Year: 2020
Type: article
Abstract: In vehicular networks of the future, sensing and communication functionalities will be intertwined. In this article, we investigate a radar-assisted predictive beamforming design for vehicle-to-infrastructure (V2I) communication by exploiting the dual-functional radar-communication (DFRC) technique. Aiming for realizing joint sensing and communication functionalities at road side units (RSUs), we present a novel extended Kalman filtering (EKF) framework to track and predict kinematic parameters of each vehicle. By exploiting the radar functionality of the RSU we show that the communication beam tracking overheads can be drastically reduced. To improve the sensing accuracy while guaranteeing the downlink communication sum-rate, we further propose a power allocation scheme for multiple vehicles. Numerical results have shown that the proposed DFRC based beam tracking approach significantly outperforms the communication-only feedback based technique in the tracking performance. Furthermore, the designed power allocation method is able to achieve a favorable performance trade-off between sensing and communication.
Institutions: University College London, UNSW Sydney
Language: English
Subfield: Aerospace Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
Awards: Exploiting interference for physical layer security in 5G networks [CI-PHY] (EPSRC-FNR), Millimetre wave communications for mobile broadband systems, Combining MIMO Radar with MU-MIMO Communications: More than Coexistence (ComRad), Learning to Communicate: Deep Learning based solutions for the Physical Layer of Machine Type Communications [LeanCom]
OpenAlex ID: W3072033075