A Nanowatt Area-Efficient 16-Channel Bandpass Filterbank with Floating Active Capacitance Multiplier for Acoustic Signal Processing

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A Nanowatt Area-Efficient 16-Channel Bandpass Filterbank with Floating Active Capacitance Multiplier for Acoustic Signal Processing
Title:
A Nanowatt Area-Efficient 16-Channel Bandpass Filterbank with Floating Active Capacitance Multiplier for Acoustic Signal Processing
Journal Title:
2024 IEEE International Symposium on Circuits and Systems (ISCAS)
Publication Date:
02 July 2024
Citation:
Zhang, Z., Goh, W. L., & Gao, Y. (2024). A Nanowatt Area-Efficient 16-Channel Bandpass Filterbank with Floating Active Capacitance Multiplier for Acoustic Signal Processing. 2024 IEEE International Symposium on Circuits and Systems (ISCAS), 1–5. https://doi.org/10.1109/iscas58744.2024.10557888
Abstract:
This paper introduces an area-efficient nanowatt 16-channel bandpass filterbank tailored for acoustic signal processing in Artificial Internet of Things (AIoT) sensor systems. Integration of a floating active capacitance multiplier (FACM) adeptly addresses the inherent challenge of increased area in source-follower-based filters due to their larger capacitance. Compared to conventional gm-C circuits, this work offers reduced power consumption, a more straightforward structure, and tunability. In a standard 0.13-μm CMOS process, simulations reveal the filterbank's frequency range spans from 90 Hz to 5 kHz with a gain of 17dB, and a total power consumption of 97nW for the 16 channels. When benchmarked against contemporary BPFs, this work achieves an unparalleled area efficiency of 0.038mm^2/channel and superior linearity. Such a compact and energy-efficient design offers a competitive solution for analog feature extraction in edge AI applications.
License type:
Publisher Copyright
Funding Info:
This research / project is supported by the Agency for Science, Technology and Research (A*STAR), Singapore - Nanosystems at the Edge Programme
Grant Reference no. : A18A1b0055
Description:
© 2024 IEEE.  Personal use of this material is permitted.  Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
ISSN:
2158-1525
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