Trade-off between Secrecy Rate and Energy Consumption in a Secure UAV- MEC System

Abstract

Unmanned aerial vehicles (UAV) used as the mobile edge computing (MEC) platform is capable of providing flexible offloading tasks, but is also facing the risk of being wiretapped by nearby eavesdroppers (Eves). In this paper, we investigate a full-duplex UAV to interfere with Eves by sending jamming signals while simultaneously processing the offloading tasks, which saves more resources overhead compared with introducing an extra jamming UAV. To trade off between the secrecy rate and energy consumption of the secure UAV-enabled MEC system, we formulate a multi-objective optimization problem aiming to maximize the average secrecy rate of the system while consuming the minimum energy of users. With the constraints of task latency requirement, the energy consumption of the legitimate UAV and the maximum capacity of self-executed tasks, the proposed multi-objective problem is also non-convex. To solve this issue, an alternating algorithm based on the successive convex approximating (SCA) method is proposed to optimize the parameters iteratively. The simulation results demonstrate that the significant performance improvement can be achieved by our proposed algorithm over the baseline schemes.