Channel estimation method for large-scale MIMO system based on improved distributed compressed sensing algorithm

Abstract

The invention discloses a channel estimation method for a large-scale MIMO system based on an improved distributed compressed sensing algorithm. Pilot information is transmitted through NT antennas ata single cell base station and received at NR single antenna user terminals. The method includes the steps of S1, calculating a measurement vector y of the pilot information received at each user receiving terminal, establishing a compressed sensing mathematical model for the pilot information transmission process according to the sparsity consistency of channels of the large-scale MIMO system, and constructing a sensing matrix [Phi]; S2, obtaining a block structure sensing matrix [Psi] through block structure transformation, and reconstructing a block sparse signal g through a reconstructionalgorithm; and S3, reconstructing a sparse signal h by using a block structure adaptive compressed sampling matching pursuit algorithm. According to the invention, the time domain sparsity consistency of the channels of the large-scale MIMO system is utilized, the channel impulse response is reconstructed by using the block structure adaptive compressed sampling matching pursuit algorithm, the estimation can be performed when the sparsity is unknown, and the use of the pilot frequency can be reduced.

Description

technical field [0001] The present invention relates to communication channel estimation, in particular to a method for channel estimation of a massive MIMO system based on an improved distributed compressed sensing algorithm. Background technique [0002] With the rapid development of wireless communication transmission technology and the rapid popularization of smart phones in recent years, massive MIMO technology can build multiple parallel signal transmission channels between the transmitting antenna and the user end, make full use of space resources, and effectively improve communication. The spectrum utilization rate, information transmission rate and capacity of the system have become one of the key technologies of 5G. The invention belongs to the technical field of communication channel estimation, in particular to a massive MIMO system channel estimation technology based on a distributed compressed sensing algorithm. [0003] In a massive MIMO system, first of all,...

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Problems solved by technology

[0004] In view of the problems of using too many pilots and low estimation accuracy when the compressed sensing algorithm is applied to downlink channel estimation of massive MIMO system in the prior art, the purpose of the present invention is to provide a channel estimation method which utilizes massive MIMO The space-time correlation of the system channel is sparsely consistent in the time domain, and the distributed compressed sensing algorithm is used to reconstruct the channel impulse response, which can improve the accuracy of channel estimation while reducing the number of pilots

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