Collaborative spectrum sensing based on upper bound on joint PDF of extreme eigenvalues

Muhammad Shakir, Wuchen Tang, Muhammad Ali Imran, Mohamed-Slim Alouini

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.
Original languageEnglish (US)
Title of host publication2011 19th European Signal Processing Conference
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
StatePublished - 2011

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