Joint Caching and Trajectory Design for Cache-Enabled UAV in Vehicular Networks

Abstract

Cache-enabled unmanned aerial vehicles (UAVs) are envisioned as a key enabler to flexibly serve the ground traffic demand while eliminating the limited wireless backhaul links. However, how to utilize UAVs in highly dynamic vehicular networks is not well studied yet challenging with limited UAV energy and storage capacity. In this paper, considering the vehicle mobility and content requests, we study the problem of proactive content placement, trajectory design, and content delivery for cache-enabled UAV. This problem is formulated as an optimization problem aiming at maximizing the overall network throughput improvement under the UAV energy constraint, which is non-convex and difficult to solve. To tackle this problem, we propose an efficient algorithm with a two-layered structure. First, given a content placement strategy, we devise a time-based graph decomposition method to jointly optimize the content delivery and trajectory design. Next, with the optimized content delivery and trajectory, we then leverage the particle swarm optimization (PSO) algorithm to further optimize the content placement. Numerical results show that the proposed scheme can efficiently solve the joint optimization problem and adapt to the dynamic network conditions.