Multi-UAV-Assisted Emergency Caching Networks: UAV Location and NOMA Power Optimization

In this paper, we propose an unmanned aerial vehicles (UAVs) assisted emergency caching framework based on non-orthogonal multiple access (NOMA), involving a primary UAV and several secondary UAVs. The primary UAV obtains rescue information from a remote base station (BS) and sends it to secondary UAVs hovering at designated locations to serve ground users. Specifically, a multi-objective optimization problem is formulated to maximize the number of files that can be successfully decoded in the primary UAV and minimize the number of user clusters for secondary UAVs. The multi-objective optimization problem is decomposed into three sub-problems: primary UAV deployment, power allocation, and secondary UAV deployment. First, a primary UAV deployment scheme is proposed to maximize the number of received files subject to the constraint of the demand for the line-of-sight (LoS) link probability between the primary UAV and the ground users. Subsequently, to achieve the same goal, a closed-form solution for the NOMA power allocation factor of the files is derived. Finally, due to the limited range of services of the secondary UAVs, we propose a secondary UAV deployment scheme to minimize the number of their flights, which can save energy and reduce user latency. Extensive numerical results demonstrate that the proposed algorithms outperform the random scheme and the worst scheme.