Paper Info
Title
Statistical Linearization of Phased Arrays Using Power Adaptive Power Amplifier Model
Abstract
Phased arrays used in millimeter-wave systems challenge the concept of power amplifier (PA) linearization by digital predistortion (DPD). This is due to the shared digital path and inaccuracies in analog beamforming and other component variations. However, the group behavior of multiple parallel nonlinear branches can be expected to be more predictable due to averaging effect compared to a single branch behavior. In this paper, we use a power adaptive nonlinear model to mimic the average behavior of a single PA and utilize the probability distribution of the input power of each individual PA to approximate the expected nonlinear behavior of the array over-the-air. The approximated array response is used for the DPD training. The simulation results indicate that the proposed approach provides good linearization performance for large arrays that have varying amplitude and phase weights.
Year
DOI
Venue
2019
10.1109/PIMRC.2019.8904111
2019 IEEE 30th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)
Keywords
Field
DocType
phased arrays,millimeter-wave systems,power amplifier linearization,digital predistortion,shared digital path,inaccuracies,analog beamforming,component variations,group behavior,multiple parallel nonlinear branches,averaging effect,single branch behavior,power adaptive nonlinear model,average behavior,single PA,input power,individual PA,expected nonlinear behavior,array over-the-air,approximated array response,good linearization performance,phase weights,statistical linearization,power adaptive power amplifier model
Computer science,Electronic engineering,Real-time computing,Linearization,Amplifier
Conference
ISSN
ISBN
Citations 
2166-9570
978-1-5386-8111-4
0
PageRank 
References 
Authors
0.34
1
4
Name
Order
Citations
PageRank
Bilal Khan100.34
Nuutti Tervo212.78
Aarno Pärssinen3297.12
Markku J. Juntti41065127.57