Experimental Evaluation of PA Digital Predistortion Based on Simple Feedforward Neural Network

被引：0

作者：

Rosolowski, Dawid W. ^{[1
]}

Jedrzejewski, Konrad ^{[2
]}

机构：

[1] Warsaw Univ Technol, Fac Elect & Informat Technol, Inst Radioelect & Multimedia Technol, Warsaw, Poland

[2] Warsaw Univ Technol, Fac Elect & Informat Technol, Inst Elect Syst, Warsaw, Poland

来源：

2020 23RD INTERNATIONAL MICROWAVE AND RADAR CONFERENCE (MIKON 2020) | 2020年

关键词：

digital predistortion; DPD; power amplifier; linearization; neural network;

D O I：

暂无

中图分类号：

O59 [应用物理学];

学科分类号：

摘要：

The paper presents the results of experimental studies on evaluation of employing digital predistortion based on simple feedforward neural network for linearization of microwave power amplifiers. The influence of the number of neurons in the hidden layer, the number of delayed input samples at the input of neural network, as well as the number of samples taken for learning a neural network were studied and discussed in the paper. The main goal of this work was to establish the minimal configuration of the neural network which can be used for linearization of power amplifiers excited by wideband and high PAPR signals, e.g. LTE. The results obtained for neural networks were compared with the results obtained for the conventional predistortion method based on memory polynomial.

引用

页码：293 / 296

页数：4

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