Highly Efficient Broadband Ambient Energy Harvesting System Enhanced by Meta-Lens for Wirelessly Powering Battery-less IoT Devices

Existing Internet of Things (IoT) devices face a significant challenge in terms of power consumption due to their limited battery life. Capturing and utilizing ambient radio-frequency (RF) energy emerges as a promising solution for powering low-power sensors and electronic devices, given its unique spatial and temporal distributions. However, the low level of ambient RF power severely hampers the rectenna's RF-to-direct current (dc) conversion efficiency, making it incapable of generating sufficient dc power. To address this issue and enhance the conversion efficiency of a broadband rectenna at low environmental power levels, this study introduces a novel technique called the meta-lens-assisted technique (MAT). This technique leads to a substantial increase in the rectenna's received RF power by more than 10 dB. As a result, the total conversion efficiency improves by over 30% across a wide-frequency band ranging from 2.9 to 3.63 GHz (with a fractional bandwidth of 22.3%), even when the initial RF power received (without the MAT) was as low as -20 dBm, which approaches the real-life ambient RF power level. Notably, the proposed MAT achieves a 40%-60% efficiency improvement compared to state-of-the-art approaches. These remarkable results demonstrate the promising potential of the MAT rectenna as an alternative for harvesting low-density wireless energy and supporting low-power-required industrial IoT applications.