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Machine Learning Algorithm for NLOS Millimeter Wave in 5G V2X Communication

aut.relation.conference8th International Conference on Computational Science and Engineering (CSE 2020)
aut.relation.endpage76
aut.relation.issue17
aut.relation.startpage63
aut.relation.volume10
dc.contributor.authorMohan, Deepika
dc.contributor.authorAli, GG Md Nawaz
dc.contributor.authorChong, Peter Han Joo
dc.contributor.editorMeghanathan, Natarajan
dc.contributor.editorNagamalai, Dhinaharan
dc.date.accessioned2026-05-20T02:21:19Z
dc.date.available2026-05-20T02:21:19Z
dc.date.issued2020-12-13
dc.description.abstractThe 5G vehicle-to-everything (V2X) communication for autonomous and semi-autonomous driving utilizes the wireless technology for communication and the Millimeter Wave bands are widely implemented in this kind of vehicular network application. The main purpose of this paper is to broadcast the messages from the mmWave Base Station to vehicles at LOS (Line-ofsight) and NLOS (Non-LOS). Relay using Machine Learning (RML) algorithm is formulated to train the mmBS for identifying the blockages within its coverage area and broadcast the messages to the vehicles at NLOS using a LOS nodes as a relay. The transmission of information is faster with higher throughput and it covers a wider bandwidth which is reused, therefore when performing machine learning within the coverage area of mmBS most of the vehicles in NLOS can be benefited. A unique method of relay mechanism combined with machine learning is proposed to communicate with mobile nodes at NLOS.
dc.identifier.citationComputer Science & Information Technology. Proceedings of the 8th International Conference on Computational Science and Engineering (CSE 2020), December 12 ~ 13, 2020, Dubai, UAE. 10(17), 2020. Volume Editors : Natarajan Meghanathan, Dhinaharan Nagamalai. ISBN : 978-1-925953-31-2
dc.identifier.doi10.5121/csit.2020.101706
dc.identifier.isbn9781925953312
dc.identifier.urihttp://hdl.handle.net/10292/21140
dc.publisherAIRCC Publishing Corporation
dc.relation.urihttps://aircconline.com/csit/abstract/v10n17/csit101706.html
dc.rights© 2020 By AIRCC Publishing Corporation. This article is published under the Creative Commons Attribution (CC BY) license. Computer Science & Information Technology (CS & IT) is an open access peer reviewed Computer Science Conference Proceedings (CSCP) series that welcomes conferences to publish their proceedings / post conference proceedings.
dc.rights.accessrightsOpenAccess
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subject4613 Theory Of Computation
dc.subject46 Information and Computing Sciences
dc.subject4006 Communications Engineering
dc.subject40 Engineering
dc.subjectNetworking and Information Technology R&D (NITRD)
dc.subjectMachine Learning and Artificial Intelligence
dc.titleMachine Learning Algorithm for NLOS Millimeter Wave in 5G V2X Communication
dc.typeConference Contribution
pubs.elements-id757891

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