Approximating the standard condition number for cognitive radio spectrum sensing with finite number of sensors

dc.contributor.authorKobeissi, Hussein
dc.contributor.authorNafkha, Amor
dc.contributor.authorNasser, Youssef
dc.contributor.authorLouët, Yvës
dc.contributor.authorBazzi, Oussama
dc.contributor.departmentDepartment of Electrical and Computer Engineering
dc.contributor.facultyMaroun Semaan Faculty of Engineering and Architecture (MSFEA)
dc.contributor.institutionAmerican University of Beirut
dc.date.accessioned2025-01-24T11:29:25Z
dc.date.available2025-01-24T11:29:25Z
dc.date.issued2017
dc.description.abstractIn this study, the authors consider the standard condition number (SCN) detector for a cognitive radio with finite number of cooperative sensors. They derive an exact nested form of the distribution of the SCN for the central uncorrelated, non-central uncorrelated and central semi-correlated Wishart matrices under ℋ0 and ℋ1 hypotheses. Due to the complexity of these expressions, the authors approximate the distribution of the SCN by the generalised extreme value distribution using moment matching. They derive the exact form of the pth moment of the SCN for these cases. Consequently, the performance probabilities are approximated and a simple decision threshold formula is provided. In addition, a similar approximation for the detection probability is provided using non-central/central approximation. They show that the proposed analytical approximations provide high accuracy using Monte-Carlo simulations. © The Institution of Engineering and Technology.
dc.identifier.doihttps://doi.org/10.1049/iet-spr.2016.0146
dc.identifier.eid2-s2.0-85016470593
dc.identifier.urihttp://hdl.handle.net/10938/27214
dc.language.isoen
dc.publisherInstitution of Engineering and Technology
dc.relation.ispartofIET Signal Processing
dc.sourceScopus
dc.subjectIntelligent systems
dc.subjectMonte carlo methods
dc.subjectNumber theory
dc.subjectRadio systems
dc.subjectAnalytical approximation
dc.subjectDecision threshold
dc.subjectDetection probabilities
dc.subjectGeneralised extreme value distributions
dc.subjectMoment-matching
dc.subjectSemi-correlated
dc.subjectStandard condition numbers
dc.subjectWishart matrices
dc.subjectCognitive radio
dc.titleApproximating the standard condition number for cognitive radio spectrum sensing with finite number of sensors
dc.typeArticle

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