Data-Driven 3D Placement of UAV Base Stations for Arbitrarily Distributed Crowds

TL;DR

This paper introduces a data-driven algorithm for optimally positioning UAV base stations in 3D space to enhance cellular network performance and meet diverse user demands efficiently.

Contribution

It presents a novel polynomial-time algorithm for 3D placement of UAV-BSs that maximizes sumrate while satisfying user data rate requirements in heterogeneous networks.

Findings

Improves system sumrate compared to networks without UAV-BSs.

Efficient polynomial-time algorithm for UAV-BS placement.

Effectively handles arbitrarily distributed user demands.

Abstract

In this paper, we consider an Unmanned Aerial Vehicle (UAV)-assisted cellular system which consists of multiple UAV base stations (BSs) cooperating the terrestrial BSs. In such a heterogeneous network, for cellular operators, the problem is how to determine the appropriate number, locations, and altitudes of UAV-BSs to improve the system sumrate as well as satisfy the demands of arbitrarily flash crowds on data rates. We propose a data-driven 3D placement of UAV-BSs for providing an effective placement result with a feasible computational cost. The proposed algorithm searches for the appropriate number, location, coverage, and altitude of each UAV-BS in the serving area with the maximized system sumrate in polynomial time so as to guarantee the minimum data rate requirement of UE. The simulation results show that the proposed approach can improve system sumrate in comparison with the case without UAV-BSs.