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The mobile connections and the applications are developing unprecedentedly and maximizing the popularity of worldwide wireless service that highly maximized data traffic demands. This leads to mobility issues like Hand Over Ping-Pong (HOPP) and the Radio Link Failure (RLF). Though, these solutions maximize the amount of Handovers (Hos) that maximizes the unwanted rate of HO and dropped the probability of call. In this research, the cache-enabled Transfer Learning (C-TL) method for the handoff optimization in Heterogeneous Wireless Networks (HWO). The cache is included in the process of TL to enhance the performance of TL in handoff optimization. The C-TL method attained high performance in the handoff optimization and enhances the network stability. The C-TL method is evaluated with average probability of HOPP and RLF. The C-TL method attained less HHOP probability of 0.023 and RLF probability of 0.0085 which is better than existing methods like Fuzzy Logic Controller (FLC) with Weighted Function (WF).

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Cache-Enabled Transfer Learning for Handoff Optimization in Heterogeneous Wireless Networks

  • 会议论文

  • 发表日期：

    2026年

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  • Muntather Almusawi,
  • Ghazi Mohamad Ramadan,
  • Kasapolgu Kalpana

摘要

The mobile connections and the applications are developing unprecedentedly and maximizing the popularity of worldwide wireless service that highly maximized data traffic demands. This leads to mobility issues like Hand Over Ping-Pong (HOPP) and the Radio Link Failure (RLF). Though, these solutions maximize the amount of Handovers (Hos) that maximizes the unwanted rate of HO and dropped the probability of call. In this research, the cache-enabled Transfer Learning (C-TL) method for the handoff optimization in Heterogeneous Wireless Networks (HWO). The cache is included in the process of TL to enhance the performance of TL in handoff optimization. The C-TL method attained high performance in the handoff optimization and enhances the network stability. The C-TL method is evaluated with average probability of HOPP and RLF. The C-TL method attained less HHOP probability of 0.023 and RLF probability of 0.0085 which is better than existing methods like Fuzzy Logic Controller (FLC) with Weighted Function (WF).