Research On Antenna Selection And Precoding Algorithm In Massive MIMO Correlated Channels

Massive MIMO technology improves system capacity by equipping hundreds of antennas,but it also inevitably causes interference between users.Antenna selection and precoding are the core technologies of massive MIMO systems.Most of the existing antenna selection studies assume that the channels are ideal and independent.In the actual communication environment,due to factors such as unsatisfactory antenna characteristics and uneven distribution of scatterers,the channels often have spatial correlations.Therefore,this paper explores the problem of antenna selection in related channels.In addition,in a multi-user MIMO system,the interference between users is also greater,and precoding technology has become another research focus because it can effectively reduce the interference between users.In addition,in order to reduce the computational complexity of precoding,it is necessary to study joint antenna selection and precoding algorithms.The main work of this paper is as follows:(1)Aiming at the problem of high inter-user interference caused by high correlation between antennas in the spatially correlated channel scenario of massive MIMO systems,an antenna selection algorithm based on antenna grouping is proposed.First,the transmit antennas are grouped by the instantaneous channel correlation matrix,and the optimal combined antenna subset is found to ensure that the correlation between the antennas in the same group is as high as possible;then the antennas are selected based on the channel matrix norm criterion in each group.Since the correlation between antennas in different groups is relatively low,using the antennas selected in the above steps to transmit signals can effectively reduce the loss to the system caused by strong antenna correlations.The simulation results show that when the antenna correlation factor is?=0.8 and the SNR=10d B,compared with the antenna selection algorithm based on adjacent antenna grouping,the traversal information rate of the proposed algorithm is improved by about 40%,and the proposed algorithm is in the relevant channel and independent.It has good applicability in the channel.(2)In the imperfect CSI scenario of massive MIMO system,when the number of receive antennas is more than the number of transmit antennas,traditional SLNR precoding will lead to system performance deterioration.To solve the above problems,an improved SLNR precoding scheme is proposed.The receiving filter matrix is introduced into the user's signal-to-leakage-to-noise ratio to suppress the leakage power to other users,and the iterative method breaks through the limitation of mutual coupling between the precoding matrix and the filter matrix.The proposed algorithm improves the number of supported users and performance of the system.The simulation results show that when the CSI reliability?=0.3 and SNR=10d B,the sum rate of the improved SLNR precoding algorithm is about 8.8%higher than that of the traditional SLNR precoding algorithm.(3)In the case of massive MIMO correlated channels and imperfect CSI,a joint antenna selection and precoding scheme is proposed to solve the problem of high computational complexity when solving high-dimensional precoding matrices.Firstly,the low-dimensional effective channel matrix is obtained through the antenna selection algorithm based on antenna grouping,and then the precoding matrix is obtained according to the improved SLNR precoding algorithm.This scheme reduces the computational complexity while ensuring the system performance.The results show that when?=0.8,?=0.3,and SNR=10d B,the sum rate of the joint algorithm is improved by about 7%compared with the single precoding algorithm;the complexity of the joint algorithm is O(3K×N~2)reduced to O(3K×L~2),(L<N).