A data-driven framework has been developed to assess the carbon emissions of mobile networks in China, revealing that the launch of 5G networks leads to a decline in carbon efficiency. A deep reinforcement learning algorithm, DeepEnergy, is proposed to increase the carbon efficiency of mobile networks and reduce carbon emissions.
This is a preview of subscription content, access via your institution
Relevant articles
Open Access articles citing this article.
-
Ultra-thin flexible rectenna integrated with power management unit for wireless power harvester/charging of smartwatch/wristband
Scientific Reports Open Access 28 March 2024
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 digital issues and online access to articles
$119.00 per year
only $9.92 per issue
Buy this article
- Purchase on Springer Link
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
References
I, C.-L., Han, S. & Bian, S. Energy-efficient 5G for a greener future. Nat. Electron. 3, 182–184 (2020). This paper raises concerns about the energy consumption of 5G networks.
Ding, Y. et al. Carbon emissions and mitigation potentials of 5G base station in China. Resour. Conserv. Recycl. 182, 106339 (2022). This paper discusses the carbon emissions of a single 5G base station from a whole life-cycle perspective.
Yang, Y. et al. Mean field multi-agent reinforcement learning. In Proc. 35th International Conference on Machine Learning (eds Dy, J. & Krause, A.) 5571–5580 (PMLR, 2018). This paper proposes a mean field multi-agent reinforcement learning algorithm.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
This is a summary of: Li, T. et al. Carbon emissions of 5G mobile networks in China. Nat. Sustain. https://doi.org/10.1038/s41893-023-01206-5 (2023).
Rights and permissions
About this article
Cite this article
Artificial intelligence for reducing the carbon emissions of 5G networks in China. Nat Sustain 6, 1522–1523 (2023). https://doi.org/10.1038/s41893-023-01208-3
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41893-023-01208-3
