Energy-saving control strategy for ultra-dense network base
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
6. Conclusion In this paper, we thoroughly study the base station control problem in 5G ultra-dense networks and propose an innovative MAPPO algorithm. The algorithm significantly reduces the overall power consumption of the system by optimizing inter-base station collaboration and interference management while guaranteeing user QoS.
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.
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.
When there is little or no communication activity, base stations typically consume more than 80% of their peak power consumption, leading to significant energy waste . This energy waste not only increases operational costs, but also burdens the environment, which is contrary to global sustainability goals .
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
Abstract. As the number of communication terminals in power IoT continues to grow, the significance of Ultra-Dense Networks (UDN) interference management for maintaining quality of
Nevertheless, the deployment of base stations for a multitude of communication needs also engenders considerable interference in both the frequency and power domains. This paper
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For multi-user interference, M. Schubert et al. first proposed a solution to the precoding design problem of eliminating multi-user interference [3]. For inter-base station interference, the
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