DocumentCode
1911326
Title
Recurrent neural networks usefulness in digital pre-distortion of power amplifiers
Author
Ciminski, Andrzej S.
Author_Institution
Vallingbyvagen, Vallingby, Sweden
Volume
1
fYear
2004
fDate
17-19 May 2004
Firstpage
249
Abstract
Digital pre-distortion techniques are widely utilized in linearization of RF power amplifiers. In this paper recurrent neural networks are used to model an inverse function of the power amplifier. This function predistorts an input signal in digital domain in order to increase the linearity of the modeled power amplifier. The simulation results are presented.
Keywords
distortion; microwave power amplifiers; recurrent neural nets; RF power amplifier linearization; digital pre-distortion; inverse function; power amplifiers; recurrent neural networks; Costs; Intelligent networks; Inverse problems; Linearity; Linearization techniques; Nonlinear distortion; Power amplifiers; Power generation; Radiofrequency amplifiers; Recurrent neural networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Microwaves, Radar and Wireless Communications, 2004. MIKON-2004. 15th International Conference on
Print_ISBN
83-906662-7-8
Type
conf
DOI
10.1109/MIKON.2004.1356909
Filename
1356909
Link To Document