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
Power consumption models for base stations are briefly discussed as part of the development of a model for life cycle assessment. An overview of relevant base station power
To address this, we propose a novel deep learning model for 5G base station energy consumption estimation based on a real-world dataset. Unlike existing methods, our approach integrates
In this thesis linear regression is compared with the gradient boosted trees method and a neural network to see how well they are able to predict energy consumption from field data of 5G
This technical report explores how network energy saving technologies that have emerged since the 4G era, such as carrier shutdown, channel shutdown, symbol shutdown etc., can be
Abstract: The energy consumption of 5G networks is one of the pressing concerns in green communications. Recent research is focused towards energy saving techniques of
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
Thus, the objective is to develop a machine learning model to estimate the energy consumption of 5G base stations, taking into account different engineering configurations, traffic conditions,
automation, health, etc. The main idea behind 5G is to minimize total network energy consumption, despite increased trafic and service expansion due to its use for these verticals
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
PDF version includes complete article with source references.
Get technical specifications, European subsidy information, and ROI analysis tools for peak shaving and container energy storage solutions.
ul. Technologii 15, Park Przemysłowy
geochojnice.pl, Poland
Office: +48 22 525 6683
Technical: +48 189 486 173
Monday - Friday: 8:00 AM - 6:00 PM CET