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Nonlinear Behavioral Modeling of Power Amplifiers Using Radial-Basis Function Neural Networks
University of Gävle, Department of Technology and Built Environment, Ämnesavdelningen för elektronik.
University of Gävle, Department of Technology and Built Environment, Ämnesavdelningen för elektronik. Ericsson AB, Gävle, Sweden.
University of Gävle, Department of Technology and Built Environment, Ämnesavdelningen för elektronik.
2005 (English)In: 2005 IEEE MTT-S International Microwave Symposium Digest, 2005, 1967-1970 p.Conference paper, Published paper (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
2005. 1967-1970 p.
Keyword [en]
Modeling, neural networks, nonlinear distortion, power amplifiers, radio transmitter
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:hig:diva-2427DOI: 10.1109/MWSYM.2005.1517128ISI: 000234561203063Scopus ID: 2-s2.0-31044438373ISBN: 0-7803-8845-3 (print)OAI: oai:DiVA.org:hig-2427DiVA: diva2:119089
Conference
IEEE MTT-S International Microwave Symposium, 11-17 juni, 2005, Long Beach, CA,USA8
Available from: 2007-01-18 Created: 2007-01-18 Last updated: 2017-01-11Bibliographically approved

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • harvard-cite-them-right
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • sv-SE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • de-DE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf