Identification Methods with Different Digital Predistortion Models for Power Amplifiers with Strong Nonlinearity and Memory Effects
Paper i 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

Författare

Siqi Wang

Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk

Wenhui Cao

Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk

Thomas Eriksson

Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk

2020 IEEE MTT-S International Wireless Symposium, IWS 2020 - Proceedings

9360062
9781728167039 (ISBN)

2020 IEEE MTT-S International Wireless Symposium (IWS)
Shanghai, China,

Ämneskategorier

Bioinformatik (beräkningsbiologi)

Reglerteknik

Annan elektroteknik och elektronik

DOI

10.1109/IWS49314.2020.9360062

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Senast uppdaterat

2021-03-25