QoS-Compliant 3D Deployment Optimization Strategy for UAV Base Stations
Xukai Zhong, Yiming Huo, Xiaodai Dong, Zhonghua Liang

TL;DR
This paper presents a novel 3D deployment strategy for UAV base stations that optimizes coverage and QoS by considering capacity limits and air-to-ground path loss, using a genetic algorithm approach.
Contribution
It introduces a 3D UAV deployment model incorporating capacity and QoS constraints, and proposes a genetic algorithm for optimized placement.
Findings
Enhanced coverage percentage over existing schemes
Effective 3D deployment considering capacity and QoS
Genetic algorithm improves placement efficiency
Abstract
Unmanned aerial vehicle (UAV) is being integrated as an active element in 5G and beyond networks. Because of its flexibility and mobility, UAV base stations (UAV-BSs) can be deployed according to the ground user distributions and their quality of service (QoS) requirement. Although there has been quite some prior research on the UAV deployment, no work has studied this problem in a 3 dimensional (3D) setting and taken into account the UAV-BS capacity limit and the quality of service (QoS) requirements of ground users. Therefore, in this paper, we focus on the problem of deploying UAV-BSs to provide satisfactory wireless communication services, with the aim to maximize the total number of covered user equipment (UE) subject to user data rate requirements and UAV-BSs' capacity limit. First, we model the relationship between the air-to-ground (A2G) path loss (PL) and the location of…
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