SDNenabled Deployment and Path Planning of Aerial Base Stations Abstract   Aerial Base Stations (ABSs) play a central role in mission critical environments due to the fast deployment, flexible reconfiguration, low cost. In this manner, through the controllable ABSs that are directed to the disaster region, users can continuously remain connected with ABSs. However, ABS deployment and path planning face several key challenges to provide ondemand communication and enable xe2x80x9dQuality of Experience (QoE)guaranteed service to the users. For example, energy consumption, maximizing the number of covered users and scheduling the ABSxe2x80x99s operations are important issues that need to be considered. Thus, this paper jointly presents a SDNenabled solution to efficiently deploy ABSs which maximizes the covered users and communication quality, and provides a path planning strategy which decreases the energy consumption. Our simulation is managed with SITL (Software In The Loop) simulator, which allows to create and test drones without a real vehicle using C compiler and we confirm the improvement in terms of connectivity and energy consumption when compared to a recent stateoftheart approach.

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.