Show simple item record

dc.contributor.authorJameel, Furqan
dc.contributor.authorKhan, Wali Ullah
dc.contributor.authorChang, Zheng
dc.contributor.authorRistaniemi, Tapani
dc.contributor.authorLiu, Ju
dc.date.accessioned2019-08-30T06:50:50Z
dc.date.available2019-08-30T06:50:50Z
dc.date.issued2019
dc.identifier.citationJameel, Furqan; Khan, Wali Ullah; Chang, Zheng; Ristaniemi, Tapani; Liu, Ju (2019). Secrecy analysis and learning-based optimization of cooperative NOMA SWIPT systems. In 2019 IEEE International Conference on Communications Workshops (ICC Workshops 2019), IEEE International Conference on Communications. IEEE. DOI: 10.1109/ICCW.2019.8756894
dc.identifier.otherCONVID_32505025
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/65375
dc.description.abstractNon-orthogonal multiple access (NOMA) is considered to be one of the best candidates for future networks due to its ability to serve multiple users using the same resource block. Although early studies have focused on transmission reliability and energy efficiency, recent works are considering cooperation among the nodes. The cooperative NOMA techniques allow the user with a better channel (near user) to act as a relay between the source and the user experiencing poor channel (far user). This paper considers the link security aspect of energy harvesting cooperative NOMA users. In particular, the near user applies the decode-and-forward (DF) protocol for relaying the message of the source node to the far user in the presence of an eavesdropper. Moreover, we consider that all the devices use power-splitting architecture for energy harvesting and information decoding. We derive the analytical expression of intercept probability. Next, we employ deep learning based optimization to find the optimal power allocation factor. The results show the robustness and superiority of deep learning optimization over conventional iterative search algorithm.en
dc.format.mimetypeapplication/pdf
dc.languageeng
dc.publisherIEEE
dc.relation.ispartof2019 IEEE International Conference on Communications Workshops (ICC Workshops 2019)
dc.relation.ispartofseriesIEEE International Conference on Communications
dc.rightsIn Copyright
dc.subject.otherDecode-and-forward (DF)
dc.subject.otherDeep learning
dc.subject.otherNonorthogonal multiple access (NOMA)
dc.subject.otherPower-splitting
dc.titleSecrecy analysis and learning-based optimization of cooperative NOMA SWIPT systems
dc.typeconferenceObject
dc.identifier.urnURN:NBN:fi:jyu-201908303979
dc.contributor.laitosInformaatioteknologian tiedekuntafi
dc.contributor.laitosFaculty of Information Technologyen
dc.type.urihttp://purl.org/eprint/type/ConferencePaper
dc.relation.isbn978-1-72812-373-8
dc.description.reviewstatuspeerReviewed
dc.relation.issn1550-3607
dc.type.versionacceptedVersion
dc.rights.copyright©2019 IEEE
dc.rights.accesslevelopenAccessfi
dc.relation.conferenceIEEE International Conference on Communications Workshops
dc.subject.ysooptimointi
dc.subject.ysotietoturva
dc.subject.yso5G-tekniikka
dc.subject.ysokoneoppiminen
dc.subject.ysolangaton tiedonsiirto
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p13477
jyx.subject.urihttp://www.yso.fi/onto/yso/p5479
jyx.subject.urihttp://www.yso.fi/onto/yso/p29372
jyx.subject.urihttp://www.yso.fi/onto/yso/p21846
jyx.subject.urihttp://www.yso.fi/onto/yso/p5445
dc.rights.urlhttp://rightsstatements.org/page/InC/1.0/?language=en
dc.relation.doi10.1109/ICCW.2019.8756894
jyx.fundinginformationThis work is partially supported by the National Key R & D Plan (2017YFC0803403), the National Natural Science Foundation of China (61371188) and the Fundamental Research Funds of Shandong University (2018GN051).


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record

In Copyright
Except where otherwise noted, this item's license is described as In Copyright