High Precision 16-bit SAR ADC with Random Forest-based Error Correction for IoT Devices

The demand for high precision, low power Analog to Digital Converters (ADCs) for IoT applications is steadily increasing, especially for edge devices. This paper presents the design of a 16-bit Successive Approximation Register (SAR) ADC using the Cadence tool in 45nm CMOS technology, achieving high precision while minimizing power consumption. In addition to circuit-level optimizations, we introduce a Random Forest-based error correction algorithm to enhance accuracy by compensating for nonlinearities and mismatches in the ADC. In Comparison to traditional SAR ADC designs, our proposed approach improves energy efficiency while maintaining superior Effective Number of Bits (ENOB) and Signal-to-Noise and Distortion Ratio (SNDR). Simulations confirm that the proposed SAR ADC achieves an ENOB of 15.9 and an SNDR of 54.1dB while consuming less than 4 µW, making it well-suited for IoT edge applications requiring extended battery life and accurate signal processing.

Authors

Publication Details

Published
2025-04-07
DOI
https://doi.org/10.1109/ictmim65579.2025.10988272
Citations
1
Primary Topic
CCD and CMOS Imaging Sensors
Type
article
Field-Weighted Citation Impact
0.73
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

High Precision 16-bit SAR ADC with Random Forest-based Error Correction for IoT Devices

V Gowrishankar, S Chandru, Parimala Devi M, M Bharanipriya et al.
1 citations
CCD and CMOS Imaging Sensors
0.73
article

High Precision 16-bit SAR ADC with Random Forest-based Error Correction for IoT Devices

V Gowrishankar, S Chandru, Parimala Devi M, M Bharanipriya, N Dharineesh, P Bommisumithra
article en
1 citations

Abstract

The demand for high precision, low power Analog to Digital Converters (ADCs) for IoT applications is steadily increasing, especially for edge devices. This paper presents the design of a 16-bit Successive Approximation Register (SAR) ADC using the Cadence tool in 45nm CMOS technology, achieving high precision while minimizing power consumption. In addition to circuit-level optimizations, we introduce a Random Forest-based error correction algorithm to enhance accuracy by compensating for nonlinearities and mismatches in the ADC. In Comparison to traditional SAR ADC designs, our proposed approach improves energy efficiency while maintaining superior Effective Number of Bits (ENOB) and Signal-to-Noise and Distortion Ratio (SNDR). Simulations confirm that the proposed SAR ADC achieves an ENOB of 15.9 and an SNDR of 54.1dB while consuming less than 4 µW, making it well-suited for IoT edge applications requiring extended battery life and accurate signal processing.

Openalex Percentile: Top 29%
CCD and CMOS Imaging Sensors
0.73
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.