Scalable HEMT small-signal model extraction based on a hybrid multibias approach

A multibias approach for HEMT small-signal model extraction is proposed. The method is based on scaling rules and uses a hybrid direct extraction/particle swarm optimization approach. By the use of a reduced number of S-parameter measurements in the optimization procedure, the computational effort is kept low. The extraction procedure is verified with measurements on metamorphic HEMTs, leading to accurate and scalable models in the millimeter-wave range. Furthermore, the robustness of the proposed method against measurement uncertainties is verified by using PHEMT synthetic data, intentionally affected by errors.