Abstract: Aiming at the problem that it is difficult to obtain the accurate location information of the warden node Willie in practical applications, the robust energy consumption optimization algorithm for air-ground cooperation based covert mobile edge computing is presented. Specifically, under the condition that only the estimated location information of Willie is known, in order to robustly hide the computational offloading behavior between UAV and GBSs, the covertness constraints are analyzed from the perspective of the warden node Willie and the UAV, respectively. Then the weighted total energy consumption of the UAV is minimized by jointly optimizing the computation task allocation factor, the UAV-GBS association factor, the UAV power and the UAV trajectory. To tackle the formulated non-convex optimization problem, an efficient three-stage alternating iterative optimization algorithm with parameter based on block coordinate descent method, S-procedure and successive convex approximation method is proposed. Simulation results show that the proposed algorithm can save energy consumption and offload more computing tasks to the GBSs under given covert rate constraints, and has a desirable convergence.

Key words: covert mobile edge computing, air-ground cooperation, unmanned aerial vehicle, energy consumption optimization, iterative alternating optimization algorithm