UAV-Enabled Mobile RAN and RF-Energy Transfer Protocol for Enabling Sustainable IoT in Energy-Constrained Networks

Abstract

This article introduces a novel approach for Unmanned Aerial Vehicles (UAV) assisted wireless power transfer (WPT) within a Radio Access Network (RAN) provisioned Internet of Things (IoT) network. The goal is to efficiently charge scattered IoT Nodes (INs) within their respective energy deadlines. The proposed methodology combines the concepts of Radio Frequency Energy Transfer (RFET) zones, K-means clustering, and Ant Colony Optimization (ACO) to optimize the charging process. Initially, RFET zones are formed around the INs, and K-means clustering is applied to group nodes based on their spatial proximity and energy requirements. Subsequently modified ACO algorithm is employed to construct efficient paths for UAVs to visit these clusters. This is achieved by taking into account several aspects such as node deadlines and UAV capacity, thereby assuring the timely and efficient transmission of energy. After comparative analysis with EUP-ACS and IA-DRL, the proposed algorithm achieves a substantial reduction of 22.22% and 36.36% respectively in UAV usage, while also exhibiting significant improvements in RFET zones, energy efficiency, and survival rate, confirming its effectiveness in enhancing charging performance, reducing energy waste, and meeting deadlines.