Joint Optimization of Caching Placement and Trajectory for UAV-D2D Networks

With the exponential growth of data traffic in wireless networks, edge caching has been regarded as a promising solution to offload data traffic and alleviate backhaul congestion, where the contents can be cached by an unmanned aerial vehicle (UAV) and user terminal (UT) with local data storage. In this article, a cooperative caching architecture of UAV and UTs with scalable video coding (SVC) is proposed, which provides the high transmission rate content delivery and personalized video viewing qualities in hotspot areas. In the proposed cache-enabling UAV-D2D networks, we formulate a joint optimization problem of UT caching placement, UAV trajectory, and UAV caching placement to maximize the cache utility. To solve this challenging mixed integer nonlinear programming problem, the optimization problem is decomposed into three sub-problems. Specifically, we obtain UT caching placement by a many-to-many swap matching algorithm, then obtain the UAV trajectory and UAV caching placement by approximate convex optimization and dynamic programming, respectively. Finally, we propose a low complexity iterative algorithm for the formulated optimization problem to improve the system capacity, fully utilize the cache space resource, and provide diverse delivery qualities for video traffic. Simulation results reveal that: i) the proposed cooperative caching architecture of UAV and UTs obtains larger cache utility than the cache-enabling UAV networks with same data storage capacity and radio resource; ii) compared with the benchmark algorithms, the proposed algorithm improves cache utility and reduces backhaul offloading ratio effectively.