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MIMO channel state information feedback method based on anti-fitting deep learning

A channel state information and deep learning technology, applied in the field of massive MIMO channel state information feedback based on anti-fitting deep learning, can solve problems such as insufficient accuracy of predicted channel state information

Active Publication Date: 2020-11-06
YANSHAN UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The technical problem to be solved in the present invention is to provide a MIMO channel state information feedback method based on anti-fitting deep learning to solve the problem of insufficient accuracy of predicted channel state information due to overfitting in current deep learning methods

Method used

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  • MIMO channel state information feedback method based on anti-fitting deep learning
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  • MIMO channel state information feedback method based on anti-fitting deep learning

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Embodiment Construction

[0029] Below in conjunction with embodiment the present invention is described in further detail:

[0030] Such as figure 1 As shown, a MIMO channel state information feedback method based on anti-fitting deep learning includes the following steps:

[0031] (1) Construct the AOCN (Anti-overfitting CSI net, AOCN) model, using the convolutional neural network as the encoder and decoder. The convolutional neural network can take advantage of the spatial locality by strengthening the local connection mode between adjacent layer neurons. Correlation, the real and imaginary parts of the channel matrix H as its input;

[0032] (2) The channel matrix H data enters the encoder. The encoder is located at the user end that sends the data, and encodes the channel matrix H into a low-dimensional data. The encoder includes a convolutional layer and a fully connected layer. It consists of the following: In the convolutional layer of the encoder, this layer uses a kernel of size 3×3 to gene...

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Abstract

The invention discloses an MIMO channel state information feedback method based on anti-fitting deep learning, and belongs to the field of communications. The method comprises the following steps that: firstly, an AOCN model is constructed, a channel matrix is divided into a real part and an imaginary part which are then input into an encoder of a user side, the encoder comprises a convolution layer and a full connection layer, data reaches a receiving end through a feedback link after being encoded, a decoder at the receiving end comprises an anti-fitting layer, a full connection layer, a RefineNet layer and a convolution layer, and finally a predicted channel matrix is output. After the AOCN model is constructed, offline training is performed on the model, model parameters are initialized firstly, the model is stored after error convergence, and finally, the trained and stored AOCN model is subjected to channel state information prediction online. According to the invention, the recovery precision of the information matrix can be further improved, the transmitting end of the system is ensured to obtain accurate channel state information, and the communication quality of the system is improved.

Description

technical field [0001] The invention relates to the communication field, in particular to a large-scale MIMO channel state information feedback method based on anti-fitting deep learning. Background technique [0002] As a key technology of the fifth generation (5G) communication system, massive multiple-input multiple-output (MIMO) technology has the advantages of high spectral efficiency, large system capacity, and strong system robustness. In order to ensure that the channel state information obtained by channel estimation can be Accurately fed back to the sending end, the MIMO system has a higher data transmission rate than the OFDM system, and improves the reliability of the system. Therefore, massive MIMO technology is getting more and more attention from industry and academia. However, the significant advantages of massive MIMO technology depend heavily on the availability of downlink channel state information to the transmitter. In frequency division duplex massive...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04B7/06H04L25/02G06N3/08G06N3/04
CPCH04B7/0626H04B7/0632H04L25/0254G06N3/08G06N3/045
Inventor 李鑫滨赵海红韩赵星于海峰骆曦
Owner YANSHAN UNIV
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