Joint 3D-trajectory and Resource Allocation in RISs-assisted UAV-Enabled MEC Network

This paper establishes a new multi-reconfigurable intelligence surfaces (multi-RISs) system, where multi-RISs are jointly deployed to improve the wireless communication environment in the unmanned aerial vehicle (UAV) enabled mobile edge computing (MEC) network, during which three-dimensional(3D) UAV flying scheme is considered. To optimize the total computational throughput of the system, we develop a model that concurrently addresses the allocation of time slots, the determination of on-device computation speeds, the adjustment of transmission power, the control of RISs phase shifts, and the planning of the UAV’s 3D flight trajectory. This issue represents a standard nonconvex optimization problem, and we proposed a recursive algorithm based on the block coordinate descent (BCD) and successive convex approximation (SCA) techniques to find an approximate optimal solution. Simulations have been performed and the outcomes demonstrate the superiority of the proposed methods over various reference schemes.