Identification Methods with Different Digital Predistortion Models for Power Amplifiers with Strong Nonlinearity and Memory Effects
Paper in proceeding, 2020
Different methods have been used to identify a digital predistortion (DPD) model coefficients in power amplifier (PA) linearization, especially direct and indirect learning architecture (DLA/ILA), and iterative learning control (ILC) technique, etc. A comparison is made in this paper under the scenario of a PA with strong nonlinearity. Analysis of DLA and ILC shows their similarity. However DLA works only with linear-in-parameter models, excluding the new emerging neural network models which has shown a good linearization accuracy with ILC according to experimental results.
opitmization
nonlinear distortion
power amplifiers
model identification
Digital predistortion
neural network
Author
Siqi Wang
Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks
Wenhui Cao
Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks
Thomas Eriksson
Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks
2020 IEEE MTT-S International Wireless Symposium, IWS 2020 - Proceedings
9360062
9781728167039 (ISBN)
2020 IEEE MTT-S International Wireless Symposium (IWS)
Shanghai, China,
Shanghai, China,
Subject Categories
Bioinformatics (Computational Biology)
Control Engineering
Other Electrical Engineering, Electronic Engineering, Information Engineering
DOI
10.1109/IWS49314.2020.9360062