Detail publikace

Určení optimálního řádu pro linearizaci a modelování výkonových zesilovačů

GÖTTHANS, T. BAUDOIN, G. MBAYE, A.

Originální název

Optimal Order Estimation for Modeling and Predistortion of Power Amplifiers

Český název

Určení optimálního řádu pro linearizaci a modelování výkonových zesilovačů

Anglický název

Optimal Order Estimation for Modeling and Predistortion of Power Amplifiers

Typ

článek ve sborníku

Jazyk

en

Originální abstrakt

Digital baseband predistortion is a cost effective approach to linearize a power amplifier. For a given type of model, two questions have to be solved: estimation of the model coefficients, and determination of the model structure, e.g. orders of nonlinearity, memory lengths. To choose proper orders of series is not evident in order to keep low complexity with acceptable results. In the article, we propose to use an integer genetic algorithm for the determination of orders of polynomial series for predistortion or power mamplifier modeling. The used fitness function aims to achieve a compromize between accuracy and complexity of the model. The method is evaluated on real measured power amplifier. The obtained results show that the proposed integer genetic algorithm is able to determine in a very small number of iterations a good model structure. Its complexity is quite low and it can be applied whether offline or online for adaptive determination of the structure.

Český abstrakt

Článek se zabývá určením optimálních řádů struktury linearizačních rovnic za použití celočíselného genetického algoritmu.

Anglický abstrakt

Digital baseband predistortion is a cost effective approach to linearize a power amplifier. For a given type of model, two questions have to be solved: estimation of the model coefficients, and determination of the model structure, e.g. orders of nonlinearity, memory lengths. To choose proper orders of series is not evident in order to keep low complexity with acceptable results. In the article, we propose to use an integer genetic algorithm for the determination of orders of polynomial series for predistortion or power mamplifier modeling. The used fitness function aims to achieve a compromize between accuracy and complexity of the model. The method is evaluated on real measured power amplifier. The obtained results show that the proposed integer genetic algorithm is able to determine in a very small number of iterations a good model structure. Its complexity is quite low and it can be applied whether offline or online for adaptive determination of the structure.

Klíčová slova

zesilovač, linearizace, modelování

Rok RIV

2013

Vydáno

16.11.2013

Místo

Tel-Aviv

ISBN

978-1-4577-1692-8

Kniha

IEEE COMCAS 2013

Strany od

1

Strany do

5

Strany počet

5

BibTex


@inproceedings{BUT102956,
  author="Tomáš {Götthans} and Genevieve {Baudoin} and Amadou {Mbaye}",
  title="Optimal Order Estimation for Modeling and Predistortion of Power Amplifiers",
  annote="Digital baseband predistortion is a cost effective approach to linearize a power amplifier. For a given type of model, two questions have to be solved: estimation of the model coefficients, and determination of the model structure, e.g. orders of nonlinearity, memory lengths. To choose proper orders of series is not evident in order to keep low complexity with acceptable results. In the article, we propose to use an integer genetic algorithm for the determination of orders of polynomial series for predistortion or power mamplifier modeling. The used fitness function aims to achieve a compromize between accuracy and complexity of the model. The method is evaluated on real measured power amplifier. The obtained results show that the proposed integer genetic algorithm is able to determine in a very small number of iterations a good model structure. Its complexity is quite low and it can be applied whether offline or online for adaptive determination of the structure.",
  booktitle="IEEE COMCAS 2013",
  chapter="102956",
  howpublished="electronic, physical medium",
  year="2013",
  month="november",
  pages="1--5",
  type="conference paper"
}