Research On Precoding Based On Iterative Algorithms In Massive MIMO Systems

With the rapid development of mobile communication,the research of 5G(Fifth-Generation)mobile communication is in full swing.Massive MIMO(Massive,multiple-input,multiple-output,Massive,MIMO),as one of the key technologies in 5G,has received extensive attention in recent years.Compared to the traditional MIMO,Massive MIMO systems are equipped with a large number of transmit antennas and serve more users,and the number is much larger than the traditional MIMO systems.Moreover,Massive MIMO has many advantages,for example,with the increase of the antenna number,the antenna tends to be orthogonal,the interference is reduced,and the performance of the system is improved.But because the Massive MIMO systems is equipped with a large number of transmit and receive antennas,the dimension of the matrix in the precoding algorithm is very large,which leads to the increase of the complexity of the computation matrix inverse.Therefore,this thesis focuses on how to reduce the computational complexity of precoding algorithms in Massive MIMO systems,and focuses on precoding based iterative algorithms.Firstly,the Massive MIMO systems model,signal model,and some related parameters are analyzed.The basic principle is given precoding algorithm and the process of pre-treatment,and discussed the classical precoding algorithm of zero forcing precoding and regularized zero forcing precoding,the Gauss iterative,successive over relaxation iterative method,Richardson iterative precoding based algorithm,and based on Neumann series precoding algorithm and,in the Rayleigh fading channel model,the several precoding algorithm and simulation and comparison and analysis.Secondly,based on research in the Richardson iterative precoding algorithm,from a performance perspective,the parameter selection method is improved and the parameters from the original coefficient matrix according to the maximum and minimum spectral radius using diagonal coefficient matrix of elements and selection.Then using the Richardson iterative algorithm to construct a precoding matrix is improved,namely RZF precoding based on Richardson iterative algorithm to improvement based on the complexity analysis,and compared with Neumann series precoding algorithm based on.On the BER performance and based on Neumann series precoding algorithm based on Richardson iterative precoding algorithm for simulation analysis,and based on the BER performance of improved Richardson iterative precoding algorithm varies with the number of transmit antennas,and different modulation methods to simulate the influence of BER.Finally,based on the successive over relaxation and symmetric over relaxation iterative algorithm,the comprehensive complexity and performance considerations are weighted on these two algorithms,and then use the weighted symmetric successive over relaxation algorithm to construct the precoding matrix,and proposes a precoding based on weighted symmetric successive over relaxation iterative algorithm,selection method of the relaxation parameter and weighted factor is simple,and is only related to the system parameters.The complexity of precoding algorithm based on weighted symmetric successive over relaxation iteration is analyzed and compared with the improved Richardson iterative algorithm and Neumann series based precoding algorithm mentioned above.Then,BER performance simulation of the precoding based on weighted symmetric successive over relaxation iterative algorithm,and compares with precoding of Neumann series and precoding based-on improved Richardson iterative algorithm.The error performance of precoding algorithm based on weighted symmetric successive over relaxation iteration is simulated with the influence of the number of transmit antennas and different modulation modes on their bit error rate.