Channel Estimation Method for Large-Scale MIMO System Based on Improved Distributed Compressive Sensing Algorithm

Abstract

The invention discloses a channel estimation method for a massive MIMO system based on an improved distributed compressed sensing algorithm. T Antennas transmit pilot information, at N R Receive by a single-antenna user end, including the following steps: S1. Calculate the pilot information measurement vector y received at each user receiving end, and establish compression for the pilot information transmission process according to the sparse consistency of the massive MIMO system channel. Perceive the mathematical model and construct the perceptual matrix Φ; S2. Obtain the block structure perceptual matrix Ψ through the block structure transformation, and reconstruct the block sparse signal g through the reconstruction algorithm; S3. Reconstruct the sparse signal using the block structure adaptive compression sampling matching pursuit algorithm signal h. The invention utilizes the time-domain sparsity consistency of the massive MIMO system channel, uses a block-structure self-adaptive compression sampling matching pursuit algorithm to reconstruct the channel impulse response, and can estimate when the sparsity is unknown and can reduce the use of pilot frequency.

Description

technical field [0001] The 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, and in particular relates to a massive MIMO system channel estimation technology based on a distributed compressed sensing algorithm. [0003] In a massive MIMO system, first of ...

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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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