移动通信2024，Vol.48Issue(4)：86-93,8.DOI:10.3969/j.issn.1006-1010.20231129-0001
基于改进DnCNN的RIS辅助毫米波系统信道估计
Channel Estimation for RIS-assisted Millimeter Wave System Based on DnCNN
摘要
Abstract
Reconfigurable intelligent surface(RIS)is one of the potential candidate technologies for sixth-generation wireless communication system.However,due to the passive nature of RIS lacking signal processing capability,it poses challenges to channel estimation in RIS-assisted millimeter wave(mmWave)multiple-input multiple-output(MIMO)systems.To obtain more accurate channel state information,the channel estimation is transformed into an image denoising problem,and an improved denoising convolutional neural network(DnCNN)is proposed to complete the channel estimation task.Specifically,the linear minimum mean squared error(LMMSE)method is used to estimate the channel coarsely.The DnCNN is improved by fusing the attention mechanism network and noise level estimation sub-network to enhance the network's performance on noise extraction and its adaptive performance to noise and to achieve high-precision channel estimation from the coarse one.Simulation experiments demonstrate that the proposed algorithm exhibits a good estimation performance at low signal-to-noise ratios.关键词
信道估计/RIS/去噪卷积神经网络/mmWave/注意力机制Key words
channel estimation/RIS/denoising convolutional neural network/mmWave/attention mechanism分类
信息技术与安全科学引用本文复制引用
吴颖,刘紫燕..基于改进DnCNN的RIS辅助毫米波系统信道估计[J].移动通信,2024,48(4):86-93,8.基金项目
贵州省联合资金资助项目"基于深度学习的行人重识别关键技术研究"(黔科合LH字[2017]7226号) （黔科合LH字[2017]7226号）
