Sparse Adaptive Channel Estimation Based on lp-Norm-Penalized Affine Projection Algorithm

We propose an lp-norm-penalized affine projection algorithm (LP-APA) for broadband multipath adaptive channel estimations. The proposed LP-APA is realized by incorporating an lp-norm into the cost function of the conventional affine projection algorithm (APA) to exploit the sparsity property of the...

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Bibliographic Details
Main Authors: Yingsong Li, Wenxing Li, Wenhua Yu, Jian Wan, Zhiwei Li
Format: Article
Language:English
Published: Wiley 2014-01-01
Series:International Journal of Antennas and Propagation
Online Access:http://dx.doi.org/10.1155/2014/434659
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Summary:We propose an lp-norm-penalized affine projection algorithm (LP-APA) for broadband multipath adaptive channel estimations. The proposed LP-APA is realized by incorporating an lp-norm into the cost function of the conventional affine projection algorithm (APA) to exploit the sparsity property of the broadband wireless multipath channel, by which the convergence speed and steady-state performance of the APA are significantly improved. The implementation of the LP-APA is equivalent to adding a zero attractor to its iterations. The simulation results, which are obtained from a sparse channel estimation, demonstrate that the proposed LP-APA can efficiently improve channel estimation performance in terms of both the convergence speed and steady-state performance when the channel is exactly sparse.
ISSN:1687-5869
1687-5877