Priority-aware Radio Resource Scheduling for mMTC in 5G Networks - Balancing Efficiency and Fairness

Efficient and fair resource allocation for massive machine-type communication remains a significant challenge in 5G New Radio networks due to the diverse quality of service requirements and dynamic traffic patterns. This paper proposes a priority-aware uplink scheduling (PAUS) algorithm that jointly considers channel quality, 5G QoS identifier, packet aging, and fairness in physical resource block allocation, while simultaneously mitigating starvation of low-priority user equipment. The algorithm utilizes a composite fitness function to implement binary integer optimization for uplink scheduling, supported by heuristic resource assignment to ensure scalability. Simulation results demonstrate that the PAUS algorithm achieves an improved balance between throughput, resource utilization, delay, priority satisfaction, and fairness compared to baseline schedulers with polynomial-time complexity.