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    Abstract
2012 (Vol. 4, Issue: 15)
Article Information:

Compressed Channel Estimation of Two-Way Relay Networks Using Mixed-Norm Sparse Constraint

Guan Gui, Qun Wan and Fumiyuki Adachi
Corresponding Author:  Guan Gui 

Key words:  Channel State Information (CSI), compressive channel estimation, compressive sensing, sparse multipath channel, Two-Way Relay Networks (TWRN), ,
Vol. 4 , (15): 2279-2282
Submitted Accepted Published
October 07, 2011 November 16, 2011 August 01, 2012
Abstract:

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.
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  Cite this Reference:
Guan Gui, Qun Wan and Fumiyuki Adachi, 2012. Compressed Channel Estimation of Two-Way Relay Networks Using Mixed-Norm Sparse Constraint.  Research Journal of Applied Sciences, Engineering and Technology, 4(15): 2279-2282.
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ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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