Kamarul Ariffin, Noordin and Kaharudin, Dimyati and Effariza, Hanafi and Hafiz Muhammad Fahad, Noman and Nuha Adiba, Mohd Ridzuan (2025) Machine leaming-empowered mode selection for QoS improvement in D2D-assisted communication networks. In: The 2025 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT), 3-5 July 2025, Bali, Indonesia.
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Text (Conference paper)
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Abstract
Device-to-device (D2D) communication has the potential to enhance network efficiency in upcoming sixthgeneration (6G) wireless networks by enabling direct communication between users. However, in ultra-dense network environments, severe interference can degrade D2D performance, potentially leading to suboptimal Quality of Service (QoS) for some users. To address this challenge, we propose a machine learning-based approach for dynamic mode selection between D2D and cellular communication, aiming to improve network efficiency and ensure optimal user satisfaction. The proposed framework leverages clustering algorithms, including k-means and k-medoids, to segregate users based on channel gain, Signal-to-Interference-plus-Noise Ratio (SINR), and path loss. Furthermore, we employ binary classification models, including k-Nearest Neighbor (k-NN), Naive Bayes, and Support Vector Machine (SVM), to predict the optimal communication mode, using achievable data rate as the performance metric. Simulation results demonstrate that kmedoids clustering coupled with a cubic SVM classifier achieves the highest accuracy of 98.36%, leading to significant performance improvements. Moreover, k-medoids-based mode selection results in a 19.66% throughput increase and a 20.37% reduction in energy consumption, outperforming k-meansbased approaches
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Funders: | UNSPECIFIED |
| Additional Information: | Conference paper 2025 |
| Uncontrolled Keywords: | 6G networks; D2D communication; Energy efficiency; Machine Learning; Mode selection |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Faculty of Engineering |
| Depositing User: | Mr. Mohd Safri |
| Date Deposited: | 15 Aug 2025 01:20 |
| Last Modified: | 15 Aug 2025 01:20 |
| URI: | http://eprints.um.edu.my/id/eprint/51064 |
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