电讯技术2024，Vol.64Issue(4)：512-519,8.DOI:10.20079/j.issn.1001-893x.220808001
融合残差SENet的毫米波大规模MIMO信道估计
mmWave Massive MIMO Channel Estimation Fused with Residual SENet
摘要
Abstract
In the outdoor ray tracing scene,to solve the problem of low estimation accuracy of channel estimation caused by outdoor ambient noise interference in mmWave massive multiple-input multiple-output(MIMO)systems,a channel estimation method based on the Conditional Generative Adversarial Network(CGAN)of fused residual Squeeze-and-Excitation Network(SENet)is proposed.The method uses the CGAN to reconstruct the low resolution received signal into the original signal with high resolution to complete channel estimation.At the same time,SENet is introduced into the generator network to suppress the significant noise interference in the outdoor scene and improve the estimation accuracy.Finally,the residual block in the residual network is added to the scaling operation of the SENet to improve the convergence speed of the CGAN.The simulation results show that compared with that of Orthogonal Matching Pursuit(OMP)algorithm,Convolutional Neural Network(CNN)algorithm,Denoising Convolutional Neural Network(DnCNN)algorithm and CGAN algorithm,the estimation accuracy of the proposed method in outdoor noise environment is improved by about 2.2 dB on average,and the improvement of estimation accuracy is more significant under high noise intensity.关键词
毫米波大规模MIMO/信道估计/条件生成对抗网络(CGAN)/残差挤压激励网络(SENet)Key words
millimeter wave massive MIMO/channel estimation/conditional generative adversarial network(CGAN)/squeeze-and-excitation network(SENet)分类
信息技术与安全科学引用本文复制引用
刘庆利,杨国强,张振亚..融合残差SENet的毫米波大规模MIMO信道估计[J].电讯技术,2024,64(4):512-519,8.基金项目
国家自然科学基金资助项目(61931004) （61931004）
