Backhaul for Low-Altitude UAVs in Urban Environments

Abstract

Unmanned Aerial Vehicles (UAVs) acting as access points in cellular networks require wireless backhauls to the core network. In this paper we employ stochastic geometry to carry out an analysis of the UAV backhaul performance that can be achieved with a network of dedicated ground stations. We provide analytical expressions for the probability of successfully establishing a backhaul and the expected data rate over the backhaul link, given either an LTE or a millimeterwave backhaul. We demonstrate that increasing the density of the ground station network gives diminishing returns on the performance of the UAV backhaul, and that for an LTE backhaul the ground stations can benefit from being colocated with an existing base station network.

Analytical Channel Models for Millimeter Wave UAV Networks Under Hovering Fluctuations

“…However, the proposed channel models in [25]- [27] are only applicable for a link between users and a perfectly stable UAV. In [28], the authors use stochastic geometry to study directional UAVbased mmWave backhaul links operating at 73 GHz and then, compare their performance with an LTE backhaul operating at 2 GHz. For simplicity, in [28], the antenna pattern is approximated by a rectangular radiation pattern.…”

“…In [28], the authors use stochastic geometry to study directional UAVbased mmWave backhaul links operating at 73 GHz and then, compare their performance with an LTE backhaul operating at 2 GHz. For simplicity, in [28], the antenna pattern is approximated by a rectangular radiation pattern. In [29], the authors propose a flexible UAV-assisted backhaul link that takes into account the dynamic blockage of mmWave links.…”

“…In [29], the authors propose a flexible UAV-assisted backhaul link that takes into account the dynamic blockage of mmWave links. However, the works in [28], [29] ignore the random fluctuations of UAVs and assume a perfect beam alignment between transceivers. Obviously, because of the random fluctuations as well as strict payload limitations for employing antenna stabilizers, careful alignment is not practically feasible in aerial links (particularly, for small multi-rotor UAVs) which leads to an unreliable communication system due to antenna gain mismatch between transceivers [9], [30].…”

“…and Pr{·} represents the probability of the event. Finally, from (28), (30), and (31), the PDF of γ sd is obtained in (23). From (23), the system performance metrics for a U2U2U link, e.g., channel capacity, and bit error rate can be analytically characterized without resorting to time-consuming simulations.…”

Throughput maximization in poisson aerial base station–based networks with coverage probability and power density constraints

“…[6][7][8] By using these models, we need no prior information about exact number and location of ABSs, and hence, we can use stochastic geometry in ABSs and model them randomly in space. [9][10][11][12][13] In other words, at the beginning step of network design, we find the efficient density of ABSs, and hence, we can easily obtain the relationship between network parameters and its performance. 9,11 After this step, we know some details about the network parameters and the relationships between them.…”