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    Multicasting MIMO Relay Optimization Based on Min-Max MSE Criterion

    187233_187233.pdf (117.3Kb)
    Access Status
    Open access
    Authors
    Khandaker, Muhammad
    Rong, Yue
    Date
    2012
    Type
    Conference Paper
    
    Metadata
    Show full item record
    Citation
    Khandaker, Muhammad R. A. and Rong, Yue. 2012. Multicasting MIMO Relay Optimization Based on Min-Max MSE Criterion, in Teng Joon Lim (ed), The 13th International Conference on Communication Systems IEEE ICCS, Nov 21-23 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.2012.6406100
    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/20.500.11937/36060
    Collection
    • Curtin Research Publications
    Abstract

    In this paper, we consider a multicasting multiple-input multiple-output (MIMO) relay system where the transmitter multicasts a common message to multiple receivers with the aid of a relay node, all equipped with multiple antennas. Given the power constraints at the source and the relay nodes, we aim at minimizing the maximal mean-squared error (MSE) of the signal waveform estimation among the destination nodes through joint source, relay, and receiver matrices optimization. We provide a low complexity solution to this highly nonconvex optimization problem. In particular, we show that under the (moderately) high signal-to-noise ratio (SNR) assumption, the joint source and relay optimization problem can be solved using standard semidefinite programming (SDP) technique. Numerical simulations provided demonstrate the effectiveness of the proposed algorithm.

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