Abstract
Scaled Largest Eigenvalue (SLE) detector stands out as the best 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. We study the distribution of the SLE as a large number of samples are used in detection without constraint on the number of antennas. 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 as a normal random variable. Moreover, we derive the distribution of the SLE and deduce a simple yet accurate form of the probability of false alarm. Hence, this derivation yields a very simple form of the detection threshold. The analytical derivations are validated through extensive Monte Carlo simulations.
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Acknowledgment
This work was funded by a program of cooperation between the Lebanese University and the Azem & Saada social foundation (LU-AZM) and by CentraleSupélec (France).
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© 2016 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Kobeissi, H., Nasser, Y., Nafkha, A., Bazzi, O., Louët, Y. (2016). A Simple Formulation for the Distribution of the Scaled Largest Eigenvalue and Application to Spectrum Sensing. In: Noguet, D., Moessner, K., Palicot, J. (eds) Cognitive Radio Oriented Wireless Networks. CrownCom 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 172. Springer, Cham. https://doi.org/10.1007/978-3-319-40352-6_23
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DOI: https://doi.org/10.1007/978-3-319-40352-6_23
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