Nonlinear behavioral modeling of power amplifiers using radial-basis function neural networks

被引：8
|
作者：
Isaksson, M [1 ]
Wisell, D
Rönnow, D
机构：
[1] Univ Gavle, SE-80176 Gavle, Sweden
[2] Ericsson Telecom AB, SE-80006 Gavle, Sweden
来源：
2005 IEEE MTT-S International Microwave Symposium, Vols 1-4 | 2005年
关键词：
modeling; neural networks; nonlinear distortion; power amplifiers; radio transmitter;
D O I：
10.1109/MWSYM.2005.1517128
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：
A radial-basis function neural network (RBFNN) is proposed for modeling the dynamic nonlinear behavior of RF power amplifiers. In the model the signal's envelope is used. The model requires less training than a model using both IQ-data. Sampled input and output signals from a power amplifier for 3G were used in the identification and validation. The RBFNN is compared with a parallel Hammerstein model. For a memory depth of one sample the RBFNN gives a better model, in- and out-of-band; for three samples the RBFNN reduces the in-band error more while the Hammerstein model reduces the error out-of-band more.
引用
收藏
页码：1967 / 1970
页数：4
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