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  • Research Article
  • Open Access

Adaptive Predistortions Based on Neural Networks Associated with Levenberg-Marquardt Algorithm for Satellite Down Links

EURASIP Journal on Wireless Communications and Networking20082008:132729

https://doi.org/10.1155/2008/132729

  • Received: 1 March 2008
  • Accepted: 28 June 2008
  • Published:

Abstract

This paper presents adaptive predistortion techniques based on a feed-forward neural network (NN) to linearize power amplifiers such as those used in satellite communications. Indeed, it presents the suitable NN structures which give the best performances for three satellite down links. The first link is a stationary memoryless travelling wave tube amplifier (TWTA), the second one is a nonstationary memoryless TWT amplifier while the third is an amplifier with memory modeled by a memoryless amplifier followed by a linear filter. Equally important, it puts forward the studies concerning the application of different NN training algorithms in order to determine the most prefermant for adaptive predistortions. This comparison examined through computer simulation for 64 carriers and 16-QAM OFDM system, with a Saleh's TWT amplifier, is based on some quality measure (mean square error), the required training time to reach a particular quality level, and computation complexity. The chosen adaptive predistortions (NN structures associated with an adaptive algorithm) have a low complexity, fast convergence, and best performance.

Keywords

  • Power Amplifier
  • Adaptive Algorithm
  • Satellite Communication
  • Linear Filter
  • OFDM System

Publisher note

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Authors’ Affiliations

(1)
Unité de Recherche 6'Tél/Sup'Com, route de Raoued Km 3.5, 2083 Ariana, Tunisia
(2)
ENSEEIHT, Laboratoire IRIT 2, rue C. Camichel, BP 7122, 31071 Toulouse Cedex 7, France

Copyright

© Rafik Zayani et al. 2008

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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