Compressed channel estimation of two-way relay networks using mixed-norm sparse constraint

Guan Gui, Qun Wan, Fumiyuki Adachi

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


In this study, compressed channel estimation method for sparse multipath two-way relay networks is investigated. Conventional estimation methods, e.g., Least Square (LS) and Minimum Mean Square Error (MMSE), are based on the dense assumption of relay channel and cannot exploit channel sparsity which has been verified by lots of channel measurements. Unlike the previous methods, we propose a compressed channel estimation method by using bi-sparse constraint which can exploit the sparsity and hence provide significant improvements in MSE performance when compared with conventional LS-based estimation method. Simulation results confirm the superiority of proposed method.

Original languageEnglish
Pages (from-to)2279-2282
Number of pages4
JournalResearch Journal of Applied Sciences, Engineering and Technology
Issue number15
Publication statusPublished - 2012 Jul 17


  • Channel state information (CSI)
  • Compressive channel estimation
  • Compressive sensing
  • Sparse multipath channel
  • Two-way relay networks (TWRN)

ASJC Scopus subject areas

  • Computer Science(all)
  • Engineering(all)


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