Effective Sparse Channel Estimation for Wireless Multipath Systems

  • Nina Wang
  • Tian Tang
  • Zhi Zhang
  • Jun Jiang
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 127)


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.


Channel Estimation Channel State Information Compress Sense Training Sequence Sparse Signal 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Key Laboratory of Universal Wireless Communications, Ministry of EducationBeijing University of Posts and TelecommunicationsBeijingChina

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