Performance Optimization for UAV-Enabled Wireless Communications under Flight Time Constraints

TL;DR: A gradient-based algorithm is proposed for optimally partitioning the geographical area based on the users' distribution, flight times, and locations of the UAVs, and results show that the proposed cell partitioning approach yields a significantly higher fairness among the users compared to the classical weighted Voronoi diagram.

Abstract: In this paper, the effective use of unmanned aerial vehicles (UAVs) as flying base stations that can provide wireless service to ground users is investigated. In particular, a novel framework for optimizing the performance of such UAV-based wireless systems, in terms of the average number of bits (data service) transmitted to users under flight time constraints, is proposed. In the considered model, UAVs are deployed over a given geographical area to serve ground users that are distributed within a given area based on an arbitrary spatial distribution function. In this case, based on the maximum possible flight times of the UAVs, the average data service delivered to the users is maximized by finding the optimal cell partitions associated to the UAVs, under a fair resource allocation scheme. To this end, using the powerful mathematical framework of optimal transport theory, a gradient-based algorithm is proposed for optimally partitioning the geographical area based on the users' distribution, flight times, and locations of the UAVs. Simulation results show that the proposed cell partitioning approach yields a significantly higher fairness among the users compared to the classical weighted Voronoi diagram. In particular, by using our approach, the Jain's fairness index is improved by a factor of 2.6.