A 0.016 mm2 12 b $\Delta \Sigma $ SAR With 14 fJ/conv. for Ultra Low Power Biosensor Arrays
| Autor: | Timothy G. Constandinou, Lieuwe B. Leene |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Engineering
business.industry 020208 electrical & electronic engineering Electrical engineering Topology (electrical circuits) 02 engineering and technology Delta-sigma modulation Noise (electronics) Noise shaping 020202 computer hardware & architecture Effective number of bits Sampling (signal processing) CMOS 0202 electrical engineering electronic engineering information engineering Electronic engineering Oversampling Electrical and Electronic Engineering business |
| Zdroj: | IEEE Transactions on Circuits and Systems I: Regular Papers. 64:2655-2665 |
| ISSN: | 1558-0806 1549-8328 |
| DOI: | 10.1109/tcsi.2017.2703580 |
| Popis: | The instrumentation systems for implantable brain–machine interfaces represent one of the most demanding applications for ultra low-power analogue-to-digital-converters (ADC) to date. To address this challenge, this paper proposes a $\Delta \Sigma $ SAR topology for very large sensor arrays that allows an exceptional reduction in silicon footprint by using a continuous time 0–2MASH topology. This configuration uses a specialized FIR window to decimate the $\Delta \Sigma $ modulator output and reject mismatch errors from the SAR quantizer, which mitigates the overhead from dynamic element matching techniques commonly used to achieve high precision. A fully differential prototype was fabricated using $0.18\,\mu $ m CMOS to demonstrate 10.8 ENOB precision with a 0.016 mm2 silicon footprint. Moreover, a 14fJ/conv figure-of-merit can be achieved, while resolving signals with the maximum input amplitude of ±1.2 Vpp sampled at 200 kS/s. The ADC topology exhibits a number of promising characteristics for both high speed and ultra low-power systems due to the reduced complexity, switching noise, sampling load, and oversampling ratio, which are critical parameters for many sensor applications. |
| Databáze: | OpenAIRE |
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