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A Fast Adaptive Method for Subspace Based Blind Channel Estimation

Abstract : In this paper, a new fast adaptive blind channel estimation method is proposed using the subspace information from the correlation matrix. The algorithm is fully adaptive in the sense that both the subspace information and the optimization which leads to the channel estimation are computed adaptively. It is based on the recently proposed YAST subspace tracker which has been shown to outperform other methods both in terms of speed of convergence and computational complexity. A discussion on the convergence properties of the proposed algorithm is presented. We also propose a hybrid method which makes use of the YAST subspace tracker for initial fast convergence and the subspace information is then updated using the numerically stable OPAST subspace tracker.
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Submitted on : Monday, March 24, 2014 - 4:05:56 PM
Last modification on : Tuesday, March 8, 2022 - 5:46:03 PM
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  • HAL Id : hal-00945268, version 1



Jon Altuna, Bernie Mulgrew, Roland Badeau, Vicente Atxa. A Fast Adaptive Method for Subspace Based Blind Channel Estimation. Proc. of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2006, Toulouse, France. pp.1121--1124. ⟨hal-00945268⟩



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