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    Distributed IRS With Statistical Passive Beamforming for MISO Communications

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    2009.06286.pdf
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    Description:
    Accepted Manuscript
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    Type
    Article
    Authors
    Gao, Yuwei cc
    Xu, Jindan cc
    Xu, Wei cc
    Ng, Derrick Wing Kwan cc
    Alouini, Mohamed-Slim cc
    KAUST Department
    Communication Theory Lab
    Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division
    Electrical and Computer Engineering Program
    Physical Science and Engineering (PSE) Division
    Date
    2021-02
    Permanent link to this record
    http://hdl.handle.net/10754/667545
    
    Metadata
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    Abstract
    Intelligent reflecting surface (IRS) has recently been identified as a prominent technology with the ability of enhancing wireless communication by dynamically manipulating the propagation environment. This letter investigates a multiple-input single-output (MISO) system deploying distributed IRSs. For practical considerations, we propose an efficient design of passive reflecting beamforming for the IRSs to exploit statistical channel state information (CSI) and analyze the achievable rate of the network taking into account the impact of CSI estimation error. The ergodic achievable rate is derived in a closed form, which provides insightful system design guidelines. Numerical results confirm the accuracy of the derived results and unveil the performance superiority of the proposed distributed IRS deployment over the conventional centralized deployment.
    Citation
    Gao, Y., Xu, J., Xu, W., Ng, D. W. K., & Alouini, M.-S. (2021). Distributed IRS With Statistical Passive Beamforming for MISO Communications. IEEE Wireless Communications Letters, 10(2), 221–225. doi:10.1109/lwc.2020.3024952
    Publisher
    Institute of Electrical and Electronics Engineers (IEEE)
    Journal
    IEEE Wireless Communications Letters
    DOI
    10.1109/lwc.2020.3024952
    arXiv
    2009.06286
    Additional Links
    https://ieeexplore.ieee.org/document/9200774/
    http://arxiv.org/pdf/2009.06286
    ae974a485f413a2113503eed53cd6c53
    10.1109/lwc.2020.3024952
    Scopus Count
    Collections
    Articles; Physical Science and Engineering (PSE) Division; Electrical and Computer Engineering Program; Communication Theory Lab; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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