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Abstract
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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
Submitted: May 11, 2012
Accepted: June 08, 2012
Published: January 01, 2013 |
Abstract:
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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.
Key words: Mutual Incoherent Property (MIP), Orthogonal Matching Pursuit (OMP), Sensing Training Matrix (STM), sparse channel estimation, , ,
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Abstract
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Cite this Reference:
Guan Gui, Aihua Kuang, Ling Wang and Aihua Zhang, . MIP-Mitigated Sparse Channel Estimation Using Orthogonal Matching Pursuit Algorithm. Research Journal of Applied Sciences, Engineering and Technology, (01): 180-186.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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