Neural network and memory polynomial methodologies for PA modeling

摘要

This paper attempts to present the performance of an artificial neural network (ANN) model and a memory polynomial (IMP) model for power amplifier (PA) modeling, which exhibits memory effects. The ANN model was based on time delay neural network (TDNN) and the memory polynomial model was developed using analytical polynomial function. Both models were developed to fit the dynamic AM-AM and AM-PM conversions of the PA obtained from QPSK digital modulated signal. The comparison results show that both models are applicable to model the PA, however, the TDNN model, compared to the memory polynomial model, can give better modeling results.