Natural gradient algorithm for neural networks applied to non-linear high power amplifiers

International Journal of Adaptive Control and Signal Processing

Volumn 16, Issue 8 SPEC., 2002, Pages 557-576

  Abdulkader, H ^a   Langlet, F ^a   Roviras, D ^a   Castanie, F ^a  

^a UNIVERSITÉ DE TOULOUSE   (France)

Author keywords

Equalization; High power amplifier; Identification; Natural gradient algorithm; Neural networks; Predistortion

Indexed keywords

COMPUTER SIMULATION; CONVERGENCE OF NUMERICAL METHODS; GRADIENT METHODS; INTERFERENCE SUPPRESSION; INTERSYMBOL INTERFERENCE; LEARNING ALGORITHMS; MULTILAYER NEURAL NETWORKS; POWER AMPLIFIERS; SATELLITES; SIGNAL DISTORTION; SIGNAL FILTERING AND PREDICTION; TRAVELING WAVE TUBES;

EQUALIZATION; HIGH POWER AMPLIFIERS; NATURAL GRADIENT ALGORITHM; PREDISTOTION;

MOBILE TELECOMMUNICATION SYSTEMS;

EID: 0036772455     PISSN: 08906327     EISSN: None     Source Type: Journal    
DOI: 10.1002/acs.725     Document Type: Article

References (36)

