Sensing Assisted Predictive Beamforming for V2I Networks: Tracking on the Complicated Road: (Invited Paper)

In this paper, we propose a sensing-assisted beam-forming design for integrated sensing and communication (ISAC) system in a vehicle-to-infrastructure (V2I) network, where a road side unit (RSU) provides localization and communication services to the vehicles on an arbitrarily shaped road. In our proposed scheme, the position and motion of the vehicles are decomposed into longitudinal and lateral directions to simplify the kinematic functions. We establish a curvilinear coordinate system based on the road geometry and employ an extended Kalman filter (EKF) to accurately estimate and predict the state of the vehicles. By employing such prediction, we construct a beamformer directing to the vehicles to acquire high array gain and corresponding high quality of service. Numerical results validate the feasibility of tracking and predicting the state of the vehicles by applying a curvilinear coordinate system. The superiority of the proposed algorithm in both communication and tracking metrics is also verified.