Content Fetching Delay Optimization-Based Caching and Resource Allocation for UAV-Enabled Networks

Abstract

In this work, we investigate content caching problem in unmanned aerial vehicle (UAV)enabled networks where UAVs are allowed to store user requested content so as to enhance the content transmission performance of users. To predict user content request, we propose a bidirectional long shortterm memory-based algorithm. Then, the content transmission delay of users is examined and the UAV deployment, content caching and resource allocation problem is formulated as an overall content fetching delay minimization problem. As the formulated problem is difficult to solve, we transform it into two subproblems which are solved iteratively. To tackle the UAV deployment and content caching subproblem, we first design a modified K-means-based clustering scheme and then propose a UAV deployment strategy by using quadratic transformation. To solve subcarrier and power allocation subproblem, we apply Lagrangian dual method to determine power allocation strategy and propose a Kuhn-Munkres algorithm-based subcarrier allocation strategy. Simulation results show that our approach achieves approximately 11.1% lower overall content fetching delay compared to the existing algorithm.INDEX TERMS Unmanned aerial vehicles, user clustering, UAV deployment, content caching, resource allocation.