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, Kommunikations- och antennsystem, Kommunikationssystem

Wenhui Cao

Chalmers, Elektroteknik, Kommunikations- och antennsystem, Kommunikationssystem

Thomas Eriksson

Chalmers, Elektroteknik, Kommunikations- och antennsystem, Kommunikationssystem

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

9360062

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