1 research outputs found
Optimizing Number, Placement, and Backhaul Connectivity of Multi-UAV Networks
Multi-Unmanned Aerial Vehicle (UAV) Networks is a promising solution to
providing wireless coverage to ground users in challenging rural areas (such as
Internet of Things (IoT) devices in farmlands), where the traditional cellular
networks are sparse or unavailable. A key challenge in such networks is the 3D
placement of all UAV base stations such that the formed Multi-UAV Network (i)
utilizes a minimum number of UAVs while ensuring -- (ii) backhaul connectivity
directly (or via other UAVs) to the nearby terrestrial base station, and (iii)
wireless coverage to all ground users in the area of operation. This joint
Backhaul-and-coverage-aware Drone Deployment (BoaRD) problem is largely
unaddressed in the literature, and, thus, is the focus of the paper. We first
formulate the BoaRD problem as Integer Linear Programming (ILP). However, the
problem is NP-hard, and therefore, we propose a low complexity algorithm with a
provable performance guarantee to solve the problem efficiently. Our simulation
study shows that the Proposed algorithm performs very close to that of the
Optimal algorithm (solved using ILP solver) for smaller scenarios, where the
area size and the number of users are relatively small. For larger scenarios,
where the area size and the number of users are relatively large, the proposed
algorithm greatly outperforms the baseline approaches -- backhaul-aware greedy
and random algorithm, respectively by up to 17% and 95% in utilizing fewer UAVs
while ensuring 100% ground user coverage and backhaul connectivity for all
deployed UAVs across all considered simulation setting.Comment: To appear in IEEE Internet of Things Journa