李亦卿

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Personal Information

  • Date of Birth:

    1993-06-01
  • Date of Employment:

    2022-07-12
  • School/Department:

    计算机学院
  • Gender:

    Female
  • Status:

    On-the-job
  • Teacher College:

    School of Computer Science

Other Contact Information:

  • Telephone:

  • Email:

Paper Publications

Current position: Home > Scientific Research > Paper Publications

Achievable Rate Maximization for Intelligent Reflecting Surface- Assisted Orbital Angular Momentum-Based Communication Systems

  • Release time:2022-09-01
  • Hits:
  • Impact Factor:  

    6.239
  • DOI number:  

    10.1109/TVT.2021.3089021
  • Journal:  

    IEEE Transactions on Vehicular Technology
  • Abstract:  

    The orbital angular momentum (OAM)-based communication systems may face severe transmission problems when the transmit and receive uniform circular array pairs are blocked. In this paper, a promising technique named intelligent reflecting surface (IRS) is proposed to help alleviate blockages and provide alternative line-of-sight links. To maximize the achievable rate of the IRS-assisted OAM communication systems, we optimize its transmit power allocation along with the IRS's reflecting phase shifts, and propose an alternative optimization-based algorithm to solve the resulting optimization problem with coupled variables and non-convex structure. Specifically, the proposed algorithm obtains a closed-form solution to the transmit power allocation by applying the majorization-minimization and ℓ1 -ball projection approaches, and obtain the locally optimal solution to the IRS's reflecting phase shifts by applying the weighted minimum mean square error-based fixed point iteration approach. Simulation results demonstrate the superiority of our proposed algorithm over existing baseline algorithms and also show its robust stability to the oblique angle errors.
  • Co-author:  

    zhangguangchi,cuimiao
  • First Author:  

    Li Yiqing
  • Correspondence Author:  

    jmiao
  • Discipline:  

    Engineering
  • First-Level Discipline:  

    Information and Communication Engineering
  • Document Type:  

    J
  • Volume:  

    70
  • Issue:  

    7
  • Page Number:  

    7277–7282
  • ISSN No.:  

    1939-9359
  • Translation or Not:  

    no
  • Date of Publication:  

    2021-07-01
  • Included Journals:  

    SCI
  • Links to published journals:  

    https://ieeexplore.ieee.org/document/9454339