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Energy Efficiency Concerns and Trends in Future 5G Network Infrastructures

doi: 10.3390/en14175392
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.
- University of Huddersfield United Kingdom
- University of Huddersfield United Kingdom
- Πανεπιστήμιο Κρήτης – Τμήμα Βιολογίας Greece
- Aristotle University of Thessaloniki Greece
- National Centre of Scientific Research Demokritos Greece
energy harvesting, Technology, T, artificial intelligence (AI), energy savings, 5G; artificial intelligence (AI); energy consumption; energy efficiency; energy harvesting; energy savings; machine learning (ML); network slicing; resource allocation; smart metering, energy consumption, 5G, energy efficiency
energy harvesting, Technology, T, artificial intelligence (AI), energy savings, 5G; artificial intelligence (AI); energy consumption; energy efficiency; energy harvesting; energy savings; machine learning (ML); network slicing; resource allocation; smart metering, energy consumption, 5G, energy efficiency
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).36 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 1%
