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    A worst-case robust MMSE transceiver design for nonregenerative MIMO relaying

    197279_197279.pdf (2.253Mb)
    Access Status
    Open access
    Authors
    Shen, H.
    Wang, J.
    Xu, W.
    Rong, Yue
    Zhao, C.
    Date
    2014
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Shen, Hong and Wang, Jiaheng and Xu, Wei and Rong, Yue and Zhao, Chunming. 2014. A worst-case robust MMSE transceiver design for nonregenerative MIMO relaying. IEEE Transactions on Wireless Communications. 13 (2): pp. 695-709.
    Source Title
    IEEE Transactions on Wireless Communications
    DOI
    10.1109/TWC.2013.120413.130009
    ISSN
    15361276
    Remarks

    Copyright © 2014 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/20.500.11937/13269
    Collection
    • Curtin Research Publications
    Abstract

    Transceiver designs have been a key issue in guaranteeing the performance of multiple-input multiple-output (MIMO) relay systems, which are, however, often subject to imperfect channel state information (CSI). In this paper, we aim to design a robust MIMO transceiver for nonregenerative MIMO relay systems against imperfect CSI from a worst-case robust perspective. Specifically, we formulate the robust transceiver design, under the minimum mean-squared error (MMSE) criterion, as a minimax problem. Then, by decomposing the minimax problem into two subproblems with respect to the relay precoder and destination equalizer, respectively, we show that the optimal solution to each subproblem has a favorable channel-diagonalizing structure under some mild conditions. Based on this finding, we transform the two complex-matrix subproblems into their equivalent scalar forms, both of which are proven to be convex and can be efficiently solved by our proposed methods. We further propose an alternating algorithm to jointly optimize the precoder and equalizer that only requires scalar operations. Finally, the effectiveness of the proposed robust design is verified by simulation results.

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