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    Superimposed Channel Training for Two-Way MIMO Relay Systems

    187234a.pdf (566.0Kb)
    Access Status
    Open access
    Authors
    Chiong, C.
    Rong, Yue
    Xiang, Y.
    Date
    2012
    Type
    Conference Paper
    
    Metadata
    Show full item record
    Citation
    Chiong, Choo W. R. and Rong, Yue and Xiang, Yong. 2012. Superimposed Channel Training for Two-Way MIMO Relay Systems, in Teng Joon Lim (ed), The 13th IEEE International Conference on Communication Systems, Nov 21 2012. Singapore: IEEE.
    Source Title
    Proceedings of The 13th IEEE International Conference on Communication Systems
    Source Conference
    The 13th IEEE International Conference on Communication Systems
    DOI
    10.1109/ICCS.2012.6406101
    Remarks

    © 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

    URI
    http://hdl.handle.net/20.500.11937/8501
    Collection
    • Curtin Research Publications
    Abstract

    Two-way relaying systems are known to be capable of providing higher spectral efficiency compared with one-way relaying systems. However, the channel estimation problem for two-way relaying systems becomes more complicated. In this paper, we propose a superimposed channel training scheme for two-way MIMO relay communication systems, where the individual channel information for users-relay and relay-users links are estimated. The optimal structure of the source and relay training sequences are derived when the mean-squared error (MSE) of channel estimation is minimized. We also optimize the power allocation between the source and relay training sequences to improve the performance of the algorithm. Numerical examples are shown to demonstrate the performance of the proposed channel training algorithm.

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