Energy Efficiency for 5G and Beyond 5G: Potential, Limitations,
This method considers all possible combinations of base station sleep states to find the optimal configuration that minimizes energy consumption while maintaining network
Coordinated scheduling of 5G base station energy storage for
To enhance the utilization of base station energy storage (BSES), this paper proposes a co-regulation method for distribution network (DN) voltage control, enabling BSES
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
Energy-efficiency schemes for base stations in 5G heterogeneous
The paper aims to provide an outline of energy-efficient solutions for base stations of wireless cellular networks.
AI-based energy consumption modeling of 5G base stations: an energy
We design a Deep Neural Network (DNN) based energy consumption model. The designed DNN is then optimized through quantization process for reducing its size, inference
Optimization Control Strategy for Base Stations Based on Communication
Therefore, in response to the impact of communication load rate on the load of 5G base stations, this paper proposes a base station energy storage auxiliary power grid peak shaving method
Energy-efficiency schemes for base stations in 5G heterogeneous
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 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
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
Energy-saving control strategy for ultra-dense network base stations
Aiming at the problem of mobile data traffic surge in 5G networks, this paper proposes an effective solution combining massive multiple-input multiple-output techniques