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Fuzzy Logic Scheduler to Enhance User Equity in Cellular Networks
Abdul Khaliq and Ather Ashraf
This paper proposes a fuzzy-based user equity scheduler (FUES) to prioritize traffic according to a plan through a dynamic fuzzy inference system. The fuzzy logic engine uses fuzzy rule reasoning to define packet priorities. The priority is proportional to traffic types that are more likely to miss their Quality of Service (QoS) requirements and have poor channel conditions. Simulations are used to compare and analyze our proposed scheduler FUES with six other scheduling methods based on fairness and performance metrics. Overall, the proposed scheduler exhibits superior fairness and performance compared to other methods, although there may be specific scenarios where other methods do not excel. This suggests that proposed scheduler ‘FUES’ provides a more balanced scheduling approach.
Keywords: Cellular network, downlink scheduler, user equity, fuzzy inference system