UAV-BS Integration with Urban Infrastructure: An Energy Efficiency Perspective

UAV-BS Integration with Urban Infrastructure: An Energy Efficiency Perspective

WoS Article

The integration of uncrewed aerial vehicles (UAVs) with fifth-generation (5G) cellular networks has been a prominent research focus in recent years and continues to attract significant interest in the context of sixth-generation (6G) wireless networks. UAVs can serve as aerial wireless platforms to provide on-demand coverage, mobile edge computing, and enhanced sensing and communication services. However, UAV-assisted networks present new opportunities and challenges due to the inherent size, weight, and power constraints of UAVs, their controllable mobility, and the line-ofsight (LoS) characteristics of communication channels. This article discusses these opportunities and challenges from the viewpoint of mobile network operators (MNOs), and offers a novel perspective on efficiently utilizing modern city infrastructures for UAV deployment in typical urban scenarios. In these scenarios, UAV-mounted base stations (UAV-BSs) can significantly improve service continuity and network energy efficiency. We compare system performance in terms of user satisfaction and energy efficiency between conventional UAV deployment, which follows demand dynamics, and an alternative approach where UAVs land on urban infrastructure equipped with charging stations. To identify the preferred UAV locations, while considering the limited availability of such stations and environmental dynamics, we employ a data-driven genetic algorithm. This algorithm closely approximates the true optimal locations subject to a moderate computational budget.

The integration of uncrewed aerial vehicles (UAVs) with fifth-generation (5G) cellular networks has been a prominent research focus in recent years and continues to attract significant interest in the context of sixth-generation (6G) wireless networks. UAVs can serve as aerial wireless platforms to provide on-demand coverage, mobile edge computing, and enhanced sensing and communication services. However, UAV-assisted networks present new opportunities and challenges due to the inherent size, weight, and power constraints of UAVs, their controllable mobility, and the line-ofsight (LoS) characteristics of communication channels. This article discusses these opportunities and challenges from the viewpoint of mobile network operators (MNOs), and offers a novel perspective on efficiently utilizing modern city infrastructures for UAV deployment in typical urban scenarios. In these scenarios, UAV-mounted base stations (UAV-BSs) can significantly improve service continuity and network energy efficiency. We compare system performance in terms of user satisfaction and energy efficiency between conventional UAV deployment, which follows demand dynamics, and an alternative approach where UAVs land on urban infrastructure equipped with charging stations. To identify the preferred UAV locations, while considering the limited availability of such stations and environmental dynamics, we employ a data-driven genetic algorithm. This algorithm closely approximates the true optimal locations subject to a moderate computational budget.

Genetic algorithms; Autonomous aerial vehicles; Optimization; Heuristic algorithms; Wireless communication; Energy efficiency; Batteries; Wireless sensor networks; Vehicle dynamics; Sensors

Genetic algorithms; Autonomous aerial vehicles; Optimization; Heuristic algorithms; Wireless communication; Energy efficiency; Batteries; Wireless sensor networks; Vehicle dynamics; Sensors

KIRUBAKARAN, B.; VIKHROVA, O.; ANDREEV, S.; HOŠEK, J.

2025

04.11.2024

IEEE

PISCATAWAY

0163-6804

IEEE COMMUNICATIONS MAGAZINE

63

3

United States of America

100

106

7

https://ieeexplore.ieee.org/abstract/document/10742573

http://hdl.handle.net/11012/250747

UAV-BS_Integration_with_Urban_Infrastructure_An_Energy_Efficiency_Perspective