Latency Minimization for RSMA-Assisted Wireless Caching Networks With Dynamic Recommendation

In this work, our aim is to minimize the average latency of a dynamic recommendation-aware wireless caching system with the utilization of rate splitting multiple access (RSMA). To this end, we first investigate the content request probability per user, which is affected by dynamic recommendation. Then, we analyze how the RSMA-oriented resource allocation influences on the system latency. These analyses enable us to formulate the average latency minimization problem from a joint content caching, dynamic recommendation, and RSMA resource allocation perspective, which is a non-linear, non-convex, and mixed-integer programming problem. To make it tractable, we decompose the original problem into three subproblems, namely, the short-term resource allocation problem for RSMA, the long-term caching optimization problem, and the dynamic recommendation optimization problem. After solving all the subproblems separately, we devise an alternating algorithm to jointly optimize the variables. Extensive simulation results show the convergence performance of our developed scheme and the superiority of our algorithm with respect to system's average latency and cache hit ratio when compared to the benchmark strategies.