Neural-network-based adaptive baseband predistortion method for RF power amplifiers

被引：35

作者：

Naskas, N ^{[1
]}

Papananos, Y ^{[1
]}

机构：

[1] Natl Tech Univ Athens, Sch Elect & Comp Engn, Zografos 15773, Greece

来源：

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS | 2004年 / 51卷 / 11期

关键词：

baseband predistortion; multilayer perceptron (MLP); neural network (NN); power amplifier (PA);

D O I：

10.1109/TCSII.2004.837284

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

An adaptive baseband predistortion method for RF power amplifier (PA) linearization is proposed and experimentally demonstrated. The predistortion component is implemented by a single-input dual-output multilayer perceptron (MLP). Both amplitude-to-amplitude and amplitude-to-phase distortion products are compensated by backpropagation training of the neural network including the response of the PA. Effects of modulator and demodulator imperfections on system performance are examined. Measurements on a system prototype reveal a significant linearity improvement that reaches 25 dB.

引用

页码：619 / 623

页数：5

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