Research On Efficient Channel Estimation Method For RIS-Assisted Communication System

Recently,reconfigurable intelligent surface(RIS)has attracted extensive attention.RIS consists of many reconfigurable reflective elements.The phases of different propagation paths can be aligned at the receiver by jointly adjusting the reflection phases of all RIS elements,thereby enhancing the received signal energy and improving the transmission performance.However,most of the existing research focuses on semi-static scenarios.In RIS-assisted mobile scenarios,if using the existing channel estimation methods,the RIS-assisted communication system will face serious problems of long-time channel estimation and high pilot overhead.Besides,the existing methods do not perform beamforming in the channel estimation stage,which means that a huge portion of spectrum resources are not efficiently utilized during channel estimation.Therefore,there is a need to study efficient channel estimation methods for RIS-assisted communication systems.Firstly,a low-cost channel estimation algorithm is studied.Due to the large number of passive RIS elements,the pilot overhead for channel estimation in RIS-assisted communication systems is huge.To address this problem,a three steps orthogonal matching pursuit algorithm is proposed.Compared with the existing low-cost channel estimation algorithms,the proposed algorithm can further reduce the number of channel estimation pilots under the premise of a given channel estimation accuracy.Specifically,the joint sparsity structure of cascaded channels associated with different users is fully revealed in this article,and the classical orthogonal matching pursuit algorithm is modified based on this sparsity structure.The proposed algorithm can jointly estimate the same channel parameters associated with different users.Therefore,it can resist the influence of noise.The simulation results show that the pilot overhead of channel estimation using the proposed algorithm is lower than using the existing schemes.Then,a phase optimization algorithm which improving the data transmission performance during the channel estimation stage is studied.To ensure the data transmission performance after the channel estimation stage,it is necessary to study the algorithm that takes both the channel estimation error and the data transmission performance into account.To address this problem,a new phase optimization algorithm is proposed in this article.Based on the prediction of the future channel from the Kalman filter,the proposed algorithm optimizes the phase reflection vector of the RIS with the goal of maximizing the average achievable rate in the channel estimation stage.With the idea of maximizes the minimum value,an iterative algorithm solving the non-convex optimization problems is proposed.The simulation results show that the proposed algorithm can effectively improve the overall transmission performance of the system.