Here we develop a large-scale data-driven framework to quantitatively assess the carbon emissions of 5G mobile networks in China, where over 60% of the global 5G base stations are implemented..
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This paper proposes a distribution network fault emergency power supply recovery strategy based on 5G base station energy storage. This strategy introduces Theil's entropy and modified Gini coef.
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Energy consumption growth of the fifth-generation (5G) mobile network infrastructure can be significant due to the increased traffic demand for a massive number of end-users with increasing traffic volum.
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Because it is estimated that in 5G, the base station's density is expected to exceed 40–50 BSs/ Km 2 . The energy consumption of the 5G network is driving attention and many world-leading network operators have launched alerts about the increased power consumption of the 5G mobile infrastructure .
However, the construction and operation of 5 G base stations face significant energy consumption challenges. Under full-load conditions, the power consumption of 5 G base stations is approximately 3–4 times that of 4 G base stations, which has a notable impact on energy consumption and environmental concerns (Zhang et al., 2020, Feng et al., 2012).
This restricts the potential use of the power models, as their validity and accuracy remain unclear. Future work includes the further development of the power consumption models to form a unified evaluation framework that enables the quantification and optimization of energy consumption and energy efficiency of 5G networks.
(1) Incorporation of Communication Caching Technology: The model includes communication caching technology, which fully leverages the delay-tolerant characteristics of communication flows, further enabling energy saving in 5 G base stations.
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