Rational function-based model with memory for power amplifier behavioral modeling

Polynomials have been extensively used to model power amplifier (PA) behavior because of their linearity in the parameters, which eases their identification. However, these models are inherently local, being unable to extrapolate the PA behavior for conditions not considered during model extraction. This paper presents a model which, based on the ratio of two polynomials, avoids the catastrophic error degradation of polynomials (being thus suitable for large-signal behavior prediction) but still can be extracted using linear regression techniques. This model is tested with measured data from a class-AB PA.