Green-Energy-Empowered Multibeam Collaborative RF Wireless Charging for IoT

Sixth generation (6G) communications empower billions of IoT devices (IoTDs), bringing significant convenience to modern life. However, the challenge of powering a burgeoning number of IoTDs has become a critical concern. radio frequency (RF) wireless charging technology is a promising solution to this issue; however, its adoption has been limited due to its relatively low charging efficiency. Beamforming facilitated by antenna arrays can enhance the efficiency of RF wireless charging. In addition, renewable (green) energy can act as the energy source for RF wireless chargers. In this work, we integrate beamforming technique with green energy empowered RF wireless charging to develop a 3-D charging model for a green charge (GC). Furthermore, when investigating the multi-GC to multi-IoTD wireless charging scenario, we derive an accurate model to quantify the accumulation of wireless energy in the charging area. Based on this, we formulate the multi-GC to multi-IoTD charging efficiency maximization problem to enhance the energy received by IoTDs within a given charging period. Since this optimization problem is proved to be NP-hard, we propose the Efficient multibeAm coopeRative chargiNg (EARN) algorithm to solve it efficiently. EARN coordinates multiple charging beams by intelligently assigning proper compensating phases to each GC, effectively utilizing the energy transmitted by GCs in all directions to strengthen the wireless charging effect. Ultimately, extensive simulations validate the performance of the EARN algorithm in conspicuously improving the wireless charging efficiency.