Electric_Load_Profile_of_5G_Base_Station
Electric_Load_Profile_of_5G_Base_Station_in_Distribution_Systems_Based_on_Data_Flow_Analysis.pdf - Google Drive Loading
Electric_Load_Profile_of_5G_Base_Station_in_Distribution_Systems_Based_on_Data_Flow_Analysis.pdf - Google Drive Loading
In this paper, firstly, an energy consumption prediction model based on long and short-term memory neural network (LSTM) is established to accurately predict the daily load changes of base stations.
Numerical results demonstrate that the proposed model is effective and can be employed as an accurate representation of the 5G BS load profile for the analysis of load characteristics.
Abstract: This paper proposes an electric load demand model of the 5th generation (5G) base station (BS) in a distribution system based on data flow analysis. First, the electric load model of a 5G BS is
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 architectures.
To ensure the safe and stable operation of 5G base stations, it is essential to accurately predict their power load. However, current short-term prediction methods are rarely applied rationally
Electric_Load_Profile_of_5G_Base_Station_in_Distribution_Systems_Based_on_Data_Flow_Analysis.pdf - Google Drive Loading
In this paper, hourly electric load profiles of 5G BSs in residential, shopping, and office areas for future 5G application are simulated to compare and investigate their characteristics based
To ensure the safe and stable operation of 5G base stations, it is
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
PDF version includes complete article with source references. Suitable for printing and offline reading.