Sensing-Assisted Multi-Beam Control for Dense Connected Automated Vehicles: A Clustering Approach

Qianyi Hao1; Qixun Zhang1; Yanpeng Cui1; Fan Liu2; Kan Yu3; Dingyou Ma1

10.1109/WCNC57260.2024.10570886

2024-04-24

1525-3511

979-8-3503-0359-9

2024 IEEE Wireless Communications and Networking Conference (WCNC)

21-24 April 2024

Dubai, United Arab Emirates

The emergence of connected autonomous vehicles (CAVs) has transformed the realms of transportation and communications. Meeting the demands of future CAVs networks requires the seamless integration of two essential functions: communications and sensing. However, in dense CAVs scenarios, meeting the demands for one-to-one beam-CAV services become challenging due to limited spatial freedom and severe beams interference. In this paper, a novel sensing-assisted CAV s clustering and beams alignment method is proposed. Based on the echo signal, the kinematic parameters are measured, and the extended Kalman filter (EKF) is designed for angle tracking. On this basis, a CAV s clustering method is also proposed. Simulation results verify superior tracking performance compared to other methods. The root mean square error (RMSE) is less than 0.03 and the sum rates can be improved by up to 4 times.

其他

EI

1.The Key Laboratory of Universal Wireless Communications, Ministry of Education, School of Information and Communication Engineeringm, Beijing University of Posts and Telecommunications, Beijing, China
2.The Department of Electronic and Electrical Engineering, Southern University of Science and Technology, Shenzhen, China
3.The Faculty of Information Technology, Macau University of Science and Technology, Taipa, Macau, China

Qianyi Hao,Qixun Zhang,Yanpeng Cui,et al. Sensing-Assisted Multi-Beam Control for Dense Connected Automated Vehicles: A Clustering Approach[C],2024.