A Machine Learning Approach to Enhance the Performance of D2D-Enabled Clustered Networks

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dc.citation.volume9
dc.contributor.authorAslam S
dc.contributor.authorAlam F
dc.contributor.authorHasan SF
dc.contributor.authorRashid MA
dc.date.available2021
dc.date.issued20/01/2021
dc.description.abstractClustering has been suggested as an effective technique to enhance the performance of multicasting networks. Typically, a cluster head is selected to broadcast the cached content to its cluster members utilizing Device-to-Device (D2D) communication. However, some users can attain better performance by being connected with the Evolved Node B (eNB) rather than being in the clusters. In this article, we apply machine learning algorithms, namely Support Vector Machine, Random Forest, and Deep Neural Network to identify the users that should be serviced by the eNB. We therefore propose a mixed-mode content distribution scheme where the cluster heads and eNB service the two segregated groups of users to improve the performance of existing clustering schemes. A D2D-enabled multicasting scenario has been set up to perform a comprehensive simulation study that demonstrates that by utilizing the mixed-mode scheme, the performance of individual users, as well as the whole network, improve significantly in terms of throughput, energy consumption, and fairness. This study also demonstrates the trade-off between eNB loading and performance improvement for various parameters.
dc.description.publication-statusPublished
dc.format.extent16114 - 16132
dc.identifierhttp://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000613539600001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=c5bb3b2499afac691c2e3c1a83ef6fef
dc.identifier.citationIEEE ACCESS, 2021, 9 pp. 16114 - 16132
dc.identifier.doi10.1109/ACCESS.2021.3053045
dc.identifier.elements-id438131
dc.identifier.harvestedMassey_Dark
dc.identifier.issn2169-3536
dc.identifier.urihttps://hdl.handle.net/10179/16015
dc.publisherIEEE
dc.relation.isPartOfIEEE ACCESS
dc.relation.urihttps://ieeexplore.ieee.org/document/9328769
dc.subjectClustering algorithm
dc.subjectcontent multicasting
dc.subjectD2D enabled networks
dc.subjectdeep neural networks
dc.subjecteNB loading
dc.subjectmachine learning
dc.subjectrandom forest
dc.subjectsupport vector machine
dc.subjectuser segregation
dc.subject.anzsrc08 Information and Computing Sciences
dc.subject.anzsrc09 Engineering
dc.subject.anzsrc10 Technology
dc.titleA Machine Learning Approach to Enhance the Performance of D2D-Enabled Clustered Networks
dc.typeJournal article
pubs.notesNot known
pubs.organisational-group/Massey University
pubs.organisational-group/Massey University/College of Sciences
pubs.organisational-group/Massey University/College of Sciences/School of Food and Advanced Technology
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