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.
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.
@cite_0
2340982237
Modern day wireless networks have tremendously evolved driven by a sharp increase in user demands, continuously requesting more data and services. This puts significant strain on infrastructure-based macro cellular networks due to the inefficiency in handling these traffic demands, cost effectively. A viable solution is the use of unmanned aerial vehicles (UAVs) as intermediate aerial nodes between the macro and small cell tiers for improving coverage and boosting capacity. This letter investigates the problem of user-demand-based UAV assignment over geographical areas subject to high traffic demands. A neural-based cost function approach is formulated, in which UAVs are matched to a particular geographical area. It is shown that leveraging multiple UAVs not only provides long-range connectivity but also better load balancing and traffic offload. Simulation study demonstrates that the proposed approach yields significant improvements in terms of fifth percentile spectral efficiency up to 38 and reduced delays up to 37.5 compared with a ground-based network baseline without UAVs.