1. Davis, JA., Jedwab, J. Peak-to-mean power control in OFDM, golay complementary sequences, and reed-muller codes. IEEE, Transaction on Information Theory 1999; 45(7).
2. Nordberg, J., Abbas, M., Sven, N., Ingvar, C. Fractionally spaced adaptive equalization of S-UMTS mobile terminals. Wiley International Journal on Adaptive Control and Signal Processing, this issue.
3. Gutierrez, A., Ryan, W. E. Performance of adaptive Volterra equalizers on nonlinear satellite channels. Proceedings of ICC'96, Seattle, USA.
4. Benedetto, S., Biglieri, E., Daffara, R., Modeling and Performance Evaluation of Nonlinear Satellite Links-A volterra Series Approach. IEEE Transactions on Aerospace and Electronics Systems AES 1979; 15(4).
5. Haykin, S. Neural Networks: A Comprehensive Foundations, 2nd edn. Prentice-Hall: Upper Saddle River, NJ. 07458, 1999.
6. Balay, Palicot, J. Equalization of non-linear perturbations by a multilayer perceptron in satellite channel transmission. Proceedings of IEEE Globecom'94.
7. Chang, P., Wang, B. Adaptive decision feedback equalization for digital satellite channels using multilayer neural networks. IEEE Journal on selected areas in Communications 1995; 13(2).
8. Chen S., et al. Adaptive equalization of finite non-linear channels using multilayer perceptrons. Signal Processing 1990; 20:107-119.
9. Cha, I., Kassam, S.A., Channel equalization using adaptive complex radial basis function networks, IEEE Journal On selected areas in communications 1995; 13(1):122-131.
10. Chen, S., McLaughlin, S., Mulgrew, B. Complex-valued radial basis function network, Part I: network architecture and learning algorithms. Signal Processing 1994; 35:19-31.
11. Kohonen, T. Self-Organizing Maps. Springer: Berlin, 1995.
12. Bouchired, S., Roviras, D., Castanie, F. Equalization of satellite mobile channels with neural network techniques. Space Communications, Vol. 15 IOS Press: Boston, New York, 1998/1999.
13. Bouchired, S., Ibnkahla, M., Roviras, D., Castanie, F. Equalization of satellite UMTS channels using neural network devices. In Proceedings of IEEE, (ICASSP'1999), Phoenix, USA.
14. Benvenuto, N., Piazza, F. On the Complex Backpropagation Algorithm. IEEE Transactions on Signal Processing 1992; 40(4):967-969.
15. Murphy, C.D., Kassam, S.A. A Novel Linear/RBF Blind Equalizer for Nonlinear Channels: Proceedings of CISS'99, Baltimore, March 1999.
16. Bernardini, A., Fina, S.D. Analysis of different optimization criteria for IF predistortion in digital radio links with nonlinear amplifiers. IEEE Transactions on Communications 1997; 45(4).
17. Langlet, F., Ibnkahla, M., Castanie, F. Neural network hardware implementation: overview and applications to satellite communications. Proceedings of DSP'98, ESA, Nordwick, Holland, September 1998.
18. Ibnkahla, M., Sombrin, J., Castanie, F. Channel identification and failure detection in digital satellite communications. Globcom'96, London (UK), November 1996.
19. Pearson, RK., Ogunnaike, BA., Doyle, FJ. Identification of structurally constrained second order Volterra models. IEEE Transactions on SP 1996; 44(11).
20. Ibnkahla, M. Applications of neural networks to digital communications-survey. Signal processing 2000; 80(7).
21. Ibnkahla, M. Neural network predistortion technique for digital satellite communications. ICASSP'2000, Istanbul, Turkey
22. Ibnkahla, M., Bershad, NJ., Sombrin, J., Castanie, F. Neural networks for modeling nonlinear channels. IEEE Transactions on SP 1997; 45(7).
23. Ibnkahla, M., Bershad, N.J., Sombrin, J., Castanie, F. Neural network modeling and identification of non-linear channels with memory: algorithms, applications, and analytic models. IEEE Transactions on SP 1998; 46(5).
24. Amari, S. A universal theorem for learning curves. Neural Networks 1993; 6: 161-166.
25. Darken, C., Moody, J. Towards faster stochastic gradient search. In Moody, JE., Hanson, SJ., Lipmann, R.P., (eds), Advances in Neural Information Processing Systems, Vol. 4. Morgan Kufmann Publishers: San Mateo, CA. 1992.
26. Magoulas, GD., Vrahatis, MN., Androulakis, GS. Improving the convergence of the backpropagation algorithm using learning rate adaptation methods. Neural Computation 1999; 11.
27. LeCun, Y., Simard, P., Pearlmutter, B. Automatic Learning Rate Maximization by On-Line Estimation of the Hessian's Eigenvectors, vol. 5, In Hanson, SJ., Cowan, JD., Giles, CL., (eds.). Morgan Kaufman: San Mateo, CA; 156-163, 1993.
28. Haykin, S. Adaptive digital communication receivers. IEEE Communications Magazine December 2000.
29. Orret, GB., Leen, TK. Using curvature information for fast stochastic search. Advances in Neural Information Processing Systems vol. 9. MIT Press: Cambridge, MA.
30. Amari, SI. Natural gradient works efficiently in learning. Neural Computing 1998, 10:251-276.
31. Yang, H.H., Amari, S.I. The efficiency and the robustness of natural gradient descent learning rule. Advances in Neural Information Processing Systems, vol. 10. MIT Press: Cambridge, MA.
32. Yang, H.H., Amari, S.I. Training multi-layer perceptrons by natural gradient descent. In ICONIP prime 97 Proceedings. new Zealand.
33. Golub, G.H., Van Loan, C.F. Matrix computation, (2nd Edn.) The Johns Hopkins University Press: 1989.
34. Saleh, A. Frequency-independent and frequency-dependent nonlinear models of TWT amplifiers. IEEE Transactions on Communications COMM 29, 1981.
35. Guntsh, A., Ibnkahla, M., Losquadro, G., Mazella, M., Roviras, D., Timm, A. EU's R&D activities on the third generation mobile satellite systems (S-UMTS). IEEE Communication Magazine 1998; 36(2):104-110.
36. Langlet, F., Roviras, D., Mallet, A., Castanie, F. Mixed analog/digital implementation of MLP NN for predistortion. International joint conference on neural networks. Hi, USA, 2002.