RF-power amplifier characteristics determination using parallel cascade Wiener models and pseudo-inverse techniques

This article presents a black-box modeling approach of a microwave power amplifier (PA) and defines the linear and nonlinear operation regions. An in-band quasi-white real-valued noise like signal is used as stimulus for the identification process to excite every possibly source of nonlinearity. A segment of the input-output measurement data is processed to generate an initial parallel cascade Wiener model (PCWM). The first order Volterra kernel is extracted in order to estimate the amplifier´s memory. Then pseudo-inverse techniques are used to find a parsimonious model. This model is cross-validated with the entire measurement data. The presented modeling approach results in a model intended to be numerically robust and having a high identification percentage based on a variance figure of merit. Finally the linear and nonlinear operation regions of the amplifier are defined, as an alternative to the use of AM/AM curves.