无线电工程2024，Vol.54Issue(4)：911-917,7.DOI:10.3969/j.issn.1003-3106.2024.04.014
基于注意力机制引导深度残差网络的RIS辅助通信信道估计
Channel Estimation for RIS-aided Communications Based on Attention Mechanism-guided Deep Residual Networks
摘要
Abstract
Using Reconfigurable Intelligent Surface(RIS)to improve wireless coverage and channel capacity has been considered as one of the candidates for future wireless communications.In order to estimate the state information of uplink Multi User(MU)channel,an attention mechanism-based deep residual network is proposed.Its structure is constructed which is comprised of a sparse block,a feature enhancement block,an attention block and a reconstruction block.The network not only implicitly learns residual noise,but also uses attention mechanism to enhance the extraction of specific channel noise features.Simulation results show that the method's accuracy is comparable to that of the ideal Linear Minimum Mean Square Error(LMMSE)estimation,whereas higher than that of a general deep residual denoising network at high signal to noise ratio.关键词
可重构智能表面/信道估计/深度学习/注意力机制Key words
RIS/channel estimation/deep learning/attention mechanism分类
信息技术与安全科学引用本文复制引用
张静,张强,苏颖..基于注意力机制引导深度残差网络的RIS辅助通信信道估计[J].无线电工程,2024,54(4):911-917,7.基金项目
上海市自然科学基金(19ZR1437600)Shanghai Municipal Natural Science Foundation of China(19ZR1437600) （19ZR1437600）
