Enhancing Wireless Connectivity Through Bayesian-Optimized UAV-BS Positioning and Charging

Abstract

Enhancing wireless network coverage in densely populated urban environments poses a significant challenge due to high-rise buildings and intricate topographical features obstructing signal propagation. To augment network coverage in challenging areas, our paper proposes the utilization of Unmanned Aerial Vehicles Base Stations (UAV-BSs) as dynamic communication relays. By employing Bayesian optimization, we strategically position UAV-BSs to extend signal coverage to regions inadequately served by traditional cellular infrastructure. An essential contribution of our approach lies in integrating diverse urban elements for UAV-BS recharging, encompassing the utilization of transformer lines, adapting customized balconies, and exploiting cellular infrastructure rooftops. These various recharging locations considerably extend the operational duration of UAV-BSs. Through extensive simulations, we demonstrate that our approach ensures a remarkable percentage increase in UAV-BS operating time and significantly enhances network connectivity for areas with high user density and traffic demand. Further, underscoring the practicality of our solution in addressing the complex challenges of urban wireless communication, this research represents a significant advancement in UAV-BS-assisted network capacity enhancement, offering a scalable and efficient solution for densely populated urban areas.