Reinforcement Learning Based Latency Minimization in Secure NOMA-MEC Systems With Hybrid SIC

physical layer security (PLS) in a non-orthogonal multiple access (NOMA)-based mobile edge computing (MEC) system is investigated, where hybrid successive interference cancellation (SIC) decoding is considered.

This work is extended to a multi-user scenario, in which a matching-based algorithm is proposed to solve the formulated sub-channel assignment problem. Simulation results indicate that: i) the proposed solution can significantly reduce the latency and provide dynamic strategy selection for various scenarios; ii) the NOMA offloading strategy with hybrid SIC decoding can outperform other strategies in the considered system.