Functional Testing of On-chip Analog/RF Circuits using Machine Learning based Regression Models

Shrivastava, A and Banerjee, G (2022) Functional Testing of On-chip Analog/RF Circuits using Machine Learning based Regression Models. In: 6th IEEE International Test Conference India, ITC India 2022, 24 - 26 July 2022, Bangalore.

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Abstract

This study aims to utilize the simulation data col-lected during the design stages of analog and RF Integrated Circuits (ICs), to enable faster functional testing during post-silicon validation. The above approach is demonstrated for an on-chip LC-Voltage Controlled Oscillator (LC-VCO) circuit, which was fabricated in a commercially available 180nm RF CMOS process, as a part of a radar-on-chip system. The key idea is to build a Machine Learning based Regression Model (MLRM) that learns various correlations between a few internal DC-node voltages (or currents) and performance-metrics of the LC-VCO circuit, using block-level simulation data. During post-silicon IC-testing, this MLRM is then used to predict the tuning-curve of the LC-VCO by measuring the same DC-node data. Finally, preliminary silicon-based measurement results show that the proposed approach holds much promise as the difference between the predicted tuning curves and measured curves is within 5.

Item Type:	Conference Paper
Publication:	6th IEEE International Test Conference India, ITC India 2022
Publisher:	Institute of Electrical and Electronics Engineers Inc.
Additional Information:	The copyright for this article belongs to Institute of Electrical and Electronics Engineers Inc.
Keywords:	Circuit oscillations; Design for testability; Integrated circuit design; Integrated circuits; Machine learning; Oscillistors; Regression analysis; Timing circuits; Tuning, Analog/rf integrated circuits; Design for test; Design-for-test; Functional testing; LC-voltage controled oscillator; Machine-learning; On chips; Regression modelling; Simulation data; Voltage-controlled-oscillator, Variable frequency oscillators
Department/Centre:	Division of Electrical Sciences > Electrical Communication Engineering
Date Deposited:	05 Oct 2022 09:25
Last Modified:	05 Oct 2022 09:25
URI:	https://eprints.iisc.ac.in/id/eprint/77057

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