Collaborative Spectrum Sensing Based on Upper Bound on Joint PDF of Exreme Eigenvalues

Shakir, M. Z., Tang, W., Imran, M. A. and Alouini, M.-S. (2011) Collaborative Spectrum Sensing Based on Upper Bound on Joint PDF of Exreme Eigenvalues. In: 2011 19th European Signal Processing Conference, Barcelona, Spain, 29 Aug - 02 Sep 2011, pp. 1214-1218.

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Abstract

Detection based on eigenvalues of received signal covariance matrix is currently one of the most effective solution for spectrum sensing problem in cognitive radios. However, the results of these schemes often depend on asymptotic assumptions since the distribution of ratio of extreme eigenvalues is exceptionally mathematically complex to compute in practice. In this paper, a new approach to determine the distribution of ratio of the largest and the smallest eigenvalues is introduced to calculate the decision threshold and sense the spectrum. In this context, we derive a simple and analytically tractable expression for the distribution of the ratio of the largest and the smallest eigenvalues based on upper bound on the joint probability density function (PDF) of the largest and the smallest eigenvalues of the received covariance matrix. The performance analysis of proposed approach is compared with the empirical results. The decision threshold as a function of a given probability of false alarm is calculated to illustrate the effectiveness of the proposed approach.

Item Type:Conference Proceedings
Additional Information:This work was supported by Collaborative Travel Funds under KAUST Global Collaborative Research (GCR) program.
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Imran, Professor Muhammad
Authors: Shakir, M. Z., Tang, W., Imran, M. A., and Alouini, M.-S.
College/School:College of Science and Engineering > School of Engineering
ISSN:2076-1465
Copyright Holders:Copyright © 2011 EURASIP
First Published:First published in 2011 19th European Signal Processing Conference: 1214-1218
Publisher Policy:Reproduced in accordance with the publisher copyright policy

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