University of Oulu

R. Inanlou, M. Safarpour and O. Silvén, "Arithmetic Tracking Adaptive SAR ADC for Signals With Low-Activity Periods," in IEEE Access, vol. 8, pp. 211621-211629, 2020, doi: 10.1109/ACCESS.2020.3040034

Arithmetic tracking adaptive SAR ADC for signals with low-activity periods

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Author: Inanlou, Reza1; Safarpour, Mehdi2; Silvén, Olli2
Organizations: 1School of Electrical and Computer Engineering, University of Tehran, Iran
2Center for Machine Vision and Signal Analysis (CMVS), University of Oulu, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 1.6 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2020120198833
Language: English
Published: Institute of Electrical and Electronics Engineers, 2020
Publish Date: 2020-12-01
Description:

Abstract

This paper introduces a novel arithmetic tracking algorithm for successive approximation ADCs, and presents its analysis. The algorithm utilizes low activity signal periods to cut the ADC energy dissipation by reducing the number of required bit-cycles. The approach determines the required step size, and bypasses conversion cycles when signal activity is low, without compromising the precision or sampling rate. The required first-order predictions and boundary checkings are performed with simple digital circuits. A lowered number of cycles paired with reduced voltage variations across DAC capacitors yields power savings. The solution has been simulated in a 90 nm CMOS process using HSPICE, demonstrating a 10-bit tracking SAR ADC. The proposed ADC was examined with low activity signals such as EEG, ECG, etc. The results predict from 5.8 μW to 27.6 μW dissipation when the sampling rates range from 32 kHz to 800 kHz, respectively.

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Series: IEEE access
ISSN: 2169-3536
ISSN-E: 2169-3536
ISSN-L: 2169-3536
Volume: 8
Pages: 211621 - 211629
DOI: 10.1109/ACCESS.2020.3040034
OADOI: https://oadoi.org/10.1109/ACCESS.2020.3040034
Type of Publication: A1 Journal article – refereed
Field of Science: 213 Electronic, automation and communications engineering, electronics
Subjects:
IoT
Funding: This work was supported by the 6G Flagship research programme under Academy of Finland Grant 318927.
Academy of Finland Grant Number: 318927
Detailed Information: 318927 (Academy of Finland Funding decision)
Copyright information: © The Authors 2020. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.
  https://creativecommons.org/licenses/by/4.0/