Efficient Delay Minimization Algorithm for Cache-Enabled NOMA Systems

This letter adopts a proactive mechanism, namely, recommendation, to boost the performance of cache-enabled non-orthogonal multiple access (NOMA) systems from a delay minimization perspective. To this end, the impact of recommendation is first explored on the average latency of a cache-aware NOMA system, which consists of two components, namely the backhaul link delay and the content delivery delay. Consequently, the closed-form expressions regarding the latency-preserving capability of cache-assisted NOMA with recommendation are derived compared to the conventional orthogonal multiple access (OMA) strategy without recommendation. Thereafter, the associated recommendation decision making problem is optimally solved by a genetic algorithm (GA)-assisted approach. Monte Carlo simulation results validate the superiority of our proposed scheme compared to a wide range of benchmarks.