Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/11776
Title: XGBoost-based QoE Prediction for Mobile Networks
Other Titles: Mobil Ağlar için XGBoost Tabanlı QoE Tahmini
Authors: Dayı, A.B.
Tuna, E.
Keywords: 6G
Decision Tree
Multimedia systems
Quality of experience
Quality of service
Wireless communication
XGBoost
Mobile telecommunication systems
Multimedia systems
Quality of service
6g
Complexes structure
Network applications
Quality of experience
Quality-of-service
Users perspective
Users' experiences
Users' satisfactions
Wireless communications
Xgboost
Decision trees
Publisher: Institute of Electrical and Electronics Engineers Inc.
Abstract: The increasing demand for advanced video-based services necessitates operators to ensure the most suitable network performance while also considering user satisfaction with the service. QoS provides significant insights on the network side to deliver satisfactory user experiences. On the other hand, QoE informs about how a given service is perceived from the user's perspective. The more advanced video-based services to be offered with the more complex structure of 6G increase the importance of mapping QoS to QoE. This paper presents an XGBoost-based method for predicting QoE based on UE-based, network-based, and application-based QoS measurements obtained from a real and live mobile network. The results indicate that XGBoost is an effective method for user experience estimation. © 2024 IEEE.
Description: Berdan Civata B.C.; et al.; Figes; Koluman; Loodos; Tarsus University
32nd IEEE Conference on Signal Processing and Communications Applications, SIU 2024 -- 15 May 2024 through 18 May 2024 -- Mersin -- 201235
URI: https://doi.org/10.1109/SIU61531.2024.10600936
https://hdl.handle.net/20.500.11851/11776
ISBN: 979-835038896-1
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

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