Optimal energy-saving operation strategy of 5G base station with
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
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
Our study introduces a communications and power coordination planning (CPCP) model that encompasses both distributed energy resources and base stations to improve
Therefore, it is reasonable to focus on the power consumption of the base stations first, while other aspects such as virtualization of compute in the 5G core or the energy
5G base stations use high power consumption and high RF signals, which require more signal processing for digital and
Our study introduces a communications and power coordination planning (CPCP) model that encompasses both distributed energy resources and
To achieve low latency, higher throughput, larger capacity, higher reliability, and wider connectivity, 5G base stations (gNodeB) need to be deployed in mmWave. Since mmWave
Although base stations (BSs) are inherently energy-intensive, their energy consumption can be optimized by dynamically disabling certain hardware components based on traffic load.
It is shown that when the 5G BS utilizes a dual power supply mode, combining mains electricity and ES backup, the power supply reliability can reach as high as 99%.
5G base stations use high power consumption and high RF signals, which require more signal processing for digital and electromechanical units, and also put greater pressure
The operation of 5G base stations requires substantially more energy than previous generations, as higher frequencies and expanded
The operation of 5G base stations requires substantially more energy than previous generations, as higher frequencies and expanded infrastructure—such as small cells
Therefore, it is reasonable to focus on the power consumption of the base stations first, while other aspects such as virtualization of compute in the 5G core or the energy
But, the high energy consumption caused by the massive deployment of 5G base stations cannot be ignored. The total annual power consumption is expected to reach 243
Our study introduces a communications and power coordination planning (CPCP) model that encompasses both distributed energy resources and base stations to improve communication
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Furthermore, the base stations dominate the energy consumption of the radio access network. Therefore, it is reasonable to focus on the power consumption of the base stations first, while other aspects such as virtualization of compute in the 5G core or the energy consumption of user equipment should be considered at a later stage.
However, this technological leap comes with a substantial increase in energy consumption. Compared to its predecessor, the fourth-generation (4G) network, the energy consumption of the 5G network is approximately three times higher .
To improve the energy eficiency of 5G networks, it is imperative to develop sophisticated models that accurately reflect the influence of base station (BS) attributes and operational conditions on energy usage.
This restricts the potential use of the power models, as their validity and accuracy remain unclear. Future work includes the further development of the power consumption models to form a unified evaluation framework that enables the quantification and optimization of energy consumption and energy efficiency of 5G networks.