Analyzing And Improving Quality of Service (Qos) In 5G Networks by Studying the Role of Simulation in Evaluating Response Time, Data Transmission, and Packet Loss

Authors

  • Mohamed Saleh khalifa Baghni Department of Electrical and Electronic Engineering, Higher Institute of Science and Technology, Nalut, Libya Author

    DOI:

    https://doi.org/10.64943/ajhas.2026.020252

    Keywords:

    5G networks, quality of service, simulation, resource management

    Abstract

    This study aimed to analyze and improve the Quality of Service (QoS) in 5G networks using simulation techniques. It examined the characteristics of these networks and identified the challenges they face, such as resource management, latency reduction, and ensuring service continuity. The study also evaluated the role of simulation in analyzing network performance under different operating conditions and measured key performance indicators (KPIs) such as response time, data transfer rate, and packet loss. Furthermore, it explored the potential of employing modern technologies like artificial intelligence (AI) and network slicing to enhance QoS. The study concluded that using simulation techniques effectively contributes to improving QoS in 5G networks. It enables the evaluation of network performance and the identification of bottlenecks before actual deployment. The results also demonstrated a positive relationship between improved resource management and QoS. Finally, the study found that integrating AI, network slicing, and dynamic spectrum management enhances network efficiency and resilience, leading to better performance that meets the demands of modern applications and increases network reliability.

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    Published

    2026-09-04

    Issue

    Section

    Articles

    How to Cite

    Mohamed Saleh khalifa Baghni. (2026). Analyzing And Improving Quality of Service (Qos) In 5G Networks by Studying the Role of Simulation in Evaluating Response Time, Data Transmission, and Packet Loss. Al-Imad Journal of Humanities and Applied Sciences (AJHAS), 2(2), 726-744. https://doi.org/10.64943/ajhas.2026.020252