Large-signal FET model with multiple time scale dynamics from nonlinear vector network analyzer data

Abstract

A non-quasi static large-signal FET model is presented incorporating self-heating and other multiple timescale dynamics necessary to describe the large-signal behavior of III–V FET technologies including GaAs and GaN. The model is unique in that it incorporates electro-thermal and trapping dynamics (gate lag and drain lag) into both the model current source and the model nonlinear output charge source, for the first time. The model is developed from large-signal waveform data obtained from a modern nonlinear vector network analyzer (NVNA), working in concert with an output tuner and bias supplies. The dependences of Id and Qd on temperature, two trap states, and instantaneous terminal voltages are identified directly from NVNA data. Artificial neural networks are used to represent these constitutive relations for a compiled implementation into a commercial nonlinear circuit simulator (Agilent ADS). Detailed comparisons to large-signal measured data are presented.