Computer Science

Computer Science ›› 2024, Vol. 51 ›› Issue (11A): 231200125-5.doi: 10.11896/jsjkx.231200125

• Network & Communication • Previous Articles     Next Articles

Deep Learning Based Joint Beamforming in Intelligent Reflecting Surface Enhanced WirelessCommunication Systems

CHEN Xiao1,4, ZHANG Quanhao2, SHI Jianfeng3,4, ZHU Jianyue3,4   

  1. 1 School of Artificial Intelligence/School of Future Technology,Nanjing University of Information Science and Technology,Nanjing 210044,China
    2 School of Computer Science,Nanjing University of Information Science and Technology,Nanjing 210044,China
    3 School of Electronic and Information Engineering,Nanjing University of Information Science and Technology,Nanjing 210044,China
    4 National Mobile Communications Research Laboratory,Southeast University,Nanjing 210096,China
  • Online:2024-11-16 Published:2024-11-13
  • About author:CHEN Xiao,born in 1993,Ph.D,lectu-rer.Her main research interests include massive multiple-input and multiple-output wireless communication systems,deep-learning based communication systems,beamforming design and channel estimation technologies.
    SHI Jianfeng,born in 1994,Ph.D,associate professor.His main research interests include 5G/6G communication wireless resource management,earth integrated networks,user-centered networks,beamforming theory and machine learning-based communication technologies.
  • Supported by:
    National Natural Science Foundation of China(62101273,62201274) and Natural Science Foundation of Jiangsu Province(BK20210641,BK20220439).

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Abstract: Intelligent reflecting surface(IRS),as one of the most potential technologies in the next-generation wireless communication,plays a significant role.However,the existing IRS-assisted multiple-input multiple-output(MIMO) systems face a challenging problem that the beamforming methods require high computational capabilities of the antennas.To address this challenge,a deep learning(DL)-based joint beamforming design has been proposed for IRS-aided multi-user MIMO communication systems aiming to maximize the sum data rate of all users.The proposed DL-based beamforming scheme utilizes convolutional neural network to jointly optimize digital beamforming at base station and reflection beamforming at IRS.The proposed DL-based beamforming method forecasts the essential features extracted from the beamforming matrix,which overcomes the challenge of direct prediction of beamforming matrix by neural network.This method significantly reduces the demand on the predictive capability of the neural network,and the trained and optimized beamforming designs are using online that can significantly reduce the real-time computational complexity.Simulation results demonstrate that the proposed beamforming design can achieve over 0.5~1bit/s/Hzdata rate improvement,which will be enhanced with the growth of user number.

Key words: Intelligent reflecting surface, Deep learning, Joint beamforming, Sum rate

CLC Number: 

  • TN929.5
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