Research On Low Complexity Channel Estimation Methods In Reconfigurable Intelligent Surface Systems

With the large-scale commercial use of the 5th generation mobile communication system,the research of the 6th generation mobile communication system has been gradually carried out.Reconfigurable intelligent surface(RIS),as one of the potential technologies of 6G,has attracted extensive attention from the academic community.The RIS consists of a large number of controllable phase-shifting elements that can reconfigure the wireless channel to reflect incoming electromagnetic waves in the desired direction.RIS has the potential to overcome congestion,increase channel capacity,and reduce transmit power for the future communications.To achieve the best performance gain of RIS systems,techniques such as joint active and passive beamforming and efficient resource allocation are required,which rely on accurate channel state information(CSI).Since the RIS contains a large number of reflective elements,more channel parameters need to be estimated in this system,and it is a challenge to obtain the CSI of the system with low computational complexity.This thesis mainly studies the lowcomplexity channel estimation problem in the RIS system.The main work is as follows:1.Aiming at the high complexity of channel estimation in RIS-assisted massive multiple input multiple output(MIMO)systems,a new method based on two-dimensional fast fourier transform(2D-FFT)was proposed.This is a low-complexity channel estimation method.In the proposed scheme,some components of the RIS are connected to the radio frequency(RF)chain,and the channels between the user-RIS and the RISbase station(BS)are estimated separately,and the separate acquisition of channels helps to improve the flexibility of channel estimation in user mobility scenarios.In the considered system,the received signal is zero-padded,and then the angle estimate is obtained by using the 2D-FFT algorithm.Finally,the path gain estimation is obtained by using the spectral peaks of the two-dimensional spatial spectrum of the signal and their corresponding arguments.The simulation results show that,on the premise of ensuring the channel estimation performance,the proposed scheme can greatly reduce the computational complexity and has a significant low-complexity advantage.2.Aiming at the sudden change and the slow change of the channel angle parameters in the RIS-assisted massive MIMO system,a channel tracking scheme based on Newton’s algorithm is proposed.In the proposed scheme,some of the RIS elements are connected to the RF chains.Firstly,the estimated angle parameters are initialized using the proposed channel estimation scheme based on the 2D-FFT algorithm,and the path gain parameters are estimated using the maximum likelihood algorithm.Secondly,in the channel estimation process of the subsequent time slots,the angle parameter estimation problem is transformed into the problem of finding extreme points,and the angle parameters in each time slot are estimated by using the Newton algorithm.In each slot,the proposed channel estimation scheme stops iterating when the angle estimates converge.Finally,since the appearance of new obstacles may cause a mutation in the channel matrix,if a mutation is detected,the channel parameters are initialized;otherwise,the Newton algorithm is still used to estimate the channel parameters.Simulation results show that the proposed channel estimation scheme can achieve a tradeoff between computational complexity and channel estimation performance.This thesis has made the above research results in the channel estimation research of RIS-assisted wireless communication system,which is of important significance to the research in this direction.