TY - JOUR
T1 - Energy Efficiency Concerns and Trends in Future 5G Network Infrastructures
AU - Chochliouros, Ioannis P.
AU - Kourtis, Michail Alexandros
AU - Spiliopoulou, Anastasia S.
AU - Lazaridis, Pavlos
AU - Zaharis, Zaharias
AU - Zarakovitis, Charilaos
AU - Kourtis, Anastasios
N1 - Funding Information:
The research leading to these results has been supported by the H2020 PALANTIR (?Practical Autonomous Cyberhealth for resilient SMEs & Microenterprises?) project (no. 883335), the H2020 SANCUS (?Analysis Software Scheme of Uniform Statistical Sampling, Audit and Defense Processes?) project (no. 952672), the H2020 5G?DRIVE (?HarmoniseD Research and trIals for serVice Evolution between EU and China?) project, (no. 814956) and the 5GENESIS H2020 5G?PPP (no. 815178).
Funding Information:
Funding: The research leading to these results has been supported by the H2020 PALANTIR (“Prac‐ tical Autonomous Cyberhealth for resilient SMEs & Microenterprises”) project (no. 883335), the H2020 SANCUS (“Analysis Software Scheme of Uniform Statistical Sampling, Audit and Defense Processes”) project (no. 952672), the H2020 5G‐DRIVE (“HarmoniseD Research and trIals for serVice Evolution between EU and China”) project, (no. 814956) and the 5GENESIS H2020 5G‐PPP (no. 815178).
Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021/9/1
Y1 - 2021/9/1
N2 - 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 spe-cifically, 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.
AB - 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 spe-cifically, 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.
KW - 5G
KW - Artificial Intelligence (AI)
KW - Energy consumption
KW - Energy efficiency
KW - Energy harvest-ing
KW - Energy savings
KW - Machine Learning (ML)
KW - Network slicing
KW - Resource allocation
KW - Smart metering
UR - http://www.scopus.com/inward/record.url?scp=85114088702&partnerID=8YFLogxK
U2 - 10.3390/en14175392
DO - 10.3390/en14175392
M3 - Article
AN - SCOPUS:85114088702
VL - 14
JO - Energies
JF - Energies
SN - 1996-1073
IS - 17
M1 - 5392
ER -