Modeling Power Amplifier Nonlinearities with Artifical Neural Network

This paper describes a method for modeling nonlinear power amplifier for RF applications. Presented model is based on the neural network architecture and can be applied to characterize memoryless behaviour of power amplifiers. For simulation we use feed-forward neural network to make a normalized input-output conversion for nonlinear characteristic of power amplifier. The results show that neural network can be a good tool in modeling process of nonlinear components used in RF circuits. The numerical comparison between existing methods (Saleh model) is computed in order to evaluate performance of the proposed model of interpolation of power amplifier nonlinearities.