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D2D communication would play a vital role in the next 6G wireless networks by enabling direct connection between devices, resulting in increased data speeds, less latency, and improved energy efficiency. Integrating machine learning methods into D2D communication has the benefit of optimizing resource allocation, interference control, and security assurance. In the context of 6G networks, this paper examines the convergence of ML and D2D communication and present approaches and identify domains are subject to critical evaluation for further inquiry.

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Role of Machine Leaning in D2D Communication in 6G

  • 会议论文

  • 发表日期：

    2025年

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  • Haneef Khan,
  • Malik Zaib Alam,
  • Mohammad Rafeek Khan,
  • Md Imran Alam,
  • Shams Tabrez Siddiuqi,
  • Abu Salim

摘要

D2D communication would play a vital role in the next 6G wireless networks by enabling direct connection between devices, resulting in increased data speeds, less latency, and improved energy efficiency. Integrating machine learning methods into D2D communication has the benefit of optimizing resource allocation, interference control, and security assurance. In the context of 6G networks, this paper examines the convergence of ML and D2D communication and present approaches and identify domains are subject to critical evaluation for further inquiry.