无线电工程2025，Vol.55Issue(8)：1627-1634,8.DOI:10.3969/j.issn.1003-3106.2025.08.009
基于深度学习和Web的移动通信电波预测系统
A Mobile Communication Radio Wave Prediction System Based on Deep Learning and Web
摘要
Abstract
To meet the demands of radio wave propagation prediction,a deep learning model RadioDualNet,which combines the features of satellite imagery and radio propagation characteristics is proposed,in order to achieve the visualization of radio wave propagation and its association with geospatial information.On this basis,a mobile communication radio wave prediction system based on deep learning and Web technology is designed.The system is trained and evaluated on open-source datasets and measured datasets.The results show that the prediction performance of the proposed model on the open source dataset is improved by 45.8%,and the prediction results in both datasets are highly consistent with the measured values,verifying the effectiveness and applicability of the model.This study provides valuable insights for network planning and radio wave propagation research in the field of wireless communication,and demonstrates a good robustness and application value while improving prediction accuracy.关键词
电波传播/深度学习/卫星图像/Web系统/特征融合Key words
radio wave propagation/deep learning/satellite imagery/Wed-based system/feature fusion分类
信息技术与安全科学引用本文复制引用
高宇,杨晶晶,黄铭,赵海茹..基于深度学习和Web的移动通信电波预测系统[J].无线电工程,2025,55(8):1627-1634,8.基金项目
国家自然科学基金(62361055,62261059,61963037) National Natural Science Foundation of China(62361055,62261059,61963037) （62361055,62261059,61963037）
