Computation Efficiency Maximization in UAV and RIS Assisted NOMA-MEC Networks for Emergency Communications

In the emergency communication scenario, unmanned aerial vehicle (UAV)-based relaying and mobile edge computing (MEC) networks can quickly collect ground users' (GUs) information and provide high-quality computing services. In this paper, we investigate a UAV and reconfigurable intelligent surface (RIS) assisted uplink non-orthogonal multiple access MEC networks for emergency communications, where the UAV serves as a relay to assist the transmission from GUs to base station and provides MEC services. For the considered system, the computation efficiency (CE) is maximized by jointly optimizing the phase shift of RIS, communication and computation resources, bandwidth allocation coefficients, and the space location of UAV. The formulated problem is non-convex, and we divide the problem into four sub-problems. An alternating optimization-based algorithm is proposed to deal with it. In particular, with the aid of Dinkelbach's method, semi-definite relaxation, first-order Taylor expansion, successive convex approximation and improved particle swarm optimization, the decoupled non-convex sub-problems are effectively solved. Simulation results show that the proposed scheme can effectively improve the CE of the system, as compared with the conventional schemes.