Publication:
User-centric learning for multiple access selections

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dc.contributor.authorDzulkifly S.en_US
dc.contributor.authorHashim W.en_US
dc.contributor.authorIsmail A.F.en_US
dc.contributor.authorDohler M.en_US
dc.contributor.authorid55569716800en_US
dc.contributor.authorid11440260100en_US
dc.contributor.authorid36602773900en_US
dc.contributor.authorid12791370000en_US
dc.date.accessioned2023-05-29T07:23:23Z
dc.date.available2023-05-29T07:23:23Z
dc.date.issued2019
dc.description.abstractWe are in the age where business growth is based on how user-centric your services or goods is. Current research on wireless system is more focused on ensuring that user could achieve optimal throughput with minimal delay, disregarding what user actually wants from the services. Looking from con-nectivity point of view, especially in urban areas these days, there are multiple mobile and wireless access that user could choose to get connected to. As people are looking toward machine automa-tion, we understand that the same could be done for allowing users to choose services based on their own requirement. This paper looks into unconventional, non-disruptive approach to provide mobile services based on user requirements. The first stage of this study is to look for user association from three new perspectives. The second stage involved utilizing a reinforcement learning algorithm known as q-learning, to learn from feedbacks to identify optimal decision in reaching user-centric requirement goal. The outcome from the proposed deployment has shown significant improvement in user association with learning aware solution � BEIESP.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.35940/ijeat.A2666.109119
dc.identifier.epage2344
dc.identifier.issue1
dc.identifier.scopus2-s2.0-85074573760
dc.identifier.spage2338
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85074573760&doi=10.35940%2fijeat.A2666.109119&partnerID=40&md5=66bf4d46866b33268dd147ab29cac4fc
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/24420
dc.identifier.volume9
dc.publisherBlue Eyes Intelligence Engineering and Sciences Publicationen_US
dc.relation.ispartofAll Open Access, Bronze
dc.sourceScopus
dc.sourcetitleInternational Journal of Engineering and Advanced Technology
dc.titleUser-centric learning for multiple access selectionsen_US
dc.typeArticleen_US
dspace.entity.typePublication
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