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dc.contributor.authorSøraa, Aasmund
dc.contributor.authorWeerasinghe, Thilina Nuwan
dc.contributor.authorBalapuwaduge, Indika A. M.
dc.contributor.authorLi, Frank Yong
dc.date.accessioned2021-02-11T09:23:25Z
dc.date.available2021-02-11T09:23:25Z
dc.date.created2021-01-29T15:59:47Z
dc.date.issued2020
dc.identifier.citationSøraa, A., Weerasinghe, T. N., Balapuwaduge, I. A. M. & Li, F. Y. (2020). Preamble Transmission Prediction for mMTC Bursty Traffic : A Machine Learning based Approach. IEEE Global Communications Conference. doi:en_US
dc.identifier.isbn978-1-7281-8298-8
dc.identifier.issn2576-6813
dc.identifier.urihttps://hdl.handle.net/11250/2727327
dc.descriptionAuthor's accepted manuscript.en_US
dc.description© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
dc.language.isoengen_US
dc.publisherIEEEen_US
dc.relation.ispartof2020 IEEE Global Communications Conference (GLOBECOM)
dc.titlePreamble Transmission Prediction for mMTC Bursty Traffic : A Machine Learning based Approachen_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.description.versionacceptedVersionen_US
dc.rights.holder© 2020 IEEEen_US
dc.subject.nsiVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550en_US
dc.source.pagenumber6en_US
dc.source.journalIEEE Global Communications Conferenceen_US
dc.identifier.doi10.1109/GLOBECOM42002.2020.9322633
dc.identifier.cristin1882792
cristin.qualitycode1


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