With the explosive growth of mobile data traffic in wireless networks, cache-enabled unmanned aerial vehicles(UAVs) are being used in mobile computing to serve as edge servers to provide on-demand services to users in the network. To bring better quality of experience to users while satisfying other resource constraints, it jointly optimized UAVs deployment, cache placement and user association to minimize content access latency for all users and provided users with content caching services of varying quality. This paper proposed a joint optimization algorithm based on alternating optimization for the scenario where multiple UAVs and ground base stations collaborate to provide caching services. The algorithm achieved a sub-optimal solution with a convergence guarantee by iteratively solving the three sub-problems obtained from the decomposition of the objective problem. Firstly, a successive convex approximation-based algorithm solved the UAV deployment sub-problem. Secondly, it used a greedy-based algorithm to solve the content caching sub-problem. Then it used a successive convex approximation algorithm based on the penalty function to solve the user access sub-problem. Finally, it repeated the above procedure to obtain a sub-optimal solution to the target problem. Several simulation experiments verified the effectiveness and feasibility of the proposed algorithm. The simulation results show that the proposed joint optimization algorithm performs better regarding average content access latency and cache hit ratio than the benchmark algorithm.

[2023-11-02] Accepted Paper /doc/2023.08.0361/v1

[2024-04-05] Printed Article /doc/2023.08.0361/v2