Performance Analysis and Power Allocation for Covert Mobile Edge Computing With RIS-Aided NOMA

Mobile edge computing (MEC) is a key enabling technology for the sixth-generation (6G) wireless networks. In this paper, we apply covert communications to MEC to prevent information leakage, where two candidate technologies of 6G, reconfigurable intelligent surface (RIS) and non-orthogonal multiple access (NOMA), are adopted. Specifically, a legitimate transmitter sends messages to a pair of legitimate receivers, while a warden aims to detect whether the legitimate transmission exists. We can hide the existence of the stronger-signal receiver's transmission from the warden by exploiting the nature of NOMA, and we use a jammer to further hide this existence. We first analyze the performance for the case of fixed power allocation between the legitimate transmitters and the jammer. The closed-form expressions for the minimum detection error probability and ergodic public/covert rates are derived. Then, we design a reinforcement learning (RL)-based power-allocation optimization algorithm that maximizes the sum rate while ensuring covertness, by optimizing the power allocation between the transmitters and the jammer. Simulation results validate the correctness of our analysis and demonstrate the covertness of the proposed scheme. Furthermore, the performance of the RL-based algorithm is significantly better than that of the baseline scheme, which reflects the effectiveness of our proposed algorithm.