A multi-protocol energy optimization method for an adaptable wireless MAC system through machine learning
Author:
Funder
Fundação de Amparo a Ciência e Tecnologia do Estado de Pernambuco
NVIDIA Academic Hardware Grant Program
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering
Link
https://link.springer.com/content/pdf/10.1007/s12243-023-01004-2.pdf
Reference39 articles.
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2. Hazra A, Adhikari M, Amgoth T, Srirama SN (2021) A comprehensive survey on interoperability for IIoT: taxonomy, standards, and future directions. ACM Comput Surveys (CSUR) 55(1):1–35. https://doi.org/10.1145/3485130
3. Kotstein S, Decker C (2019) Reinforcement learning for IoT interoperability. In: 2019 IEEE international conference on software architecture companion (ICSA-C), pp 11–18. https://doi.org/10.1109/ICSA-C.2019.00010
4. Sun H, Chen X, Shi Q, Hong M, Fu X, Sidiropoulos ND (2017) Learning to optimize: training deep neural networks for wireless resource management. In: Proc. of IEEE SPAWC, Sapporo, Japan. https://doi.org/10.48550/arXiv.1705.09412
5. Mao Q, Hu F, Hao Q (2018) Deep learning for intelligent wireless networks: a comprehensive survey. IEEE Commun Surveys Tuts 20(4):2595–2621. https://doi.org/10.1109/COMST.2018.2846401
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