Base station energy consumption

Measurements and Modelling of Base Station Power Consumption

Base stations represent the main contributor to the energy consumption of a mobile cellular network. Since traffic load in mobile networks significantly varies during a

Energy Consumption Modelling for 5G Radio Base Stations

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

Measurements and Modelling of Base Station Power Consumption under Real

Base stations represent the main contributor to the energy consumption of a mobile cellular network. Since traffic load in mobile networks significantly varies during a working or weekend

Energy consumption optimization of 5G base stations considering

An energy consumption optimization strategy of 5G base stations (BSs) considering variable threshold sleep mechanism (ECOS-BS) is proposed, which includes the initial

Power consumption based on 5G communication

This paper proposes a power control algorithm based on energy efficiency, which combines cell breathing technology and base station sleep technology to reduce base station energy

Comparison of Power Consumption Models for 5G Cellular Network Base

The first step when modeling the energy consumption of wireless communication systems is to derive models of the power consumption for the main system components, which

Measurements and Modelling of Base Station Power

Base stations represent the main contributor to the energy consumption of a mobile cellular network. Since traffic load in mobile networks significantly varies during a working or weekend

Comparison of Power Consumption Models for 5G Cellular

The first step when modeling the energy consumption of wireless communication systems is to derive models of the power consumption for the main system components, which

AI-based energy consumption modeling of 5G base stations: an energy

This paper demonstrates the energy consumption modeling of a BS considering its energy-saving sleep modes. We design a Deep Neural Network (DNN) based energy

Predictive Modelling of Base Station Energy

This study introduces a predictive modeling approach for base station energy consumption by combining Seasonal and Trend decomposition using Loess (STL) and Long Short-Term

Power Consumption Modeling of 5G Multi-Carrier Base

We demonstrate that this model achieves good estimation performance, and it is able to capture the benefits of energy saving when dealing with the complexity of multi-carrier base stations

Measurements and Modelling of Base Station

Base stations represent the main contributor to the energy consumption of a mobile cellular network. Since traffic load in mobile

Modelling the 5G Energy Consumption using Real-world

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

AI-based energy consumption modeling of 5G base stations: an

This paper demonstrates the energy consumption modeling of a BS considering its energy-saving sleep modes. We design a Deep Neural Network (DNN) based energy