Optimizing mmWave Beamforming for High-Speed Connected Autonomous Vehicles: An Adaptive Approach

Ryo Iwaki, Jin Nakazato, Asad Muhammad, Ehsan Javanmardi, Kazuki Maruta, Manabu Tsukada, Hideya Ochiai, Hiroshi Esaki

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Citations (Scopus)

Abstract

The commercialization of 5G has been initiated for a while. Furthermore, millimeter wave (mmWave) has been introduced to small cells with small coverage due to its strong linearity and non-winding characteristics. On the other hand, in connected autonomous vehicles (CAV s), where various traffic systems can cooperatively perform recognition, decision-making, and execution, communication is assumed to be always connected. Therefore, to use low latency mm Wave for high-speed moving CAV, existing beamforming cannot follow them at high speed. This paper proposes an improved beam tracking algorithm for high-speed CAVs, which can be evaluated in a more general environment using a traffic simulator. We proposed an adaptive algorithm for a general road environment by increasing the number of beam searches and search dimensions.

Original languageEnglish
Title of host publication2024 IEEE 21st Consumer Communications and Networking Conference, CCNC 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1088-1089
Number of pages2
ISBN (Electronic)9798350304572
DOIs
Publication statusPublished - 2024
Event21st IEEE Consumer Communications and Networking Conference, CCNC 2024 - Las Vegas, United States
Duration: 6 Jan 20249 Jan 2024

Publication series

NameProceedings - IEEE Consumer Communications and Networking Conference, CCNC
ISSN (Print)2331-9860

Conference

Conference21st IEEE Consumer Communications and Networking Conference, CCNC 2024
Country/TerritoryUnited States
CityLas Vegas
Period6/01/249/01/24

Keywords

  • Connected autonomous vehicle
  • Fast beam tracking
  • Millimeter wave
  • V2X

Fingerprint

Dive into the research topics of 'Optimizing mmWave Beamforming for High-Speed Connected Autonomous Vehicles: An Adaptive Approach'. Together they form a unique fingerprint.

Cite this