text: Wireless access points on Unmanned Aerial Vehicles (UAVs) are being considered for mobile service provisioning in commercial networks. These UAV access points will carry radio infrastructure and will be temporarily deployed in areas of dense user traffic to deal with excess user data demand. In this paper, we analyze the coverage when UAVs act as access points for users on the ground in an urban area. We consider the impact of several UAV placement strategies, either independent of, or responsive to, the locations of the users on the ground. Our analysis allows us to demonstrate how the density of the UAVs in the network will determine whether the UAVs should position themselves closer to user hotspots to improve the received signal strength, or further away from one another to mitigate interference. In addition, we demonstrate how network design parameters such as the UAV height above ground or the antenna beamwidth impact the coverage probability. In addition to simulations, we provide mathematical expressions for the coverage probability, for the scenario where UAVs are positioned directly above the centers of user hotspots.
  @cite_0: UAVs (Unmanned Aerial Vehicles) are candidates for serving as wireless access points in disaster or mass event scenarios. Here we elaborate on the question where to optimally place the available UAVs in space for a Poisson user distribution on the ground. Since the number of possible placement combinations is too high for a systematic search, we approach the optimal solution by a simple heuristic bio-inspired procedure. It turns out that changes in altitude contribute almost as much to increasing the average spectral efficiency as changes in horizontal directions. However, increasing the altitude requires much more energy than an equal movement in a horizontal direction. We show that restricting altitude movements by an attenuation factor can result in similar results as a procedure without such altitude restrictions. Even more intriguingly, keeping all UAVs at one favorable fixed altitude clearly outperforms the procedure with altitude flexibility. This has implications for the time UAVs can stay aloft with their on-board energy.
summary: We report an emerging trend which can be observed in the works cited above. With the notable exception of @cite_0 , existing state of the art on UAV network optimisation tends to ignore the effects of interference, instead focusing on scenarios where individual UAVs are operating in isolation. Without interference the wireless links are limited by the geometry of the environment, and therefore the network performance is generally optimised through minimising the distance between the UAV and the receiver, as this minimises the pathloss, increases the LOS probability and enables the network to reduce transmit power. These optimisation strategies may not apply to a scenario where multiple UAVs are operating concurrently and creating interference for each other. In the presence of interference, decreasing the distances between transmitters and receivers may also have the result of decreasing the distances between interferers and receivers, potentially causing a net decrease in channel performance.