Energy Efficiency Concerns and Trends in Future 5G Network Infrastructures

被引:20
|
作者
Chochliouros, Ioannis P. [1 ]
Kourtis, Michail-Alexandros [2 ]
Spiliopoulou, Anastasia S. [1 ]
Lazaridis, Pavlos [3 ]
Zaharis, Zaharias [4 ]
Zarakovitis, Charilaos [2 ]
Kourtis, Anastasios [2 ]
机构
[1] Hellen Telecommun Org, Res Programs Sect, Athens 15124, Greece
[2] Natl Ctr Sci Res DEMOKRITOS NCSRD, Inst Informat & Telecommun, Athens 15310, Greece
[3] Univ Huddersfield, Dept Engn & Technol, Huddersfield HD1 3DH, W Yorkshire, England
[4] Aristotle Univ Thessaloniki, Dept Elect & Comp Engn, Thessaloniki 54124, Greece
基金
欧盟地平线“2020”;
关键词
5G; artificial intelligence (AI); energy consumption; energy efficiency; energy harvesting; energy savings; machine learning (ML); network slicing; resource allocation; smart metering; TECHNOLOGIES;
D O I
10.3390/en14175392
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Energy efficiency is a huge opportunity for both the developed and the developing world, and ICT will be the key enabler towards realising this challenge, in a huge variety of ways across the full range of industries. In the telecommunications space in particular, power consumption and the resulting energy-related pollution are becoming major operational and economical concerns. The exponential increases in network traffic and the number of connected devices both make energy efficiency an increasingly important concern for the mobile networks of the (near) future. More specifically, as 5G is being deployed at a time when energy efficiency appears as a significant matter for the network ability to take into account and to serve societal and environmental issues, this can play a major role in helping industries to achieve sustainability goals. Within this scope, energy efficiency has recently gained its own role as a performance measure and design constraint for 5G communication networks and this has identified new challenges for the future. In particular, the inclusion of AI/ML techniques will further enhance 5G's capabilities to achieve lower power consumption and, most importantly, dynamic adaption of the network elements to any sort of energy requirements, to ensure effective functioning.
引用
收藏
页数:14
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