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dc.contributor.authorZhao, Nan
dc.contributor.authorLiu, Xin
dc.contributor.authorYu, Richard F.
dc.contributor.authorChen, Yunfei
dc.contributor.authorHan, Tao
dc.contributor.authorChang, Zheng
dc.date.accessioned2020-01-22T08:34:24Z
dc.date.available2020-01-22T08:34:24Z
dc.date.issued2019
dc.identifier.citationZhao, N., Liu, X., Yu, R. F., Chen, Y., Han, T., & Chang, Z. (2019). IEEE Access Special Section Editorial : Cloud and Big Data-Based Next-Generation Cognitive Radio Networks. <i>IEEE Access</i>, <i>7</i>, 180354-180360. <a href="https://doi.org/10.1109/ACCESS.2019.2960172" target="_blank">https://doi.org/10.1109/ACCESS.2019.2960172</a>
dc.identifier.otherCONVID_34156363
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/67463
dc.description.abstractIn cognitive radio networks (CRN), secondary users (SUs) are required to detect the presence of the licensed users, known as primary users (PUs), and to find spectrum holes for opportunistic spectrum access without causing harmful interference to PUs. However, due to complicated data processing, non-real-time information exchange and limited memory, SUs often suffer from imperfect sensing and unreliable spectrum access. Cloud computing can solve this problem by allowing the data to be stored and processed in a shared environment. Furthermore, the information from a massive number of SUs allows for more comprehensive information exchanges to assist the resource allocation and interference management at the cloud center while relieving the stringent capacity demands in fronthaul links. Moreover, spectrum resources should be made available to more users, especially when the spectrum is underutilized but occupies a large band. Hence, cloud-based CRN can generate massive sensing samples that will benefit the applications of big data algorithms. The approaches to spectrum sensing and spectrum management can be greatly improved with decision-making capabilities of spectral big data.en
dc.format.mimetypeapplication/pdf
dc.languageeng
dc.language.isoeng
dc.publisherIEEE
dc.relation.ispartofseriesIEEE Access
dc.rightsCC BY 4.0
dc.titleIEEE Access Special Section Editorial : Cloud and Big Data-Based Next-Generation Cognitive Radio Networks
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-202001221408
dc.contributor.laitosInformaatioteknologian tiedekuntafi
dc.contributor.laitosFaculty of Information Technologyen
dc.contributor.oppiaineTietotekniikkafi
dc.contributor.oppiaineMathematical Information Technologyen
dc.type.urihttp://purl.org/eprint/type/JournalItem
dc.type.coarhttp://purl.org/coar/resource_type/c_0640
dc.description.reviewstatusnonPeerReviewed
dc.format.pagerange180354-180360
dc.relation.issn2169-3536
dc.relation.volume7
dc.type.versionpublishedVersion
dc.rights.copyright© The Authors, 2019
dc.rights.accesslevelopenAccessfi
dc.subject.ysokognitiivinen radio
dc.subject.ysopilvipalvelut
dc.subject.ysolangaton tiedonsiirto
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p26990
jyx.subject.urihttp://www.yso.fi/onto/yso/p24167
jyx.subject.urihttp://www.yso.fi/onto/yso/p5445
dc.rights.urlhttps://creativecommons.org/licenses/by/4.0/
dc.relation.doi10.1109/ACCESS.2019.2960172
dc.type.okmB1


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