功率放大器中短期记忆非线性的建模和预失真方法

P. Gilabert, G. Montoro, E. Bertran
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引用次数: 13

摘要

本文从精度(即与实际数据的相似程度)和复杂性(参数化所需系数的数量)两方面,对使用某些动态非线性模型对具有记忆效应的功率放大器(PA)建模的适用性进行了研究。随后,针对数字预失真器(PD)模型的辨识,考虑到预失真质量的主要指标(相邻信道功率比ACPR、发送端误差矢量幅值EVM和接收端误码率BER),提出了一种基于Hammerstein的预失真器,并提出了一种新的经验方法来选择对Hammerstein模型有贡献的最佳延迟。这个先前的实证研究允许使用最显著的延迟有助于预失真过程。因此,数字预失真器保持可扩展性,这是一个重要的优点因素,因为它必须能够在数字信号处理器中实现
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Methodology to Model and Predistort Short-Term Memory Nonlinearities in Power Amplifiers
This paper presents a study on the suitability of using certain dynamic nonlinear models for modelling the power amplifier (PA) with memory effects in terms of accuracy (that is how it resembles the real data) and complexity (number of coefficients needed in the parameterization). Later, focusing in the digital predistorter (PD) model identification and taking into account the main predistortion quality indicators (adjacent channel power ratio ACPR, error vector magnitude EVM at the transmitter, and the bit error rate BER at the receiver), a Hammerstein based predistorter is proposed and a new empirical method for choosing the best delays contributing in the Hammerstein model is presented. This previous empirical study permits the use of the most significant delays contributing in the predistortion process. Therefore the digital predistorter remains scalable which is an important factor of merit since it has to be capable of being implemented in a digital signal processor
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