Joint Optimization of UAV Placement and Caching under Battery Constraints in UAV-aided Small-Cell Networks.

Unmanned Aerial Vehicles (UAVs), or commonly known as drones, have recently attracted the interest of the wireless communications community. Owing to their agility and fast deployment, UAVs can act as flying base stations and adjust their locations based on users mobility in order to provide higher network coverage and service. The network performance can be further improved by using cache-equipped UAVs, i.e., by combining wireless connectivity with mobile edge caching principles. In this context, this paper studies how to allocate the UAV resources in a mobile network with UAVs, and specifically, how to optimize the cache hit ratio (CHR) by selecting the placement of UAVs, the filling of their caches, and the UAV-user associations. We show that the joint UAV placement and caching problem is NP-hard, and propose an approximation algorithm with performance guarantees. In the case of UAVs with energy constraints, we propose a heuristic algorithm that takes also into account the battery levels and UAV-user association. Our evaluation shows that the proposed algorithms outperform previous approaches that consider the problems of UAV placement and caching separately, or do not consider the energy constraints.