Digital Predistorter with Real-Valued Feedback Employing Forward Model Estimation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F18%3APU128891" target="_blank" >RIV/00216305:26220/18:PU128891 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/ICT.2018.8464937" target="_blank" >http://dx.doi.org/10.1109/ICT.2018.8464937</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ICT.2018.8464937" target="_blank" >10.1109/ICT.2018.8464937</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Digital Predistorter with Real-Valued Feedback Employing Forward Model Estimation

Popis výsledku v původním jazyce

Digital predistorters (DPD) are used in modern communication systems to linearise nonlinear power amplifiers (PA) and maximise power efficiency. For their function, a feedback signal from the PA output is required. A conventional DPD uses a quadrature mixer and two analogue-to-digital converters (ADC) which consume additional power and increase system complexity. In this paper we have proposed an innovative technique which allows to use a nonquadrature RF mixer with one ADC in the feedback path. The DPD adaptation is noniterative and based on favoured indirect learning architecture. Firstly, the forward PA model is estimated and subsequently it is used to train DPD coefficients. We have verified and compared the proposed method with other DPD architectures in simulations. The results show that the proposed architecture can achieve the same results as a DPD with complex feedback samples and the other real-valued feedback architectures.

Název v anglickém jazyce

Digital Predistorter with Real-Valued Feedback Employing Forward Model Estimation

Popis výsledku anglicky

Digital predistorters (DPD) are used in modern communication systems to linearise nonlinear power amplifiers (PA) and maximise power efficiency. For their function, a feedback signal from the PA output is required. A conventional DPD uses a quadrature mixer and two analogue-to-digital converters (ADC) which consume additional power and increase system complexity. In this paper we have proposed an innovative technique which allows to use a nonquadrature RF mixer with one ADC in the feedback path. The DPD adaptation is noniterative and based on favoured indirect learning architecture. Firstly, the forward PA model is estimated and subsequently it is used to train DPD coefficients. We have verified and compared the proposed method with other DPD architectures in simulations. The results show that the proposed architecture can achieve the same results as a DPD with complex feedback samples and the other real-valued feedback architectures.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20202 - Communication engineering and systems

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of International Conference on Telecommunications (ICT 2018)

ISBN

978-1-5386-2320-6

ISSN

—

e-ISSN

—

Počet stran výsledku

5

Strana od-do

1-5

Název nakladatele

Neuveden

Místo vydání

Neuveden

Místo konání akce

Saint Malo, France

Datum konání akce

26. 6. 2018

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000446016500087