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Noise-Parameter Uncertainties: A Monte Carlo Simulation.
1National Institute of Standards and Technology, Boulder, CO 80305.
This study quantifies uncertainties in noise-parameter measurements using Monte Carlo simulations. Results show how input variations impact noise parameter accuracy, aiding measurement enhancement.
Area of Science:
- Electrical Engineering
- Metrology
Background:
- Accurate noise-parameter measurements are crucial for electronic device characterization.
- Quantifying uncertainties in these measurements is essential for reliable performance evaluation.
Purpose of the Study:
- To develop and apply a Monte Carlo simulation to assess uncertainties in noise-parameter measurements.
- To determine the impact of various underlying quantity uncertainties on noise parameter accuracy.
Main Methods:
- Formulation of a Monte Carlo simulation model.
- Computation of the dependence of noise parameter uncertainty on underlying quantity uncertainties.
- Analysis of uncertainties from reflection coefficients, noise source temperature, connector variability, ambient temperature, and output noise measurement.
Main Results:
- Quantified the impact of individual uncertainty sources on noise-parameter measurements.
- Presented results for both uncorrelated and correlated uncertainties.
- Evaluated the effectiveness of using a cold noise source and measuring the 'reverse configuration' for measurement enhancement.
Conclusions:
- The Monte Carlo simulation effectively models uncertainties in noise-parameter measurements.
- Identified key sources contributing to measurement uncertainty.
- Demonstrated potential enhancements for improving the accuracy of noise-parameter measurements.

