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    Training Signal Design for Correlated Massive MIMO Channel Estimation

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    Type
    Article
    Authors
    Soltanalian, Mojtaba
    Naghsh, Mohammad Mahdi
    Shariati, Nafiseh
    Stoica, Petre
    Hassibi, Babak
    Date
    2017-02
    Permanent link to this record
    http://hdl.handle.net/10754/668541
    
    Metadata
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    Abstract
    In this paper, we propose a new approach to the design of training sequences that can be used for an accurate estimation of multi-input multi-output channels. The proposed method is particularly instrumental in training sequence designs that deal with three key challenges: 1) arbitrary channel and noise statistics that do not follow specific models, 2) limitations on the properties of the transmit signals, including total power, per-antenna power, having a constant-modulus, discrete-phase, or low peak-to-average-power ratio, and 3) signal design for large-scale or massive antenna arrays. Several numerical examples are provided to examine the proposed method.
    Citation
    Soltanalian, M., Naghsh, M. M., Shariati, N., Stoica, P., & Hassibi, B. (2017). Training Signal Design for Correlated Massive MIMO Channel Estimation. IEEE Transactions on Wireless Communications, 16(2), 1135–1143. doi:10.1109/twc.2016.2639485
    Sponsors
    This work was supported in part by the European Research Council, in part by the Swedish Research Council, in part by the U.S. National Science Foundation under Grant CNS-0932428, Grant CCF-1018927, Grant CCF-1423663, and Grant CCF-1409204, in part by Qualcomm Inc., in part by the NASA's Jet Propulsion Laboratory through the President and Director's Fund, in part by King Abdulaziz University, and in part by the King Abdullah University of Science and Technology.
    Publisher
    Institute of Electrical and Electronics Engineers (IEEE)
    Journal
    IEEE Transactions on Wireless Communications
    DOI
    10.1109/twc.2016.2639485
    Additional Links
    http://ieeexplore.ieee.org/document/7782871/
    ae974a485f413a2113503eed53cd6c53
    10.1109/twc.2016.2639485
    Scopus Count
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