论文标题
雷达辅助的预测范围用于车辆到基础结构链接
Radar-assisted Predictive Beamforming for Vehicle-to-Infrastructure Links
论文作者
论文摘要
在本文中，我们通过依靠路边单元（RSUS）的关节感应和通信功能来提出针对车辆到基础结构（V2I）通信的雷达辅助预测波束形成设计。我们提出了一个新颖的扩展卡尔曼滤波（EKF）框架，以跟踪和预测车辆的运动学参数。通过利用RSU的雷达功能，我们表明可以大大降低通信光束跟踪开销。数值结果表明，所提出的雷达辅助方法在角度跟踪和下行链路通信中都显着超过了基于通信的基于通信的反馈技术。
In this paper, we propose a radar-assisted predictive beamforming design for vehicle-to-infrastructure (V2I) communication by relying on the 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 the vehicle. By exploiting the radar functionality of the RSU we show that the communication beam tracking overheads can be drastically reduced. Numerical results have demonstrated that the proposed radar-assisted approach significantly outperforms the communication-only feedback based technique in both the angle tracking and the downlink communication.
