An adaptive fuzzy logic system for the compensation of nonlinear distortion in wireless power amplifiers

被引：3
|
作者：
Vaskovic, Mina [1 ]
Kodogiannis, Vassilis S. [1 ]
Budimir, Djuradj [1 ]
机构：
[1] Univ Westminster, Fac Sci & Technol, London W1W 6UW, England
来源：
NEURAL COMPUTING & APPLICATIONS | 2018年 / 30卷 / 08期
关键词：
Linearization; Pre-distortion; RF power amplifiers; Neuro-fuzzy systems; Neural networks; BEHAVIORAL-MODEL; RF;
D O I：
10.1007/s00521-017-2849-3
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Computational intelligent systems are becoming an increasingly attractive solution for power amplifier (PA) behavioural modelling, due to their excellent approximation capability. This paper utilizes an adaptive fuzzy logic system (AFLS) for the modelling of the highly nonlinear MIMIX CFH2162-P3 PA. Moreover, PA's inverse model based also on AFLS has been developed in order to act as a pre-distorter unit. Driving an LTE 1.4MHz 64 QAM signal at 880MHz as centre frequency at PA's input, very good modelling performance was achieved, for both PA's forward and inverse dynamics. A comparative study of AFLS and neural networks (NN) has been carried out to establish AFLS as an effective, robust and easy-to-implement baseband model, which is suitable for inverse modelling of PAs and capable to be used as an effective digital pre-distorter. Pre-distortion system based on AFLS achieved distortion suppression of 84.2%, compared to the 48.4% gained using the NN-based equivalent scheme.
引用
收藏
页码：2539 / 2554
页数：16
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