Uncertainty Quantification of RF Circuits Using Stochastic Collocation Techniques

Abstract

This paper presents a study on the Polynomial Chaos based approach for uncertainty quantification. It discusses employing different polynomial chaos based techniques for uncertainty quantification of RF circuits. Here, the performance of different Stochastic Collocation techniques such as the pseudo-spectral projection, linear regression, and interpolation technique, is investigated using two illustrative circuit examples. The first example deals with the uncertainty quantification of phase noise in a 2.4 GHz CMOS LC tank oscillator, while in the second one, gain of a 2.4 GHz low-noise amplifier is analyzed in the presence of uncertainty. The applied techniques are investigated and compared with the traditional Monte Carlo simulations approach. The advantages and disadvantages of each of the presented techniques are discussed, which are validated using the illustrations. The results of our study provide guidance for choosing the appropriate technique for modeling and quantifying uncertainty for similar circuits.

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