Online detection and SNR estimation in cooperative spectrum sensing

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dc.contributor.author Pérez, Jesús
dc.contributor.author Vía, Javier
dc.contributor.author Vielva, Luis
dc.contributor.author Ramírez García, David
dc.date.accessioned 2022-04-19T09:11:15Z
dc.date.available 2022-04-19T09:11:15Z
dc.date.issued 2022-04-01
dc.identifier.bibliographicCitation IEEE Transactions on Wireless Communications, (2022), 21(4), pp.: 2521-2533.
dc.identifier.issn 1536-1276
dc.identifier.uri http://hdl.handle.net/10016/34567
dc.description.abstract Cooperative spectrum sensing has proved to be an effective method to improve the detection performance in cognitive radio systems. This work focuses on centralized cooperative schemes based on the soft fusion of the energy measurements at the cognitive radios (CRs). In these systems, the likelihood ratio test (LRT) is the optimal detection rule, but the sufficient statistic depends on the local signal-to-noise ratio (SNR) at the CRs, which are unknown in most practical cases. Therefore, the detection problem becomes a composite hypothesis test. The generalized LRT is the most popular approach in those cases. Unfortunately, in mobile environments, its performance is well below the LRT because the local energies are measured under varying SNRs. In this work, we present a new algorithm that jointly estimates the instantaneous SNRs and detects the presence of primary signals. Due to its adaptive nature, the algorithm is well suited for mobile scenarios where the local SNRs are time-varying. Simulation results show that its detection performance is close to the LRT in realistic conditions.
dc.description.sponsorship This work was supported in part by the Ministerio de Ciencia, Innovación y Universidades, jointly with European Commission [European Regional Development Fund (ERDF)], under Grant TEC2017-86921-C2-1-R and Grant TEC2017-86921-C2-2-R (CAIMAN) and in part by The Comunidad de Madrid under Grant Y2018/TCS-4705 (PRACTICO-CM).
dc.format.extent 12
dc.language.iso eng
dc.publisher IEEE
dc.rights © 2021 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.
dc.subject.other Cooperative spectrum sensing
dc.subject.other Energy detection
dc.subject.other Expectation-maximization (EM) algorithm
dc.subject.other Maximum likelihood
dc.subject.other Probabilistic mixture models
dc.title Online detection and SNR estimation in cooperative spectrum sensing
dc.type article
dc.description.status Publicado
dc.subject.eciencia Telecomunicaciones
dc.identifier.doi https://doi.org/10.1109/TWC.2021.3113089
dc.rights.accessRights openAccess
dc.relation.projectID Gobierno de España. TEC2017-86921-C2-2-R
dc.relation.projectID Gobierno de España.TEC2017-86921-C2-1-R/CAIMAN
dc.relation.projectID Comunidad de Madrid. Y2018/TCS-4705
dc.type.version acceptedVersion
dc.identifier.publicationfirstpage 2521
dc.identifier.publicationissue 4
dc.identifier.publicationlastpage 2533
dc.identifier.publicationtitle IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
dc.identifier.publicationvolume 21
dc.identifier.uxxi AR/0000028377
dc.contributor.funder Comunidad de Madrid
dc.contributor.funder Ministerio de Ciencia, Innovación y Universidades (España)
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