Competitive demand for network resources has only increased during the emergence of 5G next generation cellular technology. As video streaming accounts for an overwhelming percentage of this demand, the importance of considering the often-neglected Quality of Experience (QoE) metric is essential to ensure network resources are allocated in the most effective manner. Generalized network throughput metrics are insufficient in capturing the full human experience as increased data rates do not necessarily translate to improvements in user utility. Our study compares the efficacy of existing network allocation algorithms and proposes new approaches to 5G network resource allocation schemes using a more inclusive snapshot of user demand. We provide recommendations on which approach provides the highest QoE performance and suggestions for future network-side improvements. We further propose a QoE-driven network resource allocation (QENA) algorithm that shows a 20% improvement in overall average QoE across a large set of heterogeneous users.


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    Title :

    QoE-Analysis of 5G Network Resource Allocation Schemes for Competitive Multi-User Video Streaming Applications


    Contributors:


    Publication date :

    2023-06-01


    Size :

    1043670 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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