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Polese, M., Giordani, M., Mezzavilla, M., Rangan, S. and Zorzi, M. (2021) 6G Enabling Technologies. In: Wu, Y., Singh, S., Taleb, T., Roy, A., Dhillon, H.S., Kanagarathinam, M.R. and De, A., Eds., 6G Mobile Wireless Networks, Springer International Publishing, 25-41.
https://doi.org/10.1007/978-3-030-72777-2_3

has been cited by the following article:

• TITLE: A Transitional QoE Model Framework for 5G and beyond Networks

  AUTHORS: Vinaya Surya

  KEYWORDS: 5G, 6G, Quality of Experience (QoE), Transition Models, Context Aware Models, AI Optimised Model

  JOURNAL NAME: Journal of Computer and Communications, Vol.13 No.9, September 11, 2025

  ABSTRACT: The primary objective of this study is to propose and evaluate a multi-component Quality of Experience (QoE) transition model that integrates both network-level impairments and application-level performance metrics, and a time-dependent transition factor to provide a comprehensive framework for calculating Quality of Experience during the evolution from 5G to 6G. This research employs a multi-modelling framework for calculation of QoE by combining 6G and 5G quality scores through a time-dependent transition function, while the 6G component incorporates four sub-models: an enhanced Simplified E-model for network impairments, an AI-optimized Analytic Hierarchy Process model, application-specific quality metrics, and context-aware performance indicators, all integrated through dynamic weights that adapt throughout the transition period, with 5G QoE serving as the baseline for comparison. Experiments using a synthetic dataset of video streaming demonstrate a significant QoE improvement of 35.6% by factoring in component interactions. The adaptive transition function is found to be superior to the Sigmoid and other alternatives, as it accurately models real-world patterns during the deployment phase. Statistical validation of the model yielded a simple regression equation with an R2 of 0.963, providing a practical implementation guideline for network operators. Unlike the previous works that have relied exclusively on subjective user evaluations or are limited to QoS-to-QoE mappings, this paper offers a scalable, adaptable, and hybrid approach that reflects both technical service delivery and user-level experience. Future work will focus on incorporating real user feedback, complex datasets involving multiple services, and 6G-specific applications.