Parameterized Basis Functions for Numerically Stable Behavioral Modeling of RF Power Amplifiers

In this paper, we propose a new set of parameterized basis functions suitable for behavioral modeling of RF power amplifiers exhibiting memory effects. Depending on the input signal distribution, the proposed basis functions can be optimized for numerically stable model identification procedure. The efficiency and robustness of the resulting polynomial model are demonstrated and compared to the ones of previously published polynomial models. The obtained results revealed an exceptional numerical stability regardless of the input signal statistics, making the proposed new model suitable for multimode and broadband nonlinear wireless transmitters.