Accurate Estimation of Memory Polynomial Model Dimension for Dynamic Nonlinear RF Power Amplifiers

In this paper, the dimension estimation of memory polynomial based power amplifiers' behavioral models is investigated. Comprehensive study of state of the art performance assessment metrics is carried out. To ensure the generality of the conclusions, the study is experimentally validated using three power amplifiers prototypes designed using various transistors technologies and amplifier topologies. The results show that the performance assessment metrics are equally reliable for the estimation of the device under test nonlinearity order. However, they are inconsistent when used to estimate its memory depth. This limitation is circumvented by applying memoryless post-compensation technique during the memory depth estimation. The proposed approach demonstrates that the dimension estimation can be made objective and independent of the performance assessment metric.