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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).
Accurate energy consumption modeling is essential for developing energy-efficient strategies, enabling operators to optimize resource uti-lization while maintaining network performance. To address this, we propose a novel deep learning model for 5G base station energy consumption estimation based on a real-world dataset.
(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.
The explosive growth of mobile data traffic has resulted in a significant increase in the energy consumption of 5G base stations (BSs).
Simulation results demonstrated the effectiveness of the proposed technology in reducing energy consumption and improving energy efficiency in 5G base station networks.
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Reports on the Increasing Energy Consumption of Wireless Systems and Digital Ecosystem The more we use wireless electronic devices, the more energy we will consume. 5G will exponentially increase
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An energy consumption optimization strategy of 5G base stations (BSs) considering variable threshold sleep mechanism (ECOS-BS) is proposed, which includes the initial matching
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In today''s 5G era, the energy efficiency (EE) of cellular base stations is crucial for sustainable communication. Recognizing this, Mobile Network Operators are actively prioritizing EE for both
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Importantly, this study item indicates that new 5G power consumption models are needed to accurately develop and optimize new energy saving solutions, while also considering the
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At present, 5G mobile traffic base stations in energy consumption accounted for 60% ~ 80%, compared with 4G energy consumption increased three times. In the future, high-density
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Change Log This document contains Version 1.0 of the ITU-T Technical Report on “Smart Energy Saving of 5G Base Station: Based on AI and other emerging technologies to forecast and
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To further explore the energy-saving potential of 5 G base stations, this paper proposes an energy-saving operation model for 5 G base stations that incorporates communication caching and
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Keywords—5G, base station, energy saving, AI I. NTRODUCTION With the development of mobile com munication network, the total energy consumption of operators continues to
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Accurate energy consumption modeling is essential for developing energy-efficient strategies, enabling operators to optimize resource uti-lization while maintaining network
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