A Feedback Self-adaptive Body Biasing-based RF-DC Rectifier for Highly-sensitive RF Energy Harvesting

Using radio frequency (RF) energy to power Internet of Things (IoT) devices over extended distances poses a challenge due to limited input power. As we move farther from the source, the intensity of radio waves diminishes according to an inverse square law. Implementing an internal feedback body biasing connection using flipped-well transistors can dynamically enhance the rectifier’s conductivity and eliminate the need for external circuitry. In this work, we propose a novel feedback self-adaptive body biasing rectifier for RF energy harvesting for the UHF band (902-928 MHz). Based on 22nm fully-depleted silicon-on-insulator (FDSOI) technology, this rectifier achieves the high sensitivity required to harvest weak signals at far distances and a competitive power conversion efficiency (PCE). Furthermore, we introduce a methodology for designing and optimizing a differential impedance matching network (IMN) and rectifier. Based on the simulation results, our proposed 5-stage rectifier exhibits a high sensitivity of -31.4dBm at 1V under a capacitive load, surpassing comparable results achieved by previous works. A good peak PCE of 31.3% under a 5MΩ load at the typical corner makes our rectifier an ideal choice for ultra-low power RF energy harvesting applications.