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2013 (Vol. 5, Issue: 01)
Article Information:

MIP-Mitigated Sparse Channel Estimation Using Orthogonal Matching Pursuit Algorithm

Guan Gui, Aihua Kuang, Ling Wang and Aihua Zhang
Corresponding Author:  Guan Gui 

Key words:  Mutual Incoherent Property (MIP), Orthogonal Matching Pursuit (OMP), Sensing Training Matrix (STM), sparse channel estimation, , ,
Vol. 5 , (01): 180-186
Submitted Accepted Published
May 11, 2012 June 08, 2012 January 01, 2013

Wireless communication requires accurate Channel State Information (CSI) for coherent detection. Due to the broadband signal transmission, dominant channel taps are often separated in large delay spread and thus are exhibited highly sparse distribution. Sparse Multi-Path Channel (SMPC) estimation using Orthogonal Matching Pursuit (OMP) algorithm has took advantage of simplification and fast implementation. However, its estimation performance suffers from large Mutual Incoherent Property (MIP) interference in dominant channel taps identification using Random Training Matrix (RTM), especially in the case of SMPC with a large delay spread or utilizing short training sequence. In this study, we propose a MIP mitigation method to improve sparse channel estimation performance. To improve the estimation performance, we utilize a designed Sensing Training Matrix (STM) to replace with RTM. Numerical experiments illustrate that the improved estimation method outperforms the conventional sparse channel methods which neglected the MIP interference in RTM.
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  Cite this Reference:
Guan Gui, Aihua Kuang, Ling Wang and Aihua Zhang, 2013. MIP-Mitigated Sparse Channel Estimation Using Orthogonal Matching Pursuit Algorithm.  Research Journal of Applied Sciences, Engineering and Technology, 5(01): 180-186.
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ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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