Sum Rate Maximization via Reconfigurable Intelligent Surface in UAV Communication: Phase Shift and Trajectory Optimization

Facing the fast-growing application demands in future wireless communication networks, unmanned aerial vehicles (UAVs) have emerged to provide users with highly cost-effective deployment and flexible access services. Due to the complex communication environment, the line-of-sight transmissions of aerial-ground networks are probably blocked, which seriously affects the communication quality. Reconfigurable intelligent surface (RIS) is known as a promising solution to improve the wireless environment through reconfigurable passive units. Motivated by this, we explore a novel RIS-assisted aerial-ground communication scenario, investigating the UAV trajectory design and RIS's phase shift optimization problem aiming at maximizing the sum rate. Considering that the problem is non-convex, we develop an alternating optimization method that decomposes our formulated problem into two blocks when another variable is fixed. With the given optimal phase shifts, the trajectory design subproblem is well solved by resorting to the successive convex approximation method. The experimental results show the remarkable performance of our proposed scheme compared with other schemes.