Contextual Multi-Armed Bandit based Beam Allocation in mmWave V2X Communication under Blockage

Abdulkadir Kose, Haeyoung Lee, Chuan Heng Foh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Due to its low latency and high data rates support, mmWave communication has been an important player for vehicular communication. However, this carries some disadvantages such as lower transmission distances and inability to transmit through obstacles. This work presents a Contextual Multi-Armed Bandit Algorithm based beam selection to improve connection stability in next generation communications for vehicular networks. The algorithm, through machine learning (ML), learns about the mobility contexts of the vehicles (location and route) and helps the base station make decisions on which of its beam sectors will provide connection to a vehicle. In addition, the proposed algorithm also smartly extends, via relay vehicles, beam coverage to outage vehicles which are either in NLOS condition due to blockages or not served any available beam. Through a set of experiments on the city map, the effectiveness of the algorithm is demonstrated, and the best possible solution is presented.
Original languageEnglish
Title of host publication2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring) - Proceedings
Place of PublicationUSA
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages6
ISBN (Electronic)9798350311143
Publication statusPublished - 14 Aug 2023
Event2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring) - Florence, Italy
Duration: 20 Jun 202323 Jun 2023
Conference number: 97

Publication series

NameIEEE Vehicular Technology Conference
ISSN (Print)1550-2252
ISSN (Electronic)2577-2465


Conference2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring)
Abbreviated titleVTC2023
Internet address


  • V2X
  • beam allocation
  • mmWave networks


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