Scheduling allocation in 5G slicing networks utilizing weighted exponential and logarithmic functions to improve QoS

Offering media-rich services, such as streaming videos, for emergency services requires compliance with reliability standards. The deployment of fifth-generation (5G) networks enables a wide range of services and applications with diverse Quality of Service (QoS) requirements. Supporting heterogeneous performance and migrating vital services to 5G networks pose significant challenges for emergency service providers in maintaining QoS. To address this, schedulers allocate resources to various traffic types in a QoS- and channel state-aware manner. The exponential function scheduling method (EXP RULE) is a well-established approach; however, it requires optimization to reduce packet loss rate and latency. This study proposes the Hybrid Weighted Exponential and Logarithmic Rule (HWEL RULE), which enhances EXP RULE by integrating weighted logarithmic functions to improve QoS metrics in 5G slicing networks. Operating within a Fog Radio Access Network (F-RAN) framework with Network Functions Virtualization (NFV), HWEL RULE dynamically allocates Baseband Unit (BBU) resources to Ultra-Reliable Low-Latency Communications (URLLC), Enhanced Mobile Broadband (eMBB), and Massive Machine-Type Communications (mMTC). Using LTE-Sim simulations, HWEL RULE demonstrates up to a 30.06% reduction in packet loss rate, 21% lower latency for video traffic, 23.5% lower latency for VoIP, 8.6% higher throughput, and 1.2% improved fairness compared to EXP RULE. This incremental enhancement ensures compatibility with existing 5G architectures while significantly improving real-time traffic performance.