A New Mixed Signal Platform to Study the Accuracy/Complexity Trade-Off of DPD Algorithms

The increase in bandwidth of Power Amplifier (PA) input signals has led to the development of more complex behavioral PA models. Most recent models such as the Generalized Memory Polynomial (1) or the Polyharmonic distortion modeling (2) can be used to design very performant but complex and thus very consuming Digital Predistortion algorithms (DPDs). On the other hand, with earlier simpler models, the precision of the DPD may not be enough. The model order is also the major factor influencing the requirements in terms of bandwidth and dynamic range of the digitized signal in the feedback loop of a typical Power amplification system architecture: the higher the order, the more information is needed for identification. This paper describes a new mixed signal simulation platform developed to study the complexity vs. accuracy trade-off from the DPD point of view. The platform estimates the accuracy of the DPD and the power consumption (including the consumption of the DPD itself) of the whole feedback loop, by comparing various PA models with various DPDs algorithms. Contrary to older works, measuring the accuracy on the open loop without DPD and estimating the complexity in theoretical number of operations, our goal is to be able to estimate with precision the performances and the power consumption of the whole amplification system (PA + DPD + DAC + feedback loop) for optimization of DPD algorithms.