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    Spectral and Energy Efficiency of IRS-Assisted MISO Communication with Hardware Impairments

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    Type
    Article
    Authors
    Zhou, Shaoqing
    Xu, Wei
    Wang, Kezhi
    Renzo, Marco Di
    Alouini, Mohamed-Slim cc
    KAUST Department
    Communication Theory Lab
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Electrical Engineering Program
    Date
    2020-04-28
    Preprint Posting Date
    2020-04-21
    Online Publication Date
    2020-04-28
    Print Publication Date
    2020-09
    Submitted Date
    2020-03-08
    Permanent link to this record
    http://hdl.handle.net/10754/662659
    
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    Abstract
    In this letter, we analyze the spectral and energy efficiency of an intelligent reflecting surface (IRS)-assisted multiple-input single-output (MISO) downlink system with hardware impairments. An extended error vector magnitude (EEVM) model is utilized to characterize the impact of radio-frequency (RF) impairments at the access point (AP) and phase noise is considered for the imperfect IRS. We show that the spectral efficiency is limited due to the hardware impairments even when the numbers of AP antennas and IRS elements grow infinitely large, which is in contrast with the conventional case with ideal hardware. Moreover, the performance degradation at high SNR is shown to be mainly affected by the AP hardware impairments rather than the phase noise of IRS. We further obtain in closed form the optimal transmit power for energy efficiency maximization. Simulation results are provided to verify the obtained results.
    Citation
    Zhou, S., Xu, W., Wang, K., Di Renzo, M., & Alouini, M.-S. (2020). Spectral and Energy Efficiency of IRS-Assisted MISO Communication with Hardware Impairments. IEEE Wireless Communications Letters, 1–1. doi:10.1109/lwc.2020.2990431
    Publisher
    Institute of Electrical and Electronics Engineers (IEEE)
    Journal
    IEEE Wireless Communications Letters
    DOI
    10.1109/LWC.2020.2990431
    arXiv
    2004.09854
    Additional Links
    https://ieeexplore.ieee.org/document/9079457/
    https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9079457
    http://arxiv.org/pdf/2004.09854
    ae974a485f413a2113503eed53cd6c53
    10.1109/LWC.2020.2990431
    Scopus Count
    Collections
    Articles; Electrical and Computer Engineering Program; Communication Theory Lab; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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