基于QoE的无人机网络部署和缓存策略优化方法.

In order to maximize the quality of experience ( QoE) of users, this paper designed a cellular network model using cache-enabled unmanned aerial vehicle ( UA V) for assisted communication. This model used a combination of U AV communication and edge caching to offload traffic, aiming to maximize QoE by jointly optimizing UAV deployment, cache placement and user association, and this paper used mean opinion score (MOS) to evaluate QoE. Based on the problem definition, this paper proposed a joint optimization algorithm for UAV deployment, cache placement and user association to maximize the MOS. This algorithm used K-means algorithm to create clusters for users to deploy UAV based on user locations, used penalty function-based convex optimization algorithm to obtain a cache placement strategy and greedy algorithm to obtain an association strategy for users. Several simulation experiments verify the effectiveness and feasibility of the proposed algorithm. The experimental results show that the proposed joint optimization algorithm has better performance in terms of MOS, backhaul traffic offloading and content access delay compared with the three benchmark algorithms. [ABSTRACT FROM AUTHOR]