UAVNet: Effective and Efficient UAV Network Deployment for Extending Cell Tower Coverage Nowadays we are witnessing an explosive growth of mobile data traffic, but users still often experience insufficient or unstable network bandwidth in many realistic scenarios. Unmanned aerial vehicle mounted base stations (UAVBSs) provide a novel and promising solution for serving regions with bandwidth shortfall. It is significant to investigate how to deploy UAVs for maximizing the sum throughput of a set of clients scattered in various locations in an effective and efficient way. A basic idea is to use RF ray tracing simulations as a hint to narrow down the search space of UAVs for conducting measurements. Furthermore, we study two key subproblems, chunk selection, which finds an optimal subset of chunks in the region as the search space of UAVs, and chunk search, which plans the scanning path to cover the search space with the minmax time consumption required for all UAVs. They are both proved to be NPhard, and heuristic algorithms are proposed to solve them efficiently. A prototype system, UAVNet, is implemented to conduct measurements by a UAV mounted WiFi AP communicating with 7 clients scattered in a campus, and extensive simulations are combined, reporting an obvious throughput gain with a small measurement overhead and time consumption.

EnergyEfficient UAVAssisted Communication with Spectrum optimization In traditional ground cellular systems, ground terminals (GTs) in marginal areas are often faced with performance bottlenecks due to they are too far from the macro base station (MBS). For some temporary and unexpected communication service requirements, it is uneconomical to deploy femtocell access points (FAPs) on the edge of cell. In this paper, we investigate a cellular system that utilizes a unmanned aerial vehicles (UAVs) with base station module unit as an airborne mobile base station to provide communication channel for the celledge users offloaded by the MBS. Compared with FAPs, UAV is cheaper and flexible which can provide better communication quality for the celledge GTs with better channel condition. Based on the theoretical model, we proposed plausible optimal algorithm to maximize the energyefficiency (EE) of the UAV by jointly optimizing the spectrum allocation, flying speed and user partition between the UAV and MBS. Numerical results indicate that our design could achieve relatively higher energyefficiency by exploiting optimal flight strategy and spectrum allocation strategy.