In response to the energy-saving needs of 5G base stations, this article combines IoT technology, artificial intelligence technology, and thermal design technology to conduct research on energy
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To reduce the extra power consumption due to frequent sleep mode switching of base stations, a sleep mode switching decision algorithm is proposed. The algorithm reduces unnecessary
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For the first subproblem, we develop an efficient branch-and-bound (B&B) algorithm to determine the optimal BS on/off state and traffic distribution.
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In response to the requirement of an intelligent and self-adaptive energy saving solution, artificial intelligence (AI) and big data technology are introduced to form a more precise energy saving
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The traditional power-saving effect evaluation scheme of Active Antenna Unit (AAU) is complicated, leading to errors in the final evaluation results possibly. This paper proposes a
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imize energy consumption in cellular network base stations. In this context we organize this paper in three parts: first provide a review of recent pre. iction techniques, dataset used, and employed
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The phrase “communication batteries” is often applied broadly, sometimes including handheld radios, emergency devices, or general-purpose backup batteries. In practice, when
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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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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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