通信与信息技术Issue(4)：7-9,67,4.
一种基于深度学习的电波传播场强预测方法
A method for predicting the field strength of radio wave propagation based on deep learning
摘要
Abstract
The prediction of radio wave propagation field strength is of great significance to the planning of wireless network,and its prediction accuracy is directly related to the large-scale propagation characteristics of communication environment.In order to im-prove the accuracy of radio wave propagation field intensity prediction,it is necessary to increase the input characteristic dimension as much as possible to maximize the description of the environment.The satellite image can intuitively display the environmental charac-teristics of the study area and take them as input characteristics.The convolutional neural network is used to build a model to accurately predict the radio wave propagation.Therefore,a deep learning field strength prediction method based on satellite image data is proposed in this paper.The input data are latitude and longitude,elevation and satellite image,and the output is predicted field strength.The results show that,compared with the model prediction value without satellite image as input,the prediction accuracy is improved by 15.2%after adding satellite image as input feature,and the prediction accuracy is improved by 6.4%when the satellite image data is enhanced.关键词
电波传播场强预测/卫星图像/卷积神经网络/数据增强Key words
Radio wave propagation field strength prediction/Satellite imagery/Convolutional neural networks/Data enhancement分类
信息技术与安全科学引用本文复制引用
孙绍哲,岑逸翔,谢玮松..一种基于深度学习的电波传播场强预测方法[J].通信与信息技术,2024,(4):7-9,67,4.
