Study On The Uplink Channel Estimation Algorithm Of MASSIVE MIMO Systems

Massive MIMO technology changes the characteristic of system through increasing the antennas numbers. greatly improving the system capacity and spectrum efficiency, has become one of the key technologies of 5G now. The dimension of the channel state matrix increases with the number of antennas in the system increasing, which puts forward higher requirements for the channel estimation algorithm. Pilot contamination is particularly prominent in Massive MIMO system, so it’s a serious problem to seek low complexity and anti-pilot contamination channel estimation algorithm.This paper analyzes the advantages of Massive MIMO technology, and the characteristics of point to point and multiuser Massive MIMO system. This paper introduces the modeling method of MIMO Massive system, and gives the analytical model and the simulation model of the correlation channel. On this basis, the emphasis of this paper is to study the pilot based channel estimation algorithm and subspace based semi blind channel estimation algorithm, and propose modified algorithm aiming at the shortage of the existing algorithms.Based on the theory analysis and performance simulation of the LS, ML, MMSE and MAP classical channel estimation algorithm, this paper proposes the scalar modified LS algorithm and MMSE algorithm based on noise estimation combining the approximate orthogonality of the channel vectors. The proposed algorithm improves the estimation accuracy of LS algorithm at low signal to noise ratio and improves the applicability of MMSE algorithm. For multi-cell system, pilot contamination damages to the performance of the system. The system is interference limited. People attempts to solve the pilot pollution problem by using the pilot transmission scheme based on slot offset. the feasibility of the scheme is analyzed in this paper. To eliminate pilot pollution problems, we study a kind of channel estimation algorithm based on short pilot repeated transmission. Such algorithms don’t need to know the two order statistics characteristic of the channel, effectively eliminating pilot contaminationSemi blind channel estimation algorithm only needs little pilot, so as to avoid the pilot contamination problem This paper firstly analyzes and discusses the semi blind channel estimation algorithm based on EVD proposed in the literature, and then introduces an improved algorithm, namely, the generalized linear algorithm, and the estimation error of the two algorithms are theoretically deri ved and analyzed. The ambiguity matrix of SVD algorithm is not a diagonal matrix, but a square matrix, which reduces the error caused by the non-orthogonal channel. Although it’s has a good performance, but the computation is very large. In this paper, we propose a channel estimation algorithm based on subspace tracking. Without sacrificing the estimation performance, the complexity of the SVD algorithm is greatly reduced.