MOS Transistor Noise Model Verification via Statistical Parameter Adjustment
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Solution Overview
Problem
Conventional MOS transistor models do not adequately consider noise variation, leading to imprecise noise simulation and uncertainty in design quality.
Innovation Solution
A method is developed to build and verify MOS transistor models by measuring noise on different dies, creating noise distribution diagrams, and adjusting noise parameters in simulation models to ensure data coverage, thereby accounting for statistical noise variation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional MOS transistor models use fixed noise parameters from library files, then the model structure remains simple, but the noise simulation precision deteriorates due to not considering process variations
Solution Approach 1:
The patent transforms fixed noise parameters into dynamic parameters that vary according to process variations. By introducing statistical distribution functions and random sampling, the model adapts noise parameters to different process conditions, thereby improving simulation precision without requiring a fundamentally complex model structure
Solution Approach 2:
The patent changes noise parameters from fixed values to statistically distributed values that reflect process variations. By using parameter distribution functions and random sampling techniques, the model incorporates process variation effects while maintaining the same basic model framework, thus improving precision without significantly increasing complexity
2Measurement precision
If noise parameters are adjusted to cover all measured data points, then the model precision improves, but the ease of operation deteriorates due to continuous parameter tuning required
Solution Approach 1:
The patent performs preliminary actions by pre-calculating parameter distributions and generating verification data before actual design use. The model is pre-configured with statistical parameter distributions and verified against measured data, so that during actual design operations, users can directly use the verified model without needing to perform continuous parameter tuning
Solution Approach 2:
The patent establishes a feedback mechanism where the model is verified by comparing simulation results with measured noise data from different dies. This feedback loop allows automatic adjustment and validation of parameter distributions, improving verification accuracy while automating the tuning process to maintain ease of operation
Data Source
AI summary
The present invention discloses a method for building an MOS transistor model enclosing statistical variation of noise, including: measuring noise in MOS transistors from different dies; creating a noise distribution diagram in accordance with the obtained noise data of the MOS transistors; adding a variation of noise parameter in at least one noise model file into a library file of MOS transistor to simulate noise in MOS transistors; if a simulation result does not cover the noise data in the noise distribution diagram, changing the variation of the noise parameter until the simulation result covers the noise data in the noise distribution diagram; if the simulation result covers the noise data in the noise distribution diagram, adding corresponding variation of the noise parameter into the library file of MOS transistor as the MOS transistor model enclosing statistical variation of noise. The model obtained by the present invention is more precise.