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    Robust Transceiver Design for SWIPT DF MIMO Relay Systems With Time-Switching Protocol

    88750.pdf (1.635Mb)
    Access Status
    Open access
    Authors
    Lee, J.B.
    Rong, Yue
    Gopal, Lenin
    Chiong, Choo W.R.
    Date
    2021
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Lee, J.B. and Rong, Y. and Gopal, L. and Chiong, C.W.R. 2021. Robust Transceiver Design for SWIPT DF MIMO Relay Systems With Time-Switching Protocol. IEEE Systems Journal.
    Source Title
    IEEE Systems Journal
    DOI
    10.1109/JSYST.2021.3128678
    ISSN
    1932-8184
    Faculty
    Faculty of Science and Engineering
    School
    School of Elec Eng, Comp and Math Sci (EECMS)
    Remarks

    © 2021 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/20.500.11937/88926
    Collection
    • Curtin Research Publications
    Abstract

    In this article, we investigate a dual-hop simultaneous wireless information and power transfer decode-and-forward multiple-input and multiple-output relay communication system, in which the relay node harvests energy based on the radio frequency (RF) signal transmitted from the source node through the time-switching (TS) protocol to decode and forward the re-encoded information to the destination node. With the consideration of the channel estimation error, the joint optimization of the TS factor and source and relay precoding matrices is proposed with robustness against the channel state information mismatch to maximize the mutual information (MI) between the source and destination nodes. We derive the optimal structure of the source and relay precoding matrices to simplify the transceiver optimization problem under fixed and flexible power constraints. Numerical examples demonstrate that the proposed algorithms with robustness provide better MI performance compared to the nonrobust algorithm.

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