Publication:
Optimal sensing policy for energy harvesting cognitive radio systems

dc.affiliation.dptoUC3M. Departamento de Teoría de la Señal y Comunicacioneses
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Comunicacioneses
dc.contributor.authorUrquiza Villalonga, David Alejandro
dc.contributor.authorFernández-Getino García, María Julia
dc.contributor.authorTorres Gómez, Jorge
dc.contributor.funderEuropean Commissionen
dc.contributor.funderMinisterio de Economía y Competitividad (España)es
dc.date.accessioned2020-06-17T13:52:39Z
dc.date.available2020-06-17T13:52:39Z
dc.date.issued2020-03-18
dc.description.abstractEnergy harvesting (EH) emerges as a novel technology to promote green energy policies. Based on Cognitive Radio (CR) paradigm, nodes are designed to operate with harvested energy from radio frequency signals. CR-EH systems state several strategies based on sensing and access policies to maximize throughput and protect primary users from interference, simultaneously. However, reported solutions do not consider to maximize detection performance to detect spectrum holes which represent a major drawback whenever available energy is not efficiently used. In this concern, this paper addresses optimal sensing policies based on energy harvesting schemes to maximize probability of detection of available spectrum. These novel policies may be incorporated to previous reported solutions to maximize performance. Optimal processing scheduling schemes are proposed for offline and online scenarios based on convex optimization theory, Dynamic Programming (DP) algorithm and heuristic solutions (Constant Power and Greedy policies). Performance of proposed policies are validated by simulations for common detection techniques such as Matched Filter (MF), Quadrature Matched Filter (QMF) and Energy Detector (ED). As a result, it is shown that the best detection scheme theoretically addressed by MF, does not always perform better than the poorest detection scheme, given by the ED, in an energy harvesting scenario.en
dc.description.sponsorshipThis work has received funding from the European Union (EU) Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie ETN TeamUp5G, grant agreement No. 813391. Also, this work has been supported in part by the Spanish National Project TERESA-ADA, funded by (MINECO/AEI/FEDER, UE) under grant TEC2017-90093-C3-2-R.en
dc.format.extent14
dc.identifier.bibliographicCitationIEEE Transactions on Wireless Communications, 19(6) , June 2020, Pp. 3826-3838en
dc.identifier.doihttps://doi.org/10.1109/TWC.2020.2978818
dc.identifier.issn1536-1284
dc.identifier.issn1558-0687 (online)
dc.identifier.publicationfirstpage1es
dc.identifier.publicationfirstpage3826
dc.identifier.publicationissue6
dc.identifier.publicationlastpage14es
dc.identifier.publicationlastpage3838
dc.identifier.publicationtitleIEEE Transactions on Wireless Communicationsen
dc.identifier.publicationvolume19
dc.identifier.urihttps://hdl.handle.net/10016/30033
dc.identifier.uxxiAR/0000024422
dc.language.isoengen
dc.publisherIEEEen
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/813391/TeamUp5Gen
dc.relation.projectIDGobierno de España. TEC2017-90093-C3-2-Res
dc.rights© 2020 IEEE.es
dc.rights.accessRightsopen access
dc.subject.ecienciaElectrónicaes
dc.subject.ecienciaTelecomunicacioneses
dc.subject.otherEnergy harvestinges
dc.subject.otherCognitive radioes
dc.subject.otherOptimal processing schedulinges
dc.subject.otherOffline power allocation policieses
dc.subject.otherOnline power allocation policieses
dc.titleOptimal sensing policy for energy harvesting cognitive radio systemsen
dc.typeresearch article*
dc.type.hasVersionAM*
dspace.entity.typePublication
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