Publication:
Energy-Efficient Cooperative Spectrum Sensing based on Stochastic Programming in Dynamic Cognitive Radio Sensor Networks Normal

dc.affiliation.dptoUC3M. Departamento de Teoría de la Señal y Comunicacioneses
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Comunicacioneses
dc.contributor.authorKaschel, Hector
dc.contributor.authorToledo, Karel
dc.contributor.authorTorres Gómez, Jorge
dc.contributor.authorFernández-Getino García, María Julia
dc.contributor.funderMinisterio de Economía y Competitividad (España)es
dc.date.accessioned2021-05-19T10:44:14Z
dc.date.available2021-05-19T10:44:14Z
dc.date.issued2021
dc.description.abstractNowadays, Cognitive Radio Sensor Networks (CRSN) arise as an emergent technology to deal with the spectrum scarcity issue and the focus is on devising novel energy-efficient solutions. In static CRSN, where nodes have spatial fixed positions, several reported solutions are implemented via sensor selection strategies to reduce consumed energy during cooperative spectrum sensing. However, energy-efficient solutions for dynamic CRSN, where nodes are able to change their spatial positions due to their movement, are nearly reported despite today's growing applications of mobile networks. This paper investigates a novel framework to optimally predict energy consumption in cooperative spectrum sensing tasks, considering node mobility patterns suitable to model dynamic CRSN. A solution based on the Kataoka criterion is presented, that allows to minimize the consumed energy. It accurately estimates -with a given probability-the spent energy on the network, then to derive an optimal energy-efficient solution. An algorithm of reduced-complexity is also implemented to determine the total number of active nodes improving the exhaustive search method. Proper performance of the proposed strategy is illustrated by extensive simulation results for pico-cells and femto-cells in dynamic scenarios.en
dc.description.sponsorshipThis work was supported in part by the DICYT Project, Direction of Research, Development and Innovation, Universidad de Santiago de Chile, USACH, under Grant 061813KC, in part by the CONICYT-PFCHA/Doctorado Nacional/2016-21160292, and in part by the Spanish National Project TERESA-ADA (MINECO/AEI/FEDER, UE) under Grant TEC2017-90093-C3-2-R.en
dc.format.extent13
dc.identifier.bibliographicCitationKaschel, H., Toledo, K., Gomez, J. T. & Garcia, M. J. F. G. (2021). Energy-Efficient Cooperative Spectrum Sensing Based on Stochastic Programming in Dynamic Cognitive Radio Sensor Networks. IEEE Access, vol. 9, pp. 720–732.en
dc.identifier.doihttps://doi.org/10.1109/ACCESS.2020.3046466
dc.identifier.issn2169-3536
dc.identifier.publicationfirstpage720
dc.identifier.publicationlastpage732
dc.identifier.publicationtitleIEEE Accessen
dc.identifier.publicationvolume9
dc.identifier.urihttps://hdl.handle.net/10016/32681
dc.identifier.uxxiAR/0000027509
dc.language.isoeng
dc.publisherIEEE
dc.relation.projectIDGobierno de España. TEC2017-90093-C3-2-Res
dc.rights© 2020 by the author(s).en
dc.rightsAtribución 3.0 España*
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subject.ecienciaTelecomunicacioneses
dc.subject.otherDynamic CRSNen
dc.subject.otherEnergy efficiencyen
dc.subject.otherSpectrum sensingen
dc.subject.otherStochastic programmingen
dc.titleEnergy-Efficient Cooperative Spectrum Sensing based on Stochastic Programming in Dynamic Cognitive Radio Sensor Networks Normalen
dc.typeresearch article*
dc.type.hasVersionVoR*
dspace.entity.typePublication
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