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Proceedings Paper

Online Levenberg-Marquardt algorithm for digital predistortion based on direct learning and indirect learning architectures
Author(s): Limin Chen; Yin Liang; Guojin Wan
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Paper Abstract

An regularization approach is introduced into the online identification of inverse model for predistortion. It is based on a modified backpropagation Levenberg-Marquardt algorithm with sliding window. Adaptive predistorter with feedback was identified respectively based on direct learning and indirect learning architectures. Length of the sliding window was discussed. Compared with the Recursive Prediction Error Method (RPEM) algorithm and Nonlinear Filtered Least-Mean-Square (NFxLMS) algorithm, the algorithm is tested by identification of infinite impulse response Wiener predistorter. It is found that the proposed algorithm is much more efficient than either of the other techniques. The values of the parameters are also smaller than those extracted by the ordinary least-squares algorithm since the proposed algorithm constrains the L2-norm of the parameters.

Paper Details

Date Published: 14 May 2012
PDF: 7 pages
Proc. SPIE 8334, Fourth International Conference on Digital Image Processing (ICDIP 2012), 833402 (14 May 2012); doi: 10.1117/12.945918
Show Author Affiliations
Limin Chen, Nanchang Univ. (China)
Yin Liang, Nanchang Univ. (China)
Guojin Wan, Nanchang Univ. (China)

Published in SPIE Proceedings Vol. 8334:
Fourth International Conference on Digital Image Processing (ICDIP 2012)
Mohamed Othman; Sukumar Senthilkumar; Xie Yi, Editor(s)

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