This letter studies the optimization of a UAV-aided vehicular communication system where a rotary-wing UAV serves a moving vehicle. Considering the propulsion energy of the UAV, our goal is to maximize the energy efficiency (EE) of the system by optimizing UAV trajectory. Due to the causality of the vehicle location information (VLI), the formulated optimization problem is challenging to solve. To address the VLI causality issue, a vehicle's trajectory prediction framework is proposed, in which a short-term accurate trajectory prediction model and a long-term coarse trajectory prediction model are integrated. Based on the proposed vehicle's trajectory prediction framework, a novel receding horizon optimization method is proposed to transform the EE maximization problem into a sequence of optimization problems, in which a time window of the short-term vehicle's trajectory prediction is successively moved along the vehicle's trip. By solving the sequence of optimization problems, an energy-efficient UAV's trajectory optimization algorithm is obtained. Simulation results verify that our proposed scheme can achieve about 20%-40% EE performance gains over existing baseline schemes.

中文翻译：

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具有车辆轨迹预测的无人机辅助车辆通信设计


这封信研究了无人机辅助车辆通信系统的优化，其中旋翼无人机为移动车辆提供服务。考虑到无人机的推进能量，我们的目标是通过优化无人机轨迹来最大化系统的能量效率（EE）。由于车辆位置信息（VLI）的因果关系，所提出的优化问题很难解决。为了解决VLI因果关系问题，提出了一种车辆轨迹预测框架，其中集成了短期精确轨迹预测模型和长期粗略轨迹预测模型。基于所提出的车辆轨迹预测框架，提出了一种新颖的后退视野优化方法，将EE最大化问题转化为一系列优化问题，其中短期车辆轨迹预测的时间窗口沿着车辆的行程连续移动。通过求解该序列优化问题，得到节能无人机轨迹优化算法。仿真结果验证了我们提出的方案可以比现有基准方案实现约 20%-40% 的 EE 性能增益。