带记忆的数字预失真非线性算子级联模型

A. Smirnov
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引用次数: 1

摘要

功率放大器(PA)中宽带信号的非线性失真与记忆扰动是分析处理和实际放大器线性化器实现的一个挑战。在本文中,我们将重点放在PA记忆非线性的简化级联模型上,该模型能够解决建模和识别误差以及欠采样对数字预失真性能的影响等问题。在此基础上,提出了预失真器级联非线性模型,并采用查找表两步识别算法,提高了模型识别的稳定性。与传统的记忆多项式非线性模型相比,该模型对于特定的PA失真模型具有显著的性能增益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cascaded Model of Nonlinear Operator for Digital Predistortion with Memory
Nonlinear distortion with memory perturbing the wideband signal in power amplifiers (PAs) is challenging both for analytical treatment and implementation of practical PA linearizers. In the present letter we focus on a simplified cascaded model of the PA memory nonlinearity that enables to approach such problems as the effect of modeling and identification errors and undersampling on the digital predistortion performance. Based on the presented analysis, we propose a cascaded nonlinearity model for predistorter with a 2-step identification algorithm using look-up table to improve stability of the model identification. Proposed model is shown to have significant performance gain compared to conventional memory polynomial nonlinearity model for specific models of PA distortion.
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