Unmanned Aerial Vehicle With Underlaid Device-to-Device Communications: Performance and Tradeoffs

TLDR

The study examines the trade‑off between coverage and delay, measured by the number of UAV stop points, needed to fully cover a target area. The paper analyzes deploying a UAV as a flying base station to provide on‑the‑fly wireless communication over a specified geographic region. An analytical framework is developed to evaluate coverage and rate for a UAV‑based downlink coexisting with an underlaid D2D network, considering static and mobile UAV scenarios, optimal altitude, stop‑point planning via disk covering, and outage probability with retransmissions. Results indicate that optimal UAV altitudes exist for maximizing sum‑rate and coverage depending on D2D density, and that intelligent UAV mobility reduces total transmit power while achieving full coverage.

Abstract

In this paper, the deployment of an unmanned aerial vehicle (UAV) as a flying base station used to provide on the fly wireless communications to a given geographical area is analyzed. In particular, the co-existence between the UAV, that is transmitting data in the downlink, and an underlaid device-todevice (D2D) communication network is considered. For this model, a tractable analytical framework for the coverage and rate analysis is derived. Two scenarios are considered: a static UAV and a mobile UAV. In the first scenario, the average coverage probability and the system sum-rate for the users in the area are derived as a function of the UAV altitude and the number of D2D users. In the second scenario, using the disk covering problem, the minimum number of stop points that the UAV needs to visit in order to completely cover the area is computed. Furthermore, considering multiple retransmissions for the UAV and D2D users, the overall outage probability of the D2D users is derived. Simulation and analytical results show that, depending on the density of D2D users, optimal values for the UAV altitude exist for which the system sum-rate and the coverage probability are maximized. Moreover, our results also show that, by enabling the UAV to intelligently move over the target area, the total required transmit power of UAV while covering the entire area, is minimized. Finally, in order to provide a full coverage for the area of interest, the tradeoff between the coverage and delay, in terms of the number of stop points, is discussed.