover, we derive the distribution of the SLE and deduce a simple yet accurate form of the probability of false alarm and the probability of detection. Hence, this derivation yields a very simple form of the detection threshold. Correlation coeÿcient between the largest eigenvalue and the trace is also considered as we derive a simple analytical expression. These analytical derivations are validated through extensive Monte Carlo simulations