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Instantaneous Sample Indexed Magnitude-Selective Affine Function-Based Behavioral Model for Digital Predistortion of RF Power Amplifiers

机译:基于瞬时样本索引的基于幅度选择仿射函数的射频功率放大器数字预失真行为模型

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摘要

In this paper, we present a new behavioral model for digital predistortion (DPD) of RF power amplifiers in wireless transmitters. Derived from the decomposed vector rotation model, the new model uses magnitude-selective affine functions as nonlinear operators to construct nonlinear behavior of the model, leading to a highly efficient hardware implementation. Moreover, cross-terms are carefully redesigned based on a new formulation of model structure that not only improves the modeling performance but also significantly lowers the complexity of model extraction. Simulation and experimental results have demonstrated its superior performance and efficient hardware implementation, making this model well suitable for future DPD deployment in 5G small cell base stations where digital hardware resource is highly constrained.
机译:在本文中,我们提出了一种新的行为模型,用于无线发射机中射频功率放大器的数字预失真(DPD)。从分解后的矢量旋转模型衍生而来,新模型使用幅度选择仿射函数作为非线性算子来构造模型的非线性行为,从而实现了高效的硬件实现。此外,根据新的模型结构公式精心设计了交叉术语,不仅提高了建模性能,而且显着降低了模型提取的复杂性。仿真和实验结果证明了其卓越的性能和高效的硬件实现,使得该模型非常适合数字硬件资源高度受限的5G小型蜂窝基站中未来的DPD部署。

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