Effective Sparse Channel Estimation for Wireless Multipath Systems
In real communication systems, most of the multipath channels tend to exhibit sparse behavior. By taking advantage of the sparsity, compressed sensing (CS) techniques is treated as an effective way to estimate the unknown channel frequency response. In this paper, an alternative Dantzig selector algorithm (ADS) based on CS is proposed. Simulations show that the proposed algorithm has better MSE performance compared with the traditional Least Square (LS) method and the Lasso algorithm on CS domain.
KeywordsChannel Estimation Channel State Information Compress Sense Training Sequence Sparse Signal
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