Optimized Technique for Unmanned Aerial Vehicle (UAV) Power Harvesting in Cloud-RAN

Abstract

This paper introduces an Optimized Technique for Unmanned Aerial Vehicles (UAVs) Power Harvesting in Cloud-RAN. In full cooperation scenarios, all base station antennas emit energy in all directions, which can lead to higher power consumption and reduced efficiency. Additionally, a power harvesting scheme is implemented to enable UAVs to recharge their batteries during operation, thus extending their endurance. The proposed techniques involve formulating sparse optimization problems and applying reweighted ℓ1- norm approximation and semidefinite relaxation (SDR) algorithms to solve them iteratively with RRHs simultaneously transmitting information beams to information-receiving terminals and energy beams to active energy-receiving terminals, aiming to optimize power harvesting, reduce total power transmission, and lower the costs of the network. The results demonstrate significant improvements in power harvesting efficiency compared to traditional full cooperation-based approaches. In conclusion, the techniques presented in this paper offer effective solutions for optimizing UAV power harvesting in Cloud-RAN systems. By utilizing sparse beamforming and addressing the problem of full cooperation, these techniques enhance the power harvesting efficiency and sustainability of UAV-based wireless communication networks in Cloud-RAN.