中文

Journal of Applied Sciences ›› 2011, Vol. 29 ›› Issue (4): 347-352.doi: 10.3969/j.issn.0255-8297.2011.04.003

• Communication Engineering • Previous Articles     Next Articles

Compressed Sensing Based Sparse Channel Estimation in MIMO Systems

WANG Ni-na1, GUI Guan2;3, ZHANG Zhi1, TANG Tian1   

  1. 1. School of Information and Communication Engineering, Beijing University of Posts and Telecommunications,
    Beijing 100876, China
    2. School of Electronic and Engineering, University of Electronic Science and Technology of China,
    Chengdu 611731, China
    3. Department of Electrical and Communication Engineering, Graduate School of Engineering,
    Tohoku University, Sendai 980-8579, Japan
  • Received:2010-12-20 Revised:2011-05-16 Online:2011-07-30 Published:2011-07-30

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Abstract:

Abstract: In MIMO systems, channel state information (CSI) is necessary for coherent detection and channel
equalization at the receiver. Traditional channel estimation methods such as least squares (LS) and minimum
mean square error (MMSE) are based on the rich multipath assumption which leads to low frequency spectrum
utilization. This paper studies sparse channel estimation for single carrier MIMO systems. A novel method
based on compressed sensing is proposed by using sparsity, which can obtain accurate CSI with fewer pilots so
as to improve frequency spectrum utilization. Simulation and theoretical analysis show that the compressive
sampling matching pursuit (CoSaMP) estimation is the best choice for MIMO sparse multipath channel estimation.

Key words: compressed sensing (CS), sparse multipath, channel estimation, CoSAMP algorithm, multipleinput multiple-output (MIMO)

CLC Number: