T-GCN Based Intelligent Decision-making System of 4G/5G Base Stations for Energy Saving and Emission Reduction
With the rapid development of 4G/5G mobile internet,in order to meet the growing traffic demand and improve the cov-erage of cellular networks,the traffic load of base stations is increasing explosively.In the context of global energy shortage,in order to achieve the goal of carbon peak and carbon neutrality,without reducing communication quality,it is an important issue to know how to accurately switch the base stations to reduce their energy consumption to the minimum.Therefore,based on the grid model and the base station energy-consuming calculation model,an intelligent base station decision system based on Temporal-Graph Convolutional Network(T-GCN)prediction and self-designed heuristic algorithm is proposed to realize intelligent opening and closing of base stations.At the same time,it is guaranteed to meet the practical constraints,so as to improve network resource management efficiency and optimize network energy consumption performance.Simulation experiment show that the flow-predicting consequence is good and an ideal decision result of base station switch is obtained in a certain range.
energy-savingT-GCN traffic predictionheuristic algorithm for switching decisionintelligent switch for base stations
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