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Priority-aware Radio Resource Scheduling for mMTC in 5G Networks – Balancing Efficiency and Fairness
by
Khunteta, Ajay
, Baheti, Prashant Kumar
in
5G mobile communication
/ Algorithms
/ Connectivity
/ Energy efficiency
/ Optimization
/ Polynomials
/ Priority scheduling
/ Quality of service
/ Radio networks
/ Resource allocation
/ Resource scheduling
/ Resource utilization
/ Scheduling
/ Simulation
/ Spectrum allocation
/ Uplinking
/ Wireless communications
2026
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Priority-aware Radio Resource Scheduling for mMTC in 5G Networks – Balancing Efficiency and Fairness
by
Khunteta, Ajay
, Baheti, Prashant Kumar
in
5G mobile communication
/ Algorithms
/ Connectivity
/ Energy efficiency
/ Optimization
/ Polynomials
/ Priority scheduling
/ Quality of service
/ Radio networks
/ Resource allocation
/ Resource scheduling
/ Resource utilization
/ Scheduling
/ Simulation
/ Spectrum allocation
/ Uplinking
/ Wireless communications
2026
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While trying to remove the title from your shelf something went wrong :( Kindly try again later!
Do you wish to request the book?
Priority-aware Radio Resource Scheduling for mMTC in 5G Networks – Balancing Efficiency and Fairness
by
Khunteta, Ajay
, Baheti, Prashant Kumar
in
5G mobile communication
/ Algorithms
/ Connectivity
/ Energy efficiency
/ Optimization
/ Polynomials
/ Priority scheduling
/ Quality of service
/ Radio networks
/ Resource allocation
/ Resource scheduling
/ Resource utilization
/ Scheduling
/ Simulation
/ Spectrum allocation
/ Uplinking
/ Wireless communications
2026
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Priority-aware Radio Resource Scheduling for mMTC in 5G Networks – Balancing Efficiency and Fairness
Journal Article
Priority-aware Radio Resource Scheduling for mMTC in 5G Networks – Balancing Efficiency and Fairness
2026
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Overview
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.
Publisher
Instytut Lacznosci - Panstwowy Instytut Badawczy (National Institute of Telecommunications)
Subject
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