Table of Contents
International Journal of Microwave Science and Technology
Volume 2011, Article ID 468497, 5 pages
http://dx.doi.org/10.1155/2011/468497
Research Article

A Two-Step Identification Approach for Twin-Box Models of RF Power Amplifier

1Department of Engineering Physics, Tsinghua University, Beijing 100084, China
2Institute of Electronic Engineering, China Academy of Engineering Physics, Mianyang 621900, China

Received 21 April 2011; Revised 11 July 2011; Accepted 19 July 2011

Academic Editor: Paolo Colantonio

Copyright © 2011 You-Jiang Liu et al. 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.

Linked References

  1. D. Schreurs, M. O'Droma, A. A. Goacher, and M. Gadringer, RF Power Amplifier Behavioral Modeling, Cambridge University Press, New York, NY, USA, 2008.
  2. H. Ku and J. S. Kenney, “Behavioral modeling of nonlinear RF power amplifiers considering memory effects,” IEEE Transactions on Microwave Theory and Techniques, vol. 51, no. 12, pp. 2495–2504, 2003. View at Publisher · View at Google Scholar · View at Scopus
  3. M. Isaksson, D. Wisell, and D. Rönnow, “A comparative analysis of behavioral models for RF power amplifiers,” IEEE Transactions on Microwave Theory and Techniques, vol. 54, no. 1, pp. 348–359, 2006. View at Publisher · View at Google Scholar · View at Scopus
  4. F. M. Ghannouchi and O. Hammi, “Behavioral modeling and predistortion,” IEEE Microwave Magazine, vol. 10, no. 7, pp. 53–64, 2009. View at Publisher · View at Google Scholar · View at Scopus
  5. P. N. Landin, M. Isaksson, and P. Händel, “Parameter extraction and performance evaluation method for increased performance in RF power amplifier behavioral modeling,” International Journal of RF and Microwave Computer-Aided Engineering, vol. 20, no. 2, pp. 200–208, 2010. View at Publisher · View at Google Scholar · View at Scopus
  6. T. Ogunfunmi, Adaptive Nonlinear System Identification: The Volterra and Wiener Model Approaches, Springer, New York, NY, USA, 2007.
  7. F. Guo, A new identification method for Wiener and Hammerstein Systems, Doctor thesis, Universität Karlsruhe, Berlin, Germany, 2004.
  8. L. Ljung, “Convergence analysis of parametric identification methods,” IEEE Transactions on Automatic Control, vol. 23, no. 5, pp. 770–783, 1978. View at Google Scholar · View at Scopus
  9. P. L. Gilabert, G. Montoro, and E. Bertran, “On the wiener and hammerstein models for power amplifier predistortion,” in Proceedings of the Asia-Pacific Microwave Conference, pp. 1–4, 2005.
  10. J. Liu, W. Xu, and J. Sun, “Nonlinear system identification of hammerstein and wiener model using swarm intelligence,” in Proceedings of the IEEE International Conference on Information Acquisition '06, pp. 1219–1223, 2006.
  11. H. W. Kang, Y. S. Cho, and D. H. Youn, “Adaptive precompensation of wiener systems,” IEEE Transactions on Signal Processing, vol. 46, no. 10, pp. 2825–2829, 1998. View at Google Scholar · View at Scopus