煤矿安全2024，Vol.55Issue(2)：211-217,7.DOI:10.13347/j.cnki.mkaq.20230658
基于改进图像超分辨卷积网络的矿井OFDM信道估计研究
Research on OFDM channel estimation of mine based on improved SRCNN
摘要
Abstract
Aiming at the problem of low accuracy of traditional channel estimation algorithms in the harsh environment of under-ground coal mines,this paper proposes an improved Super Resolution Convdutional Network(SRCNN)for channel estimation.In the improved SRCNN model,the estimated value at the pilot frequency is used as input,and the improved SRCNN model replaces the interpolation process in the traditional channel estimation algorithm to reduce the complexity,and the attention mechanism ECA module is added to improve the learning of channel features to achieve more accurate channel estimation for the underground coal mine environment.Simulation results show that the channel estimation algorithm of the improved SRCNN model outperforms the traditional channel estimation algorithm and improves the estimation accuracy by one order of magnitude compared with the channel estimation of the SRCNN model.关键词
矿井无线通信/智能矿山/改进SRCNN/信道估计/MSE/深度学习Key words
mine wireless communication/intelligent mine/improved SRCNN/channel estimation/MSE/deep learning分类
矿业与冶金引用本文复制引用
王安义,梁艳..基于改进图像超分辨卷积网络的矿井OFDM信道估计研究[J].煤矿安全,2024,55(2):211-217,7.基金项目
国家自然科学基金资助项目(U19B2015) （U19B2015）
