Open AccessAdaptive‐stage rectifier for mm ‐scale implants
Author(s) -
Alafghani T.,
Mandloi N.K.,
Ha S.
Publication year - 2020
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
ISSN - 1350-911X
DOI - 10.1049/el.2019.2307
Subject(s) - rectifier (neural networks) , transmitter , voltage , electrical engineering , antenna (radio) , cmos , peak inverse voltage , electronic engineering , signal (programming language) , engineering , computer science , voltage divider , channel (broadcasting) , dropout voltage , programming language , stochastic neural network , machine learning , recurrent neural network , artificial neural network
As the dimensions of neural implants are miniaturised to mm‐scale, wireless powering becomes more challenging. Antenna sizes become smaller, and so does the amplitudes of the received RF signal. More importantly, a meticulous effort is required when multiple implants are placed on the brain under a transmitter, as each implant has a different spatial position from the transmitter coil. In addition, RF power may fluctuate over time. These factors, both effects the coupling coefficient. In this case, rectifiers with a fixed number of stages are limited to a rather narrow operational voltage range, and cannot accommodate such variations. To address this, the authors propose an adaptive‐stage rectifier that changes the number of connected stages by monitoring the final rectifier output voltage using two comparators and a digital block. By doing so, it can generate an output voltage within the targeted voltage range for a much wider RF input voltage range. The authors' design and simulations in 180‐nm CMOS SOI process show that the proposed rectifier is capable of keeping the output voltage within 1–1.7 V for an RF input range from 0.73 to 2 V, which is five times wider than that of conventional rectifiers with three fixed stages.