Improved Network Coverage with Adaptive Navigation of mmWave-based Drone-Cells

Abstract

The use of drone-cells in 5G wireless systems is a topic of ongoing discussions in the 3GPP standardization community. A major advantage of employing drones is that they can dynamically and timely improve the capacity and coverage of cellular networks. To address this challenge, efficient network planning tools targeting spontaneous and rapidly changing scenarios for dynamic network design need to be developed. Complementing the recent studies on the optimal static drone-cell positioning for a Poisson point process of user equipment (UE) placement, we study UE distributions with correlated mobility models. We first derive the coverage metrics for static drone-cell deployments and then proceed by developing an algorithm for adaptive drone-cell navigation. Considering the mean number of covered UEs, we show that enabling drone-cell navigation improves the overall system performance.