IC Noise Modeling Using Trigger-Correlated Frequency Extraction
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Solution Overview
Problem
Existing noise model generating methods for integrated circuits lack accuracy in distinguishing noise generated in response to trigger signals, leading to inaccurate noise models that fail to effectively manage noise in circuit operations.
Innovation Solution
A method involving calculating a transfer function, acquiring a noise level waveform with high correlation to a trigger signal, and generating a noise model using short-time Fourier transform and filtering to extract relevant frequencies, thereby isolating noise associated with trigger signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional noise model generating methods are used, then the process is simple, but the accuracy of noise model is insufficient
Solution Approach 1:
The patent segments the noise measurement process into distinct frequency components using Short-Time Fourier Transform (STFT). By dividing the time-frequency space and analyzing different frequency bands separately, the method can identify noise correlated with trigger signals at specific frequencies while filtering out uncorrelated noise, thereby improving noise model accuracy without overwhelming complexity
Solution Approach 2:
The patent introduces an intermediary processing step that calculates correlation between measured noise and trigger signals at each frequency component. This intermediary correlation analysis acts as a mediator to distinguish relevant noise from irrelevant noise, enabling accurate noise model generation while maintaining manageable processing complexity through systematic filtering
2Measurement precision
If noise measurement is performed without frequency analysis, then the measurement process is simple, but the ability to identify trigger-related noise is insufficient
Solution Approach 1:
The patent transforms the noise measurement from a single time-domain signal into a two-dimensional time-frequency representation using STFT. By adding the frequency dimension, the method can identify which frequency components are correlated with trigger signals, significantly improving noise identification accuracy while the systematic approach keeps measurement complexity manageable
3Measurement precision
If all noise components are included in the noise model, then the model covers all noise sources, but the model includes irrelevant noise reducing its effectiveness
Solution Approach 1:
The patent extracts only the noise components that are correlated with trigger signals by analyzing each frequency component's correlation with the trigger. This extraction process removes irrelevant noise from the noise model, improving its relevance and effectiveness for predicting trigger-related noise while maintaining reasonable filtering complexity through the systematic correlation-based selection
Data Source
AI summary
A noise model generating method includes calculating a transfer function from inside of an integrated circuit of an electric circuit to a measurement point in the electric circuit; acquiring a noise level waveform of a frequency with a high correlation with a trigger signal from measurement results of noise when the integrated circuit is caused to output the trigger signal; and generating the noise model of the integrated circuit on the basis of the transfer function calculated and the noise level waveform acquired. Acquiring the noise level waveform further includes: causing the integrated circuit to output a trigger signal; measuring the trigger signal and noise at the measurement point at time intervals to obtain measured values at the measurement point and at the time intervals; performing a conversion operation to generate, for each frequency, the noise level waveform indicating a change of the noise over time on the basis of the measured values at the measurement point; calculating, for each frequency, a correlation value indicating a correlation between the noise level waveform and a change of the trigger signal over time; and performing a filtering operation to extract the noise level waveform of a frequency with a high correlation from the correlation value.