Exploration and Experiment of Graph Intelligence AI Technology in Base Station Traffic Prediction
5G network provides support for new technology fields with its high speed,extensive connectivity,and low latency,but it faces a severe challenge in terms of energy consumption.It explores the application of AI technology in enhancing the energy efficiency of base stations,and proposes a traffic prediction method based on Graph Neural Networks that takes into account the spatial correlation and temporal dependency of traffic data.The method combines graph convolutional networks and 1-D convolution modules to optimize the distribution of base station traffic,which significantly improves the accuracy of traffic prediction.Accurate traffic prediction can provide scientific basis for base station shutdown strategies,which effectively reduce energy consumption,improve energy efficiency,reduce costs,and promote sustainable development.
5G base stationEnergy savingTraffic predictionArtificial intelligenceGraph neural network
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