PERTANIKA JOURNAL OF SCIENCE AND TECHNOLOGY

5G networks provide the Quality of Service (QoS) to various services, including Enhanced Mobile Broadband (eMBB), Ultra-Reliable Low-Latency Communications (URLLC), and massive Machine-Type Communications (mMTC) with different requirements. However, the existing 5G network deploys the static 5G QoS Identifiers (5QI) framework, which provides a basic level of services differentiation and supports the class-based prioritisation. The static 5QI fails to support the dynamic and user-centric QoS requirements. This paper reviews user-centric QoS provisioning schemes that focus on the Software-Defined Networks (SDN), Machine Learning (ML), and network slicing schemes. A structured evaluation methodology is used to analyse the existing works in terms of architecture, mechanisms, QoS metrics, scalability, and real-world feasibility. The reviews discover that SDN improves programmability and policy-based control, ML predicts the traffic adaptively, and network slicing provides service isolation. However, user-centric schemes can increase computational load, raising controller overhead and latency. This paper identifies the research gaps in the user-centric schemes related to scheme readiness, scalability, security, and heterogeneity. The paper also proposed a direction for deploying user-centric QoS schemes in real 5G networks that support future 5G enhancement that covers the adaptive, efficient, and personalised QoS provisioning.