New Transistor Behavioral Model Formulation Suitable for Doherty PA Design

Abstract

This work presents a new artificial neural network (ANN) model formulation for RF high-power transistors which includes the S-parameters of the active device. This improves the small-signal extrapolation capability, and the OFF-state impedance approximation, making it suitable for Doherty power amplifier (DPA) design. This extrapolation capability plays a key role in the correct Doherty load modulation prediction, since, at low power levels, the peaking PA is subjected to active loads that cannot be synthetized with a passive load-pull system, forcing the model to extrapolate. Thus, the proposed model formulation is able to solve the issues that are normally observed when ANN-based models are used in complex PA architectures as the Doherty PA. To validate the proposed behavioral model, a 700-W asymmetrical LDMOS DPA, centered at 1.84 GHz, was simulated and measured.