Machine Learning Algorithm for NLOS Millimeter Wave in 5G V2X Communication
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Mohan, Deepika
Ali, GG Md Nawaz
Chong, Peter Han Joo
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AIRCC Publishing Corporation
Abstract
The 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.
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4613 Theory Of Computation, 46 Information and Computing Sciences, 4006 Communications Engineering, 40 Engineering, Networking and Information Technology R&D (NITRD), Machine Learning and Artificial Intelligence
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Computer 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
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© 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.
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Except where otherwise noted, this item's license is described as © 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.