Optimization strategy of UAV‐ARIS assisted vehicular communication system

In recent years, the Integrated Satellite Aerial Terrestrial (I‐SAT) network has garnered significant attention as an innovative and integrated communication system. However, it still encounters interference in the face of the complex external environment. In this context, reconfigurable intelligent surface (RIS) provides a key way of solving this problem and effectively improves the performance and stability of the I‐SAT network. This article considers the combination of unmanned aerial vehicle (UAV) and RIS and proposes a novel architecture for sub‐connected active RIS (ARIS) under the energy consumption constraints of UAV and ARIS. The authors first provide a UAV‐ARIS based position prediction strategy for the vehicle. Then, a joint RIS phase shift, amplification and UAV trail optimization algorithm is proposed to pursue a high achievable rate. The interference between each link and the total energy consumption are all taken into consideration. In addition, a deep deterministic policy gradient (DDPG) algorithm is utilized for the optimization problem, and achieves convergence in continuous action space. Finally, the simulation results affirm the precision of the proposed method in significantly enhancing performance compared to other schemes. This paper considers the combination of unmanned aerial vehicle (UAV) and reconfigurable intelligent surface (RIS) and proposes a novel architecture for sub‐connected active RIS under the energy consumption constraints of UAV and active RIS. We provide an UAV‐ARIS based position prediction strategy for the vehicle and propose a joint RIS phase shift, amplification and UAV trail optimization algorithm to pursue a high achievable rate. In addition, a Deep Deterministic Policy Gradient (DDPG) algorithm is utilized for the optimization problem, and achieves convergence in continuous action space.