Reinforcement Learning Based Latency Minimization in Secure NOMA-MEC Systems With Hybrid SIC
Creators
- 1. University of Manchester
- 2. University of Surrey
Description
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.
Files
Reinforcement_Learning_Based_Latency_Minimization_in_Secure_NOMA-MEC_Systems_With_Hybrid_SIC.pdf
Files
(1.9 MB)
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