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    Channel Estimation for Time-Varying MIMO Relay Systems

    228154_161779_TimeVaryingCh.pdf (189.4Kb)
    Access Status
    Open access
    Authors
    Chiong, Choo Wee Raymond
    Rong, Yue
    Xiang, Y.
    Date
    2015
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Chiong, C. and Rong, Y. and Xiang, Y. 2015. Channel Estimation for Time-Varying MIMO Relay Systems. IEEE Transactions on Wireless Communications. [In Press].
    Source Title
    IEEE Transactions on Wireless Communications
    DOI
    10.1109/TWC.2015.2459700
    ISSN
    15361276
    School
    Department of Electrical and Computer Engineering
    Funding and Sponsorship
    http://purl.org/au-research/grants/arc/DP110100736
    http://purl.org/au-research/grants/arc/DP110102076
    http://purl.org/au-research/grants/arc/DP140102131
    URI
    http://hdl.handle.net/20.500.11937/42563
    Collection
    • Curtin Research Publications
    Abstract

    In this paper, we investigate the channel estimation problem for multiple-input multiple-output (MIMO) relay communication systems with time-varying channels. The time-varying characteristic of the channels is described by the complexexponential basis expansion model (CE-BEM). We propose a superimposed channel training algorithm to estimate the individual first-hop and second-hop time-varying channel matrices for MIMO relay systems. In particular, the estimation of the secondhop time-varying channel matrix is performed by exploiting the superimposed training sequence at the relay node, while the first-hop time-varying channel matrix is estimated through the source node training sequence and the estimated second-hop channel. To improve the performance of channel estimation, we derive the optimal structure of the source and relay training sequences that minimize the mean-squared error (MSE) of channel estimation. We also optimize the relay amplification factor that governs the power allocation between the source and relay training sequences. Numerical simulations demonstrate that the proposed superimposed channel training algorithm for MIMO relay systems with time-varying channels outperforms the conventional two-stage channel estimation scheme.

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