Channel Estimation And System Performance Analysis For Reconfigurable Intelligent Surface Assisted Hybrid Millimeter Wave Systems

Reconfigurable Intelligent Surface(RIS)can realize automatic regulation the wireless environment by controlling electromagnetic components.It brings a revolutionary breakthrough in the way of information transmission for future communication technology.However,the practical design and implementation of wireless communication systems assisted by RIS faces various challenges,including channel estimation with RIS,passive beamforming design on the RIS,and the error caused by nonideal hardware system.In order to fully exploit the potential of RIS,it is essential for RIS to obtain accurate channel state information(CSI),but the inherent passive characteristics of RIS make the channel estimation technology of RIS more difficult.In this paper,the channel estimation of RIS-assisted Hybrid Millimeter Wave Systems is studied in depth,and the main work is briefly described as follows:Firstly,we propose a sensing-based two-timescale channel estimation algorithm for RIS assisted multi-user hybrid millimeter wave systems.The proposed channel estimation algorithm aims to separately estimate the base station(BS)-RIS and RIS-user channels instead of estimating the cascaded BS-RIS-user channel with a limited number of radio frequency chains equipped at the BS.To be specific,the proposed algorithm first cooperatively acquires parameters of the BS-RIS channel via sensing methods by transmitting and receiving pilot signals at the BS once over the large timescale.Then,users transmit orthogonal training sequences to the BS while RIS elements are sequentially turned on and off for obtaining CSIs of time-varying RIS-user channels over the small timescale.We analyze the normalized mean square error(NMSE)performance of the proposed channel estimation algorithm.We also derive the corresponding closed-form performance bound and the Cramer-Rao lower Bound(CRLB).Facilitating with the perfect CSI of the BS-RIS channel at the BS,we also derive the NMSE performance of the scenario that simultaneously turning on and off multiple RIS elements.The derived analytical results demonstrate the superiority of the scenario that turning on and off RIS elements one by one in mm Wave channels in terms of the NMSE performance.Furthermore,we illustrate the robustness of the proposed channel estimation under the impact of various types of errors,e.g.,low-resolution phase control for RIS elements and large timescale sensing errors.All analytical results have been verified via numerical simulations.Finally,the mm Wave communication system is extended from a single RIS to distributed multiRIS,aiming at distributed RIS-assisted mm Wave Hybrid system.Under mm Wave sparse channels,the critical performance improvement of the overall communication system is enhanced by using distributed multi-RISs,i.e.,by controlling and adjusting the wireless channel between the BS and the user,artificially changing the wireless communication environment to increase the system degree of freedom.The proposed method to obtain the line-of-sight(LOS)angle between the RIS and the user.The linear constrained minimum variance(LCMV)beamforming at the user is designed based on the strongest line-of-sight angle to reduce the mutual interference between multiple data.Simulation results demonstrate that the achievable rate at the user is significantly improved compared to conventional beamforming(CBF).