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Two novel memory polynomial models for modeling of RF power amplifiers

Published online by Cambridge University Press:  02 April 2014

Per N. Landin Open the ORCID record for Per N. Landin [Opens in a new window] ,
Kurt Barbé ,
Wendy Van Moer ,
Magnus Isaksson  and
Peter Händel
Per N. Landin*
Affiliation:
Department of Electronics, Mathematics and Natural Sciences, University of Gävle, Kungsbäcksvägen 47, 80176 Gävle, Sweden. Phone: +46 31 772 1885 Department of Signals and Systems, Chalmers University of Technology, Hörsalsvägen 11, 41296 Göteborg, Sweden Department for Fundamental Electricity and Instrumentation (ELEC), Vrije Universiteit Brussel, Pleinlaan 2, 1050 Elsene, Brussels, Belgium Signal Processing Laboratory, KTH Royal Institute of Technology, Osquldasväg 1, 10044 Stockholm, Sweden
Kurt Barbé
Affiliation:
Department for Fundamental Electricity and Instrumentation (ELEC), Vrije Universiteit Brussel, Pleinlaan 2, 1050 Elsene, Brussels, Belgium
Wendy Van Moer
Affiliation:
Department for Fundamental Electricity and Instrumentation (ELEC), Vrije Universiteit Brussel, Pleinlaan 2, 1050 Elsene, Brussels, Belgium
Magnus Isaksson
Affiliation:
Department of Electronics, Mathematics and Natural Sciences, University of Gävle, Kungsbäcksvägen 47, 80176 Gävle, Sweden. Phone: +46 31 772 1885
Peter Händel
Affiliation:
Signal Processing Laboratory, KTH Royal Institute of Technology, Osquldasväg 1, 10044 Stockholm, Sweden
*
Corresponding author: P.N. Landin Email: [email protected]
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Abstract

Two novel memory polynomial models are derived based on physical knowledge of a general power amplifier (PA). The derivations are given in detail to facilitate derivations of other model structures. The model error in terms of normalized mean square error (NMSE) and adjacent channel error power ratio (ACEPR) of the novel model structures are compared to that of established models based on the number of parameters using data measured on two different amplifiers, one high-power base-station PA and one low-power general purpose amplifier. The novel models show both lower NMSE and ACEPR for any chosen number of parameters compared to the established models. The low model errors make the novel models suitable candidates for both modeling and digital predistortion.

Keywords

Power amplifiers and linearizersWireless systems and signal processing (SDR, MIMO, UWB, etc.)
Type
Research Papers
Information
International Journal of Microwave and Wireless Technologies , Volume 7 , Issue 1 , February 2015 , pp. 19 - 29
Copyright
Copyright © Cambridge University Press and the European Microwave Association 2014 

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