Automated SAR ADC Sizing Using Analytical Equations

Fuente: arXiv
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Autori principali: Li, Zhongyi, Tao, Zhuofu, Zhou, Yanze, Shi, Yichen, Yu, Zhiping, Lin, Ting-Jung, He, Lei
Natura: Preprint
Pubblicazione: 2025
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author Li, Zhongyi
Tao, Zhuofu
Zhou, Yanze
Shi, Yichen
Yu, Zhiping
Lin, Ting-Jung
He, Lei
author_facet Li, Zhongyi
Tao, Zhuofu
Zhou, Yanze
Shi, Yichen
Yu, Zhiping
Lin, Ting-Jung
He, Lei
contents Conventional analog and mixed-signal (AMS) circuit designs heavily rely on manual effort, which is time-consuming and labor-intensive. This paper presents a fully automated design methodology for Successive Approximation Register (SAR) Analog-to-Digital Converters (ADCs) from performance specifications to complete transistor sizing. To tackle the high-dimensional sizing problem, we propose a dual optimization scheme. The system-level optimization iteratively partitions the overall requirements and analytically maps them to subcircuit design specifications, while local optimization loops determines the subcircuits' design parameters. The dependency graph-based framework serializes the simulations for verification, knowledge-based calculations, and transistor sizing optimization in topological order, which eliminates the need for human intervention. We demonstrate the effectiveness of the proposed methodology through two case studies with varying performance specifications, achieving high SNDR and low power consumption while meeting all the specified design constraints.
format Preprint
id arxiv_https___arxiv_org_abs_2505_09172
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Automated SAR ADC Sizing Using Analytical Equations
Li, Zhongyi
Tao, Zhuofu
Zhou, Yanze
Shi, Yichen
Yu, Zhiping
Lin, Ting-Jung
He, Lei
Hardware Architecture
Signal Processing
Conventional analog and mixed-signal (AMS) circuit designs heavily rely on manual effort, which is time-consuming and labor-intensive. This paper presents a fully automated design methodology for Successive Approximation Register (SAR) Analog-to-Digital Converters (ADCs) from performance specifications to complete transistor sizing. To tackle the high-dimensional sizing problem, we propose a dual optimization scheme. The system-level optimization iteratively partitions the overall requirements and analytically maps them to subcircuit design specifications, while local optimization loops determines the subcircuits' design parameters. The dependency graph-based framework serializes the simulations for verification, knowledge-based calculations, and transistor sizing optimization in topological order, which eliminates the need for human intervention. We demonstrate the effectiveness of the proposed methodology through two case studies with varying performance specifications, achieving high SNDR and low power consumption while meeting all the specified design constraints.
title Automated SAR ADC Sizing Using Analytical Equations
topic Hardware Architecture
Signal Processing
url https://arxiv.org/abs/2505.09172