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Channel estimation method for large-scale MIMO system based on block structure adaptive compressive sampling matching pursuit algorithm

A compression sampling and matching tracking technology, applied in channel estimation, baseband system, baseband system components, etc., can solve the problems of inflexibility, large number of pilots, etc., achieve good estimation effect and reduce mean square error

Inactive Publication Date: 2018-09-28
NORTHEASTERN UNIV
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Problems solved by technology

There are still some problems in the current compressed sensing algorithm for channel estimation in massive MIMO systems, such as the need to know in advance the channel sparsity that is difficult to obtain in practical applications, or the inflexibility in the selection of atoms, so that the number of pilots used in estimation is still large Wait

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  • Channel estimation method for large-scale MIMO system based on block structure adaptive compressive sampling matching pursuit algorithm
  • Channel estimation method for large-scale MIMO system based on block structure adaptive compressive sampling matching pursuit algorithm
  • Channel estimation method for large-scale MIMO system based on block structure adaptive compressive sampling matching pursuit algorithm

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[0018] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention are clearly and completely described below in conjunction with the drawings in the embodiments of the present invention:

[0019] Such as figure 1 Shown: A massive MIMO system channel estimation method based on block-structure adaptive compressed sampling matching pursuit algorithm, through N T Antennas transmit pilot information, at N R A single-antenna user terminal receives, including the following steps:

[0020] S1. Calculate the pilot information measurement vector y received at the receiving end of each user, and establish a compressed sensing mathematical model for the pilot information transmission process according to the sparse consistency of the massive MIMO system channel, and construct a sensing matrix Φ, specifically include:

[0021] S101. Each antenna at the base s...

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Abstract

The invention discloses a channel estimation method for a large-scale MIMO system based on a block structure adaptive compressive sampling matching pursuit algorithm. Pilot information is sent at a single cell base station through NT antennae and received at NR single antenna user terminals. The method includes the following steps: S1, calculating a pilot information measurement vector y receivedat each user receiving end, establishing a compressive sensing mathematical model for a pilot information transmission process according to the sparsity consistency of channels of the large-scale MIMOsystem, 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 reconstruction algorithm; and S3, reconstructing a sparse signal h by using the block structure adaptive compressive sampling matching pursuit algorithm. According to the scheme of the invention, the time domain sparsity consistency of the channels of the large-scale MIMO system is utilized, a channel impulse response is reconstructed by using the block structure adaptive compressive sampling matching pursuit algorithm, and moreover, the estimation can be performed when the sparsity is unknown, and the use of pilots can be reduced.

Description

technical field [0001] The invention relates to communication channel estimation, in particular to a massive MIMO system channel estimation method based on a block-structure self-adaptive compression sampling matching pursuit algorithm. Background technique [0002] With the development of wireless communication transmission technology in recent years, massive MIMO technology has become one of the key technologies of 5G. It can build multiple signal transmission channels between the transmitting antenna and the user end, making full use of space resources. Generally, massive MIMO systems configure dozens or even hundreds of antennas at the base station to form an antenna array, serving multiple users at the same time, and using spatial multiplexing and transmission diversity technologies to improve the information transmission rate and transmission reliability of the system and at the same time Improved spectrum utilization. Research on signal detection and correlation equa...

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Application Information

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IPC IPC(8): H04B7/0413H04L25/02H04L27/26
CPCH04B7/0413H04L25/0202H04L25/0242H04L27/2601H04L27/2613
Inventor 佘黎煌张石庞晓睿
Owner NORTHEASTERN UNIV
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