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<p>As mobile networks grow to 5G, 6G, and beyond, uniform Handover Management (HOM) becomes important to ensure continuous connectivity and an improved user experience. This research investigates the complexities of HOM in next-generation (NZ) networks, concentrating on the problems and solutions for a smooth transition between various network types and standards. Device-to-Device (D2D) requires a fast, intelligent, and reliable handover (HO) decision system to deliver seamless mobility and ongoing service. With the exponential growth of Internet of Things (IoT) devices, D2D communication, augmented reality (AR), virtual reality (VR), and other technologies, efficiently managing the handover process which is critical to ensuring low latency, high data rates, and huge connectivity. The study investigates advanced methods such as machine learning (ML), long short-term memory (LSTM) model, and deep learning (DL) for improving handover management and reducing service disruptions. This paper is in accordance with sustainable development goals (SDGs), Goal 9: specifically, industry, innovation, and infrastructure, by linking the generations inside the network using creative HO techniques. Through improving digital infrastructure, encouraging innovation, and guaranteeing fair access to high-quality, reliable, and robust communication networks, the results seek to advance sustainable manufacturing. This in-depth examination of handover management for 5G, 6G, and beyond offers a thorough study that researchers, policymakers, and network operators working toward a sustainable digital future will find invaluable.</p>

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Intelligent device to device handover management techniques for 5G/6G and beyond

  • 期刊论文

  • 发表日期：

    2025年4月12日

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  • S M Topazal,
  • Shayla Islam,
  • Raenu A./L. Kolandaisamy,
  • Mohammad Kamrul Hasan,
  • Ahmad Fadzil Ismail,
  • Nur Hanis Sabrina Suhaimi,
  • Huda Saleh Abbas,
  • Muhammad Attique Khan,
  • Kamal Ali Alezabi

摘要

As mobile networks grow to 5G, 6G, and beyond, uniform Handover Management (HOM) becomes important to ensure continuous connectivity and an improved user experience. This research investigates the complexities of HOM in next-generation (NZ) networks, concentrating on the problems and solutions for a smooth transition between various network types and standards. Device-to-Device (D2D) requires a fast, intelligent, and reliable handover (HO) decision system to deliver seamless mobility and ongoing service. With the exponential growth of Internet of Things (IoT) devices, D2D communication, augmented reality (AR), virtual reality (VR), and other technologies, efficiently managing the handover process which is critical to ensuring low latency, high data rates, and huge connectivity. The study investigates advanced methods such as machine learning (ML), long short-term memory (LSTM) model, and deep learning (DL) for improving handover management and reducing service disruptions. This paper is in accordance with sustainable development goals (SDGs), Goal 9: specifically, industry, innovation, and infrastructure, by linking the generations inside the network using creative HO techniques. Through improving digital infrastructure, encouraging innovation, and guaranteeing fair access to high-quality, reliable, and robust communication networks, the results seek to advance sustainable manufacturing. This in-depth examination of handover management for 5G, 6G, and beyond offers a thorough study that researchers, policymakers, and network operators working toward a sustainable digital future will find invaluable.