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OA

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.