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Subthreshold DC-Gain enhancement by exploiting small size effects of MOSFETs


Yang, M-H; Liu, S-C; Delbruck, T (2014). Subthreshold DC-Gain enhancement by exploiting small size effects of MOSFETs. Electronics Letters, 50(11):835-837.

Abstract

A pseudo-cascode split-transistor technique is proposed for DC-gain enhancement of amplifiers in the subthreshold by exploiting the small size effects of metal-oxide semiconductor field effect transistors (MOSFETs) including the reverse short-channel effect and the inverse narrow-width effect. It requires no body-biasing and occupies a small area. A compact 114 μm2 two-stage amplifier with pseudo-cascode compensation for in-pixel amplification in vision sensors has been designed using the proposed technique. A total of 10 samples of split-transistors and amplifiers fabricated in an UMC 0.18 μm standard CMOS process were measured. More than half of the tested split-transistors show considerable DC-gain enhancement over a wide range of bias currents and nine amplifiers have increased DC gains larger than 85 dB at about 4 nA power consumption.

Abstract

A pseudo-cascode split-transistor technique is proposed for DC-gain enhancement of amplifiers in the subthreshold by exploiting the small size effects of metal-oxide semiconductor field effect transistors (MOSFETs) including the reverse short-channel effect and the inverse narrow-width effect. It requires no body-biasing and occupies a small area. A compact 114 μm2 two-stage amplifier with pseudo-cascode compensation for in-pixel amplification in vision sensors has been designed using the proposed technique. A total of 10 samples of split-transistors and amplifiers fabricated in an UMC 0.18 μm standard CMOS process were measured. More than half of the tested split-transistors show considerable DC-gain enhancement over a wide range of bias currents and nine amplifiers have increased DC gains larger than 85 dB at about 4 nA power consumption.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Neuroinformatics
Dewey Decimal Classification:570 Life sciences; biology
Language:English
Date:2014
Deposited On:25 Feb 2015 10:23
Last Modified:05 Apr 2016 19:01
Publisher:The Institution of Engineering and Technology
Number of Pages:3
ISSN:0013-5194
Publisher DOI:https://doi.org/10.1049/el.2014.1056

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