Hybrid PSO-GWO Optimization Based Parameter Extraction Method Applied to GaN Devices

Abstract

In this research, four different equivalent circuit models that characterize the substrate/buffer loading effect for GaN HEMT on Si substrate have been investigated. Z-parameter measurements of an open de-embedded structure have been used to characterize this effect in 16×200 μm GaN HEMT on Si. An optimization technique based on hybridization between two meta-heuristic techniques which are Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO) has been developed to extract the models elements. Each of those techniques has been tested separately to evaluate the performance of the proposed technique. The validation process of the extracted elements is done by comparing the simulated and the measured data of the model. The accuracy and the rate of convergence of the extraction results are considered as evaluation criteria. The proposed PSO-GWO technique shows a very good agreement with previous research results, which accordingly validates the applicability of this technique for small- and large-signal modeling of transistors.