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Near-Optimal Decoding of Incremental Delta-Sigma ADC Output

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journal contribution
submitted on 2023-08-27, 08:42 and posted on 2023-09-19, 12:57 authored by Bo Wang, Man-Kay Law, Samir Brahim Belhaouari, Amine Bermak

This paper presents a nonlinear digital decoder (reconstruction filter) for incremental delta-sigma modulators. This decoder utilizes both the magnitude and pattern information of the modulator output to achieve accurate input estimation. Compared to the conventional linear filters with the same oversampling ratio (OSR), it can improve the converter's signal-to-quantization noise ratio by a few dB to a few 10's of dB with slight thermal noise performance degradation. Using the proposed decoder, the modulator's OSR can be a few times less while achieving the same resolution and data rate, thus minimizing the modulator as well as its peripheral circuits' energy consumption. In this paper, the proposed decoder is optimized for digital implementation, with its function being verified using a modulator prototype. This decoder is mainly designed for dc or near-dc signal conversions and it does not provide frequency notches.

Other Information

Published in: IEEE Transactions on Circuits and Systems I: Regular Papers
License: https://creativecommons.org/licenses/by/4.0/
See article on publisher's website: https://dx.doi.org/10.1109/tcsi.2020.3010991

Funding

Open Access funding provided by the Qatar National Library.

History

Language

  • English

Publisher

IEEE

Publication Year

  • 2020

License statement

This Item is licensed under the Creative Commons Attribution 4.0 International License.

Institution affiliated with

  • Hamad Bin Khalifa University
  • College of Science and Engineering - HBKU