Thesis:

Designing a Fuzzy Logic-Based System for Handover Reduction in 5G Networks: Dynamic Classification of High-Speed ​​Users

Fifth-generation (5G) networks are designed to achieve high data rates, ultra-low latency, and massive user connectivity. However, in high-speed environments such as highways, the small size of cells causes users to experience a large number of handovers (HOs). This not only increases the signaling overhead of the network but can also degrade the Quality of Service (QoS) and Quality of Experience (QoE). In this research, a fuzzy logic-based method for mobility management in 5G networks is proposed. In the proposed approach, users are dynamically and softly classified based on their speed and position, and channel allocation is performed in a user-centric rather than cell-centric manner. To evaluate the proposed method, simulations were carried out in MATLAB using Monte Carlo iterations. The results show that the proposed method can significantly reduce the number of HOs and improve user classification accuracy. Therefore, the use of fuzzy logic can be an efficient solution for reducing signaling overhead and enhancing communication stability in high-mobility 5G applications, particularly in intelligent transportation systems (ITS).

Keywords: 5G Network, Handover, Fuzzy Logic, Mobility Management, High-Speed Users