DocumentCode
2640040
Title
Using neural network for reduction distrotion introduced by power amplifier in digital communication systems
Author
Pochmara, J.
Author_Institution
Poznan Univ. of Technol.
fYear
2006
fDate
22-24 June 2006
Firstpage
698
Lastpage
702
Abstract
We proposed and improved an adaptive neural predistorter, which can automatically compensate for amplifier nonlinearity and thus makes it possible to transmit OFDM signals without incurring intolerable distortions. The neural predistorter utilizes gradient algorithms for its adaptation. Our results indicate clear improvements in performance for neural networks networks incorporating memory into their structure
Keywords
OFDM modulation; digital communication; neural nets; power amplifiers; OFDM signals; adaptive neural predistorter; digital communication systems; distortion reduction; gradient algorithms; neural network; nonlinear distortion; power amplifier linearization; Computer science; Digital communication; Intelligent networks; Microelectronics; Neural networks; Power amplifiers;
fLanguage
English
Publisher
ieee
Conference_Titel
Mixed Design of Integrated Circuits and System, 2006. MIXDES 2006. Proceedings of the International Conference
Conference_Location
Gdynia
Print_ISBN
83-922632-2-7
Type
conf
DOI
10.1109/MIXDES.2006.1706674
Filename
1706674
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