Efficient generation of X-parameters transistor models by sequential sampling

This letter proposes a sequential sampling technique to generate efficiently multidimensional X-parameters models for microwave transistors, while guaranteeing X-parameters' validity and overcoming simulator convergence issues. The sequential sampling process selects a set of samples that are subsequently used to construct behavioral models with radial basis functions. The proposed method was compared with a tabular X-parameters model with cubic spline interpolation. The radial basis function models demonstrate very fast convergence and greater accuracy already for a few tens of samples. The proposed technique is illustrated for a GaAs HEMT using Curtice3 and Chalmers empirical model simulations as the data source.This letter proposes a sequential sampling technique to generate efficiently multidimensional X-parameters models for microwave transistors, while guaranteeing X-parameters' validity and overcoming simulator convergence issues. The sequential sampling process selects a set of samples that are subsequently used to construct behavioral models with radial basis functions. The proposed method was compared with a tabular X-parameters model with cubic spline interpolation. The radial basis function models demonstrate very fast convergence and greater accuracy already for a few tens of samples. The proposed technique is illustrated for a GaAs HEMT using Curtice3 and Chalmers empirical model simulations as the data source.A