Sparse Multipath Channel Estimation Using Regularized Orthogonal Matching Pursuit Algorithm

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 138)

Abstract

Conventional linear channel estimation methods, such as the least squares, are unavailable in practical applications since all entries of the solution obtained by these methods were nonzeros. Using the sparsity of channel, several methods have been proposed, such as orthogonal matching pursuit (OMP) and convex program. However, OMP algorithm is unstable in the case of highly redundant dictionary and the convex program method is hard to implement due to its complexity. In this paper, a novel sparse channel estimate strategy named as regularized orthogonal matching pursuit algorithm is proposed. This algorithm combines the advantage of OMP algorithm and convex program methods. Numeral experiments demonstrate that the proposed algorithm is effective for the problem of sparse multi-path channel estimation.

Keywords

Sparse multi-path channel (SMPC) Regularized orthogonal matching pursuit (ROMP) Sparse approximation 

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Copyright information

© Springer-Verlag London Limited  2012

Authors and Affiliations

  1. 1.School of Computer Science and TechnologyHenan Polytechnic UniversityJiaozuoChina

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