This paper, investigates and presents the optimal parameter identification of digital pre-distortion (DPD) models for radio frequency power amplifiers (RF PAs) using a modified differential evolution (MDE) based optimization algorithm. Compared to the conventional exhaustive search method which is computationally intensive, our proposed approach enables the identification of a best-fit DPD model from a combinatorially large model space in a short time. In addition, applying information criteria based objective functions in the optimization process enables us to achieve sparse selection of dynamical models, which balances the model accuracy and model complexity. Experimental validation on a GaN based class AB power amplifier illustrates that, our proposed approach was able to accurately identify complexity reduced optimal DPD models without compromising the modeling accuracy.

本文研究并提出了一种基于改进的差分进化（MDE）的优化算法，用于射频功率放大器（RF PA）的数字预失真（DPD）模型的最优参数识别。与传统的穷举搜索方法（计算量大）相比，我们提出的方法能够在短时间内从组合大的模型空间中识别出最适合的DPD模型。此外，在优化过程中应用基于信息准则的目标函数可以使我们实现动力学模型的稀疏选择，从而平衡了模型的准确性和模型的复杂性。在基于GaN的AB类功率放大器上进行的实验验证表明，