Energy-efficiency schemes for base stations in 5G
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 both
To address the issue of power-intensive base stations, proposed a combined approach involving base station sleep and spectrum allocation. This approach aims to discover the most efficient operating state and spectrum allocation for SBS to minimize power consumption and network disturbance.
Using this technique, the energy consumption of a base station can be reduced by turning off energy-intensive devices inside the base station, or by turning off the entire base station and keeping only the sensing module to wake up the base station.
Meanwhile, communication base stations often configure battery energy storage as a backup power source to maintain the normal operation of communication equipment [3, 4]. Given the rapid proliferation of 5G base stations in recent years, the significance of communication energy storage has grown exponentially [5, 6].
In the distributed execution phase, each actor network makes decisions independently based only on its own network and observations, and although each actor executes independently, the whole system is able to obtain a better base station control strategy because their strategies are based on the results of global optimization. Fig. 2.
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 both
A telecom base station in a remote location is a lifeline. It connects isolated communities, supports emergency services, and enables digital economies. When this station loses power, the impact is
This paper explores optimized control strategies for green low-carbon base station (BS) systems within the energy router (ER) framework. It highlights challenges such as rising energy
On the basis of ensuring smooth user communication and normal operation of base stations, it realizes orderly regulation of energy storage for large-scale base stations, participates in
An interactive hybrid control mode between energy storage and the power system under the base station sleep control strategy is delved into, demonstrating that the proposed model can
However, the deployment of numerous small cells results in a linear increase in energy consumption in wireless communication systems. To enhance system efficiency and establish green
Request PDF | On Oct 1, 2024, Yan Zhen and others published Energy-Saving Control Strategy for Ultra-Dense Network Base Stations Based on Multi-Agent Reinforcement Learning | Find, read and
With the rapid development of the digital new infrastructure industry, the energy demand for communication base stations in smart grid systems is escalating daily. The country is vigorously
A base station control algorithm based on Multi-Agent Proximity Policy Optimization (MAPPO) is designed. In the constructed 5G UDN model, each base station is considered as an
This paper proposed a multi-agent reinforcement learning based power control strategy for base stations in UDN. The method initially modeled system energy consumption with EE and SE as
PDF version includes complete article with source references. Suitable for printing and offline reading.