Multiple Access Techniques for Intelligent and Multifunctional 6G: Tutorial, Survey, and Outlook

Clerckx, Bruno; Mao, Yijie; Yang, Zhaohui; Chen, Mingzhe; Alkhateeb, Ahmed; Liu, Liang; Qiu, Min; Yuan, Jinhong; Wong, Vincent W. S.; Montojo, Juan

doi:10.1109/jproc.2024.3409428

Cited by 12 publications

References 321 publications

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A Method for Sharing English Education Resources in Multiple Virtual Networks Based on 6G

2024

Int J Network Mgmt

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The rapid advancement of communication technologies, particularly in English language learning, is sharing education with the implementation of sixth‐generation (6G) networks, offering immersive and interactive learning experiences. The purpose of the research is to establish an advanced method for sharing English education resources across multiple virtual networks enabled by 6G technology. Traditional resource‐sharing systems lack the effectiveness and optimization requirement for large‐scale instructional assignments, especially in virtual settings with various user demands. To address this, the study proposed a novel Dynamic Tunicate Swarm Refined Graph Neural Networks (DTS‐RGNN) model to optimize resource allocation and improve the efficiency of resource sharing among educational tasks. The approach uses TSO for resource allocation scalable through 6G technology and GNN for task assignment according to the previous performances and interaction with the students to balance resource utilization. The experimental group performed writing (90%), sharing (91%), listening (85%), and reading (75%), finishing the task in 5.5 s at 1000 GB. Throughput increased by 5.0 GBps and resource utilization efficiency improved to (96%) and student outcomes showed high satisfaction (93%), retention (89%), and engagement (90%). The findings demonstrated the proposed method significantly improves the sharing of online English education resources, promoting more interactive and effective language learning experiences in virtual networks.

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