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Decorrelation-based Piecewise Digital Predistortion: Operating Principle and RF Measurements

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Details

Original languageEnglish
Title of host publication2019 16th International Symposium on Wireless Communication Systems (ISWCS)
PublisherIEEE
Pages340-344
Number of pages5
ISBN (Electronic)978-1-7281-2527-5
ISBN (Print)978-1-7281-2528-2
DOIs
Publication statusPublished - 21 Oct 2019
Publication typeA4 Article in a conference publication
EventInternational Symposium on Wireless Communication Systems -
Duration: 1 Jan 1900 → …

Publication series

NameInternational Symposium on Wireless Communication Systems (ISWCS)
ISSN (Print)2154-0217
ISSN (Electronic)2154-0225

Conference

ConferenceInternational Symposium on Wireless Communication Systems
Period1/01/00 → …

Abstract

In this paper, we propose a new closed-loop learning architecture for digital predistortion (DPD) with piecewise (PW) memory polynomial models. The technique is targeted specifically for power amplifiers (PAs) that exhibit strong nonlinear behavior and nonlinear memory effects, such as those implemented with gallium nitride (GaN) technology. The learning algorithm is based on a computationally simple decorrelating learning rule, which is applied on each PW polynomial model separately. Measurements with LTE-A signals on a basestation GaN PA show that the proposed technique clearly outperforms the reference closedloop memory polynomial DPD, in terms of reducing the adjacent channel emissions.

Keywords

  • Radio frequency, Gallium nitride, Decorrelation, Silicon, Nonlinear distortion, Distortion measurement, Predistortion, 5G, digital predistortion, GaN power amplifiers, linearization, adaptive filters, nonlinear signal processing

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