ANN-BASED PAD MODELING TECHNIQUE FOR MOSFET DEVICES

In this paper, an approach for the pad modeling of the test structure for Metal Oxide Semiconductor Field Effect Transistor (MOSFET) up to 40\,GHz is presented. The approach is based on a combination of the conventional equivalent circuit model and artificial neural network (ANN). The pad capacitances and series resistors are directly obtained from EM (electromagnetic) simulation of the $S$ parameters with different size of pad and operating frequency. The parasitic elements in the test structure can be modeled by using a sub artificial neural network (SANN). So the pad capacitances and series resistors can be regarded as functions of the dimensions of the pad structure and operating frequencies by using SANN. Good agreement between the ANN-based modeling and EM simulation results has been demonstrated. In order to remove the impact of the parasitic elements, the de-embedding procedure for MOSFET device using ANN-based pad model is also demonstrated.