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Nonlinear Behavioral Modeling of Power Amplifiers Using Radial-Basis Function Neural Networks
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- Isaksson, Magnus, 1969- (author)
- Högskolan i Gävle,Ämnesavdelningen för elektronik
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- Wisell, David (author)
- Högskolan i Gävle,Ämnesavdelningen för elektronik,Ericsson AB, Gävle, Sweden
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- Rönnow, Daniel (author)
- Högskolan i Gävle,Ämnesavdelningen för elektronik
- (creator_code:org_t)
- 2005
- 2005
- English.
- In: 2005 IEEE MTT-S International Microwave Symposium Digest. - 0780388453 ; , s. 1967-1970
- Conference paper (peer-reviewed)
Abstract
Subject headings
Close
- 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.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Annan elektroteknik och elektronik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Other Electrical Engineering, Electronic Engineering, Information Engineering (hsv//eng)
Keyword
- Modeling
- neural networks
- nonlinear distortion
- power amplifiers
- radio transmitter
- Electronics
- Elektronik
Publication and Content Type
- ref (subject category)
- kon (subject category)
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