Research On Channel Estimation Algorithm For Massive MIMO Systems

Massive MIMO(multiple input multiple output MIMO)system can greatly improve the communication quality of the wireless channel,and can greatly improve the spectrum utilization rate and system capacity of the communication system.It is because of this distinctive characteristic that the massive MIMO system is large.Massive MIMO has an undisputed dominance in the upcoming 5G era.However,good channel state information plays an important role in massive MIMO systems.Therefore,further research on channel estimation technology has become urgently needed for us,and cost-effective channel estimation technology can be greatly improved.Communication quality of wireless communication systems.Based on the research of massive MIMO system,this paper briefly introduces the principle and channel model of massive MIMO system,and briefly discusses the channel characteristics of wireless communication,and further carries out the two channel models in massive MIMO system.Research,namely flat fading and frequency selective fading channel models.Based on this channel model,the channel estimation technique in massive MIMO system is described in detail,and it is mainly used for Least squares(LS)and Singular Value Decomposition(SVD)based channel estimation Technology is discussed.In massive MIMO systems,SVD is studied by covariance matrix of signals.This method uses limited sample data to replace real data for channel estimation.This will inevitably increase the error and reduce the feasibility of the algorithm.Aiming at the shortcomings of this channel estimation algorithm,this paper proposes a channel estimation algorithm combining SVD and iterative least square with projection(ILSP),which can reduce the deviation in existing algorithms.It can greatly improve the estimation accuracy of the channel,and can improve the practicability of the algorithm to some extent.In massive MIMO,how to accurately obtain channel status information(CSI)is a prerequisite for improving channel capacity.However,since CSI is related to pilot sequences to some extent,the number of antennas is larger,and the pilot sequence is also followed.The more,the greater the channel overhead.Aiming at this problem,this paper proposes a new acquisition CSI scheme and an estimation algorithm based on low rank matrix recovery.The algorithm fully converts the channel estimation problem into a low-rank matrix recovery problem based on the characteristics of the massive MIMO channel,and solves the CSI used to obtain the complete user through the softthreshold algorithm.The simulation results show that the proposed method can improve the estimation accuracy of the channel and improve the complexity of the algorithm to some extent while using less channel overhead.Finally,the proposed algorithm is simulated and analyzed.By comparing the existing channel estimation algorithms,the proposed SVD+ILSP algorithm can improve the channel estimation accuracy.Similarly,the SVD-based low rank matrix recovery channel estimation algorithm can effectively reduce channel overhead and reduce algorithm complexity.