Machine Learning Based Small Cell ON/OFF for Energy Efficiency in 5G Heterogeneous Networks
Author:
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,Computer Science Applications
Link
https://link.springer.com/content/pdf/10.1007/s11277-023-10383-7.pdf
Reference27 articles.
1. Soh, Y., Quek, T., & Kountouris, M. (2013). Energy efficient heterogeneous cellular networks. IEEE Journal on Selected Areas in Communications, 31(5), 840–850.
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3. Hong, E. K., Baek, J. Y., Jang, Y. O., Na, J. H., & Kim, K. S. (2018). QoS-guaranteed scheduling for small cell networks. ICT Express, 4(4), 175–180.
4. Guo, X., Niu, Z., Zhou, S., & Kumar, P. R. (2016). Delay-constrained energy-optimal base station sleeping control. IEEE Journal on Selected Areas in Communications, 34(5), 1073–1085.
5. Tung, L-P., Wang, L-C., & Chen, K-S. (2017). An interference-aware small cell on/off mechanism in hyper dense small cell networks. In 2017 International conference on computing, networking and communications (ICNC). IEEE.
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1. Landscape-enabled algorithmic design for the cell switch-off problem in 5G ultra-dense networks;Engineering Optimization;2024-06-19
2. IS3CQL : Intelligent sleep scheduling of small cells in high density 5G MIMO networks via incremental Deep Q learning optimizations;Journal of Information and Optimization Sciences;2024
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