A bivariate Volterra series approach to modeling and linearization of power amplifiers

Abstract

A bivariate Volterra series perspective is adopted for a generic power amplifier (PA) modeling. This approach is motivated by the presence of a PA mechanism responsible of an internal signal generation. The bivariate resulting model extends a conventional Volterra model by including terms containing cross products of the input signal and the new internal variable. The approach is developed considering a simple univariate Volterra model and the signal envelope as the internal variable. The enriched structure incorporates new terms with the envelope raised to odd powers. A particular case of this bivariate Volterra series approach is the generalized memory polynomial model. The convenience of the bivariate terms in the model structure of a class J PA is experimentally demonstrated for the amplifier driven by a 30-MHz 5G New Radio signal, over a range of more than 13 dB output power levels. Results for the digital predistortion of the class J PA are also provided, illustrating as well the benefits of the bivariate model for the linearization performance.