Feature-Based Deep Neural Networks for Short-Term Prediction of WiFi Channel Occupancy Rate



Al-Tahmeesschi, Ahmed, Umebayashi, Kenta, Iwata, Hiroki, Lehtomaki, Janne and Lopez-Benitez, Miguel ORCID: 0000-0003-0526-6687
(2021) Feature-Based Deep Neural Networks for Short-Term Prediction of WiFi Channel Occupancy Rate. IEEE ACCESS, 9. 85645 - 85660.

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Item Type: Article
Uncontrolled Keywords: Predictive models, Neural networks, Deep learning, Autoregressive processes, Resource management, Wireless fidelity, Time series analysis, 5G, deep neural networks, explainable AI, GRU, LSTM, occupancy rate, SHAP, short-term prediction, spectrum awareness, WiFi
Divisions: Faculty of Science and Engineering > School of Electrical Engineering, Electronics and Computer Science
Depositing User: Symplectic Admin
Date Deposited: 01 Jun 2021 14:46
Last Modified: 05 Oct 2021 14:10
DOI: 10.1109/ACCESS.2021.3088423
Related URLs:
URI: https://livrepository.liverpool.ac.uk/id/eprint/3124744