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1 Journal of Telecommunications and Information Technology

1 2023

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Deep Learning-Powered Beamforming for 5G Massive MIMO Systems

Bendjillali Ridha Ilyas, Bendelhoum Mohammed Sofiane, Tadjeddine Ali Abderrazak, Kamline Miloud

Journal of Telecommunications and Information Technology

2023

nr 4

38--45

In this study, a ResNeSt-based deep learning approach to beamforming for 5G massive multiple-input multipleoutput (MIMO) systems is presented. The ResNeSt-based deep learning method is harnessed to simplify and optimize the beamforming process, consequently improving performance and efficiency of 5G and beyond communication networks. A study of beamforming capabilities has revealed potential to maximize channel capacity while minimizing interference, thus eliminating inherent limitations of the traditional methods. The proposed model shows superior adaptability to dynamic channel conditions and outperforms traditional techniques across various interference scenarios.