Research On Hybrid Precoding Technology In 5G Massive MIMO System

Massive MIMO(Massive Multiple Input Multiple Output)is a key technology in 4.5G and 5G modern mobile communication systems.It is based on the basic principles of spatial diversity and spatial multiplexing to greatly improve the throughput and spectrum efficiency of the cell.Due to the complexity of the integrated antenna that the Massive MIMO system relies on,Massive MIMO technology has become a research hotspot in the modern communications industry.Aiming at the problem of how to improve the system capacity of 5G Massive MIMO system,this paper proposes a hybrid precoding algorithm.Massive MIMO system capacity can be described as a non-convex solution process,inspired by the user's continuous signal serial interference cancellation detection algorithm.The total capacity of the solution system is converted into the sum of the reachable rates of each user,which ultimately maximizes the system capacity.This can be achieved by maximizing the rate of each sub-antenna array.Therefore,a hybrid precoding algorithm based on MMSE-SIC(Minimum Mean-Square Error-based Successive Interference Cancellation)is proposed in this paper.And the hybrid precoding algorithm reduces the complexity of the algorithm by using the matrix's eigenvalue decomposition method instead of the matrix's singular value decomposition and matrix inversion.Finally,a system capacity simulation evaluation of the MMSE-SIC algorithm was performed.Simulation results show that the system capacity of the improved low-complexity MMSE-SIC algorithm is close to 90%of the capacity of the traditional all-digital algorithm system,and the algorithm complexity is based on sparse scattering 10%of the algorithm.The simulation proves that the proposed MMSE-SIC algorithm not only meets the system capacity requirements,but also greatly reduces the algorithm complexity,and has good robustness.