Generalized mean detector for collaborative spectrum sensing

Handle URI:
http://hdl.handle.net/10754/562712
Title:
Generalized mean detector for collaborative spectrum sensing
Authors:
Shakir, Muhammad Zeeshan; Rao, Anlei; Alouini, Mohamed-Slim ( 0000-0003-4827-1793 )
Abstract:
In this paper, a unified generalized eigenvalue based spectrum sensing framework referred to as Generalized mean detector (GMD) has been introduced. The generalization of the detectors namely (i) the eigenvalue ratio detector (ERD) involving the ratio of the largest and the smallest eigenvalues; (ii) the Geometric mean detector (GEMD) involving the ratio of the largest eigenvalue and the geometric mean of the eigenvalues and (iii) the Arithmetic mean detector (ARMD) involving the ratio of the largest and the arithmetic mean of the eigenvalues is explored. The foundation of the proposed unified framework is based on the calculation of exact analytical moments of the random variables of test statistics of the respective detectors. In this context, we approximate the probability density function (PDF) of the test statistics of the respective detectors by Gaussian/Gamma PDF using the moment matching method. Finally, we derive closed-form expressions to calculate the decision threshold of the eigenvalue based detectors by exchanging the derived exact moments of the random variables of test statistics with the moments of the Gaussian/Gamma distribution function. The performance of the eigenvalue based detectors is compared with the traditional detectors such as energy detector (ED) and cyclostationary detector (CSD) and validate the importance of the eigenvalue based detectors particularly over realistic wireless cognitive environments. Analytical and simulation results show that the GEMD and the ARMD yields considerable performance advantage in realistic spectrum sensing scenarios. Moreover, our results based on proposed simple and tractable approximation approaches are in perfect agreement with the empirical results. © 1972-2012 IEEE.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division; Electrical Engineering Program; Communication Theory Lab
Publisher:
Institute of Electrical and Electronics Engineers
Journal:
IEEE Transactions on Communications
Issue Date:
Apr-2013
DOI:
10.1109/TCOMM.2013.13.110594
Type:
Article
ISSN:
00906778
Appears in Collections:
Articles; Electrical Engineering Program; Communication Theory Lab; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorShakir, Muhammad Zeeshanen
dc.contributor.authorRao, Anleien
dc.contributor.authorAlouini, Mohamed-Slimen
dc.date.accessioned2015-08-03T11:02:39Zen
dc.date.available2015-08-03T11:02:39Zen
dc.date.issued2013-04en
dc.identifier.issn00906778en
dc.identifier.doi10.1109/TCOMM.2013.13.110594en
dc.identifier.urihttp://hdl.handle.net/10754/562712en
dc.description.abstractIn this paper, a unified generalized eigenvalue based spectrum sensing framework referred to as Generalized mean detector (GMD) has been introduced. The generalization of the detectors namely (i) the eigenvalue ratio detector (ERD) involving the ratio of the largest and the smallest eigenvalues; (ii) the Geometric mean detector (GEMD) involving the ratio of the largest eigenvalue and the geometric mean of the eigenvalues and (iii) the Arithmetic mean detector (ARMD) involving the ratio of the largest and the arithmetic mean of the eigenvalues is explored. The foundation of the proposed unified framework is based on the calculation of exact analytical moments of the random variables of test statistics of the respective detectors. In this context, we approximate the probability density function (PDF) of the test statistics of the respective detectors by Gaussian/Gamma PDF using the moment matching method. Finally, we derive closed-form expressions to calculate the decision threshold of the eigenvalue based detectors by exchanging the derived exact moments of the random variables of test statistics with the moments of the Gaussian/Gamma distribution function. The performance of the eigenvalue based detectors is compared with the traditional detectors such as energy detector (ED) and cyclostationary detector (CSD) and validate the importance of the eigenvalue based detectors particularly over realistic wireless cognitive environments. Analytical and simulation results show that the GEMD and the ARMD yields considerable performance advantage in realistic spectrum sensing scenarios. Moreover, our results based on proposed simple and tractable approximation approaches are in perfect agreement with the empirical results. © 1972-2012 IEEE.en
dc.publisherInstitute of Electrical and Electronics Engineersen
dc.subjectarithmetic mean detectoren
dc.subjecteigenvalue ratio detectoren
dc.subjectGaussian and gamma approximation and moment matchingen
dc.subjectgeneralized meanen
dc.subjectgeometric mean detectoren
dc.subjectSpectrum sensingen
dc.titleGeneralized mean detector for collaborative spectrum sensingen
dc.typeArticleen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.contributor.departmentElectrical Engineering Programen
dc.contributor.departmentCommunication Theory Laben
dc.identifier.journalIEEE Transactions on Communicationsen
dc.contributor.institutionDept. of Electrical and Computer Engineering, Texas A and M University at Qatar (TAMUQ), Education City, P.O. Box 23874, Doha, Qataren
dc.contributor.institutionDept. of Electrical and Computer Engineering, University of Texas, Austin, TX, United Statesen
kaust.authorAlouini, Mohamed-Slimen
All Items in KAUST are protected by copyright, with all rights reserved, unless otherwise indicated.