Litcius/Paper detail

A Wide Input Range All-NMOS Rectifier With Gate Voltage Boosting Technique for Wireless Power Transfer

Xiaguang Li, Keping Wang, Yixin Zhou, Yanjie Pan, Fanyi Meng, Kaixue Ma

2023IEEE Transactions on Circuits & Systems II Express Briefs14 citationsDOI

Abstract

This brief presents an all-NMOS RF-DC rectifier with a wide high power conversion efficiency (high-PCE) input power range by utilizing gate voltage boosting technique (GVBT). The all-NMOS architecture combines the benefits of cross-coupled and GVBT-based diode-like rectifiers for maximum electron mobility and reduced the conduction losses. The GVBT applied to rectifying transistors not only reduces the reverse leakage current, but also enhances the conductivity. As a result, the PCE and the input power range are improved simultaneously. The proposed rectifier is fabricated with a 0.18- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> standard CMOS technology. The measurement results show that the all-NMOS rectifier achieves 57.6% PCE, −14.8 dBm sensitivity and large than 20 dB high-PCE input power range with a 10 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\text{k}\Omega $ </tex-math></inline-formula> load.

Topics & Concepts

Wireless power transferNMOS logicBoosting (machine learning)Electrical engineeringVoltageMaterials scienceRectifier (neural networks)Computer scienceElectronic engineeringWirelessEngineeringTelecommunicationsTransistorArtificial intelligenceStochastic neural networkRecurrent neural networkArtificial neural networkEnergy Harvesting in Wireless NetworksWireless Power Transfer SystemsRadio Frequency Integrated Circuit Design