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Cited by 780

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Green radio: radio techniques to enable energy-efficient wireless networks

Han, Congzheng, Harrold, Tim, Armour, Simon, Krikidis, Ioannis, Videv, Stefan, Grant, Peter M., Haas, Harald, Thompson, John S., Ku, Ivan, Wang, Cheng-Xiang, Le, Tuan Anh, Nakhai, M. Reza, Zhang, Jiayi, Hanzo, Lajos·2011·IEEE Communications Magazine

Abstract

Recent analysis by manufacturers and network operators has shown that current wireless networks are not very energy efficient, particularly the base stations by which terminals access services from the network. In response to this observation the Mobile Virtual Centre of Excellence (VCE) Green Radio project was established in 2009 to establish how significant energy savings may be obtained in future wireless systems. This article discusses the technical background to the project and discusses models of current energy consumption in base station devices. It also describes some of the most promising research directions in reducing the energy consumption of future base stations.

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Metadata

Authors
Han, C., Harrold, T., Armour, S., Krikidis, I., Videv, S., Grant, P. M., Haas, H., Thompson, J. S., Ku, I., Wang, C.-X., Le, T. A., Nakhai, M. R., Zhang, J., & Hanzo, L.
Venue
IEEE Communications Magazine
Published
2011-06
Volume
49
Issue
6
Pages
46-54
ISSN
  • 0163-6804 (ISSN-L)
  • 1558-1896
OpenAlex
W2134790395
Cited by
780
References
0
FWCI
66.62
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Green radio: radio techniques to enable energy-efficient wireless networks. https://app.cochat.ai/papers/10.1109/mcom.2011.5783984
The paper
Han, C., Harrold, T., Armour, S., Krikidis, I., Videv, S., Grant, P. M., Haas, H., Thompson, J. S., Ku, I., Wang, C.-X., Le, T. A., Nakhai, M. R., Zhang, J., & Hanzo, L. (2011). Green radio: radio techniques to enable energy-efficient wireless networks. IEEE Communications Magazine. https://doi.org/10.1109/mcom.2011.5783984

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.