Abstract: Aiming at the problem of significant energy consumption constraints when unmanned aerial vehicle (UAV) assisted mobile edge computing (MEC) systems performed computing tasks, we constructed a system model of UAV that combined computing units and relay nodes, and used non-orthogonal multiple access (NOMA) technology to improve spectral efficiency. By meeting the task requirements of ground users, the energy efficiency of the entire system was maximized by optimizing user communication scheduling, task computation offloading, transmit power, and UAV flight trajectory. We decomposed a non-convex mixed-integer nonlinear fractional programming (MINLFP) problem that could not be directly solved into easily solvable subproblems and iteratively solved them. The fractional form of the objective function was solved by using the Dinkelbach method, which utilized successive convex approximation (SCA) to transform the original subproblems of the fractional problem into convex form. The simulation results show that the proposed method can improve the energy efficiency of the system.

Key words: unmanned aerial vehicle, mobile edge computing, resource allocation, trajectory optimization