Efficient Far-field Wireless Charging for Green Wireless Sensor Networks Using Multiple UAVs

Wireless sensor networks (WSNs) often face chronic energy supply issues, hindering their long-term continuous operations. To alleviate this issue, many existing works suggest using unmanned aerial vehicles (UAVs) to wirelessly charge WSNs. However, most of these works rely on a single UAV for charging, which is impractical for a large-scale network due to the limited energy capacity of a single UAV. In this work, we propose leveraging multiple green energy powered UAVs to charge a large-scale WSN, aiming to extend its operational lifespan. We first develop energy models for UAVs, sensor nodes (SNs) and green base station (GBS), and then formulate an optimization problem to maximize the minimum residual energy level among all SNs, thus prolonging the WSN's lifespan. Given the NP-hard nature of this problem, we present a two-step solution to solve it. In Step One, we introduce the UAVs Charging Load Balancing (UCLB) algorithm to determine the minimum number of needed UAVs and balance their energy consumption. This algorithm enables each UAV to charge as many SNs as possible, thereby reducing the overall number of UAVs required. Once the minimum required number of UAVs is established, in Step Two, we propose the SNs Energy Balancing (SEB) algorithm to ensure that all the SNs have as much energy as possible, and nearly equal residual energy levels after wireless charging. Finally, extensive simulations demonstrate the effectiveness of our proposed solution in extending the lifespans of the SNs.