SDN-enabled Cognitive Radio Network Architecture

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dc.authoridCICIOGLU, MURTAZA/0000-0002-5657-7402
dc.authoridCalhan, Ali/0000-0002-5798-3103
dc.authorwosidCICIOGLU, MURTAZA/AAL-5004-2020
dc.contributor.authorCicioglu, Murtaza
dc.contributor.authorCicioglu, Seda
dc.contributor.authorCalhan, Ali
dc.date.accessioned2021-12-01T18:48:48Z
dc.date.available2021-12-01T18:48:48Z
dc.date.issued2020
dc.department[Belirlenecek]en_US
dc.description.abstractIn this study, a new network architecture based on the software-defined networking (SDN) approach is proposed for cognitive radio networks (CRNs). The proposed network architecture [software-defined cognitive radio (SDCR)] assumes the responsibilities of network resource management for CRNs and provides a dynamic spectrum management mechanism with an SDN controller. In this way, the dependency of network users on base stations is reduced in dynamic cognitive radio environments, and network performance is improved by delegating some of the management responsibilities to the controller. The performance analysis of the SDCR is carried out through the RIVERBED MODELER simulation software. End-to-end delays and packet loss rates for the primary network are investigated by selecting different offered loads for secondary users. In addition, for the equal and different packet sizes, primary network and SDCR throughput are examined and network performance is improved by using channel bonding technique. The results indicate that the SDCR outperforms the traditional CRN architecture, in terms of the throughput, and the proposed architecture can provide effective performance. Bit error rate parameter is investigated in the study and the energy consumption parameter of the SDCR is also compared with the cognitive radio wireless network.en_US
dc.identifier.doi10.1049/iet-com.2019.1346
dc.identifier.endpage3160en_US
dc.identifier.issn1751-8628
dc.identifier.issn1751-8636
dc.identifier.issue18en_US
dc.identifier.scopus2-s2.0-85096358313en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage3153en_US
dc.identifier.urihttps://doi.org/10.1049/iet-com.2019.1346
dc.identifier.urihttps://hdl.handle.net/20.500.12684/10608
dc.identifier.volume14en_US
dc.identifier.wosWOS:000594371900009en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherWileyen_US
dc.relation.ispartofIet Communicationsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectcognitive radioen_US
dc.subjectsoftware radioen_US
dc.subjectradio spectrum managementen_US
dc.subjecttelecommunication network managementen_US
dc.subjecttelecommunication controlen_US
dc.subjectwireless channelsen_US
dc.subjecterror statisticsen_US
dc.subjecttelecommunication power managementen_US
dc.subjectbit error rate parameteren_US
dc.subjectchannel bonding techniqueen_US
dc.subjectnetwork architecture software-defined cognitive radio networksen_US
dc.subjectcognitive radio environmentsen_US
dc.subjectRIVERBED MODELER simulation softwareen_US
dc.subjectbase stationsen_US
dc.subjectSDN controlleren_US
dc.subjectspectrum managementen_US
dc.subjectnetwork resource managementen_US
dc.subjectsoftware-defined networking approachen_US
dc.subjectSDN-enabled cognitive radio networksen_US
dc.subjectcognitive radio wireless networken_US
dc.subjectSoftware-Defined Networkingen_US
dc.subjectWireless Networksen_US
dc.subjectVirtualizationen_US
dc.subjectManagementen_US
dc.subjectProtocolen_US
dc.subjectFutureen_US
dc.titleSDN-enabled Cognitive Radio Network Architectureen_US
dc.typeArticleen_US

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