基于最小二乘误差算法的功率放大器静态非线性解嵌入

Wei Wei, J. Mikkelsen, O. K. Jensen
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引用次数: 0

摘要

本文提出了一种引入最小二乘误差算法的去嵌入方法,以恢复宽带调制信号激励下功率放大器色散输出的静态非线性。静态非线性特性用多项式表示,并从显示频散调幅/调幅和调幅/调幅失真效应的实测数据中提取系数。所建立的静态非线性函数适用于Wiener和Hammerstein PA模型的实现。将所提出的解嵌入方法与先前提出的基于移动平均算法或人工神经网络的解嵌入方法进行了比较,发现所提出的解嵌入方法简化了解嵌入过程,并且使静态非线性的数学表示更简单。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Deembedding static nonlinearities of power amplifiers using least square error algorithm
This paper presents a deembedding method that introduces the least square error algorithm as a means to retrieve the static nonlinearities of the dispersive output of power amplifiers excited by wideband modulated signals. The characteristics of static nonlinearities are expressed as polynomials and the coefficients are extracted from measured data showing dispersive AM/AM and AM/PM distortion effects. The formulated static nonlinear function is suitable for both Wiener and Hammerstein PA model implementations. The proposed deembedding method is compared to previously proposed methods based on moving average algorithms or artificial neural networks, of comparable accuracy and the proposed method is found to simplify the deembedding procedure and in addition it leads to a simpler mathematical representation of the static nonlinearity.
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