Analysis, Modeling, and Design of a 2.45-GHz RF Energy Harvester for SWIPT IoT Smart Sensors

Abstract

Simultaneous wireless information and power transfer (SWIPT) is a flexible and cheap way to supply Internet-of-Things (IoT) smart sensors avoiding battery replacement. In this paper, we analyze, model, and design a 2.45-GHz RF energy harvesting (RFEH) system based on a discrete-component matching network (MN), a custom 65-nm CMOS cross-coupled rectifier, and an off-the-shelf storage-charging power management unit (PMU), which regulates the rectifier output voltage with maximum power point tracking (MPPT). We propose a reverse global analysis to model the RFEH. It allows an accurate prediction of the power harvesting efficiency (PHE) to directly size the MN and select the RFEH MPPT regulation ratio, at different incident RF power levels. We perform parasitic-aware RFEH design to take advantage of printed circuit board (PCB)/package capacitive parasitics at the rectifier input for optimizing the $\pi $ -MN with the help of the proposed RFEH modeling results. We show that this parasitic capacitance introduces a maximum bound on the real impedance at the rectifier input to ensure good impedance matching in practice. MPPT is used to help reach this target real impedance at given incident RF power, as the rectifier equivalent input impedance is a function of both its input and output voltages. Measurement results show a sensitivity as low as −17.1 dBm with a peak PHE of 48.3% at −3-dBm incident RF power. Global modeling, simulation, and measurement results demonstrate that the PHE is limited by PCB/package parasitic capacitance and that PCB/packaging technology improvement to reduce parasitic capacitance by 150 fF could boost the PHE up to 45% for a low incident RF power level of −10 dBm.