DocumentCode
2164352
Title
Behavioral modeling of power amplifiers using fully recurrent neural networks
Author
Luongvinh, Danh ; Kwon, Youngwoo
Author_Institution
Sch. of Electr. Eng., Seoul Nat. Univ., South Korea
fYear
2005
fDate
12-17 June 2005
Abstract
This paper describes the first implementation of fully recurrent neural networks (FRNN) for behavioral modeling of power amplifiers. The proposed recurrent neural network model utilizes global feedbacks and full interconnections between neurons in hidden layers. The model has successfully been trained with W-CDMA signal. Then it is tested with not only W-CDMA signal but CDMA-1S95 and 2-tone signals as well. Good agreements between measured and modeled results have been achieved.
Keywords
3G mobile communication; code division multiple access; integrated circuit modelling; neural nets; power amplifiers; 3G power amplifier; behavioral modeling; complementary cumulative probability density function; fully recurrent neural network; global feedback; neuron; wideband CDMA signal; Artificial neural networks; Integrated circuit interconnections; Multiaccess communication; Neural networks; Neurofeedback; Neurons; Nonlinear dynamical systems; Power amplifiers; Recurrent neural networks; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Microwave Symposium Digest, 2005 IEEE MTT-S International
ISSN
01490-645X
Print_ISBN
0-7803-8845-3
Type
conf
DOI
10.1109/MWSYM.2005.1517131
Filename
1517131
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