Channel estimation method of low-complexity large-scale MIMO system based on ISSOR_PCG

Abstract

According to a channel estimation method for the low-complexity large-scale MIMO system based on ISSOR_PCG provided by the invention, the calculation complexity can be reduced on the basis of maintaining the existing performance, and the convergence speed is higher. The method comprises the steps of S1, establishing a large-scale MIMO system model, and a user side sending pilot frequency sequencesignals to a base station side; S2, in the large-scale MIMO system model, the base station side estimating channel state information by using the received pilot frequency sequence signals; S3, performing vectorization processing on the pilot signal matrix Y received by the base station end to obtain a matrix of which the vector needs to be inverse according to the determination requirement; s4, decomposing the matrix required to be inversed by using a symmetric step-by-step super-relaxation method to obtain a linear equation capable of expressing the matrix required to be inversed, and converting an inversion process into solving the linear equation; s5, obtaining a preprocessing matrix by using an improved symmetric step-by-step super-relaxation method, and solving the linear equation byusing an iterative method; and S6, solving a final estimation channel matrix according to the approximate solution of the linear equation.

Description

technical field [0001] The invention relates to the technical field of wireless communication, in particular to a channel estimation method for a low-complexity massive MIMO system based on ISSOR_PCG. Background technique [0002] Massive MIMO (Massive Multiple-Input Multiple-Output, Massive MIMO) system is one of the key technologies of the fifth-generation mobile communication system. By configuring a large number of antennas at the base station and user end, the system channel capacity and data Transmission rate, spectral efficiency and communication quality. As the number of antennas at the base station and the user end increases, the dimension of the channel matrix becomes higher and higher. However, when many traditional methods are used in massive MIMO systems, direct inversion operations on high-dimensional matrices are required, and direct inversion operations will introduce high computational complexity in massive MIMO systems: There are methods, such as the most...

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Problems solved by technology

[0003] In order to solve the problem of large-scale MIMO systems, as the number of antennas increases, the dimension of the matrix also increases, and the calculation complexity is too high when directly inverting the high-dimensional matrix, resulting in long calculation time and poor performance. For the problem of high system performance requirements, the present invention provides a channel estimation method for a low-complexity massive MIMO system based on ISSOR_PCG, which can reduce the computational complexity while maintaining the existing performance, and the convergence speed is faster

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