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dc.contributor.authorShakir, Muhammad Zeeshan
dc.contributor.authorRao, Anlei
dc.contributor.authorAlouini, Mohamed-Slim
dc.date.accessioned2015-08-03T11:01:07Z
dc.date.available2015-08-03T11:01:07Z
dc.date.issued2013-03
dc.identifier.issn15361276
dc.identifier.doi10.1109/TWC.2012.011513.111486
dc.identifier.urihttp://hdl.handle.net/10754/562679
dc.description.abstractEigenvalue Ratio (ER) detector based on the two extreme eigenvalues of the received signal covariance matrix is currently one of the most effective solution for spectrum sensing. However, the analytical results of such scheme often depend on asymptotic assumptions since the distribution of the ratio of two extreme eigenvalues is exceptionally complex to compute. In this paper, a non-asymptotic spectrum sensing approach for ER detector is introduced to approximate the marginal and joint distributions of the two extreme eigenvalues. The two extreme eigenvalues are considered as dependent Gaussian random variables such that their joint probability density function (PDF) is approximated by a bivariate Gaussian distribution function for any number of cooperating secondary users and received samples. The PDF approximation approach is based on the moment matching method where we calculate the exact analytical moments of joint and marginal distributions of the two extreme eigenvalues. The decision threshold is calculated by exploiting the statistical mean and the variance of each of the two extreme eigenvalues and the correlation coefficient between them. The performance analysis of our newly proposed approximation approach is compared with the already published asymptotic Tracy-Widom approximation approach. It has been shown that our results are in perfect agreement with the simulation results for any number of secondary users and received samples. © 2002-2012 IEEE.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.subjectCopula
dc.subjectcorrelation coefficient
dc.subjecteigenvalue ratio based detection
dc.subjectnon-asymptotic Gaussian approximation
dc.subjectSpectrum sensing
dc.titleOn the decision threshold of eigenvalue ratio detector based on moments of joint and marginal distributions of extreme eigenvalues
dc.typeArticle
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentElectrical Engineering Program
dc.contributor.departmentCommunication Theory Lab
dc.identifier.journalIEEE Transactions on Wireless Communications
dc.contributor.institutionDepartment of Electrical and Computer Engineering, Texas AandM University at Qatar (TAMUQ), Education City, P.O. Box 23874, Doha, Qatar
dc.contributor.institutionDept. of Electrical and Computer Engineering, University of Texas, Austin, TX, United States
kaust.personAlouini, Mohamed-Slim


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