Channel state information reconstruction method based on deep learning

A technology of channel state information and deep learning, applied in channel estimation, baseband system, baseband system components, etc., can solve the problems of multiple iterations and increased computational complexity, and achieve the goal of reducing model overfitting and improving performance Effect
CN111464220AActive Publication Date: 2020-07-28XI AN JIAOTONG UNIV
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Patent Information

Authority / Receiving Office
CN · China
Current Assignee / Owner
XI AN JIAOTONG UNIV
Publication Date
2020-07-28

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Abstract

The invention discloses a channel state information reconstruction method based on deep learning. The method comprises the following steps: obtaining an NBS * Nc-dimensional channel matrix H on a frequency domain at a user side; converting the obtained channel matrix H into an angle delay domain channel matrix Ha with only non-zero elements; in the angle time delay domain, acquiring a new dimension matrix by advancing in the intercepted channel matrix Ha, converting the new matrix into a non-sparse vector X with the dimension of 2N * 1, wherein the non-sparse vector X serves as to-be-compressed data, and carrying out compression through the compressed sensing technology to obtain to-be-fed back channel state information Y; reconstructing and training a channel state information network; and according to the trained ReNet network model, recovering Y as input data of the network and as output data of the network from the obtained channel state information Y to be fed back, and performinginverse Fourier transform to obtain original CSI after obtaining. The original CSI data obtained by the user side is processed, subsequent compression and feedback are facilitated, and recovery ofthe compressed data is completed through the network trained by the known samples.
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Description

technical field

[0001] The invention belongs to the technical field of communication, and in particular relates to a channel state information reconstruction method based on deep learning. Background technique

[0002] Massive multiple-input multiple-output (Multiple-input Multiple-output, MIMO) system can improve the frequency spectrum and power utilization of wireless communication, and is one of the main technologies of the fifth generation wireless communication system. In a massive MIMO system, the base station usually needs to use channel state information (Channel State Information, CSI) for precoding, adaptive coding, user scheduling, etc. significant impact.

[0003] In a Time Division Duplexing (TDD) system, due to the reciprocity between the uplink and downlink channels, the transmitter can estimate the CSI through the uplink channel, and then determine the CSI of the downlink channel through the reciprocity. However, in the Frequency Division Duplexing (FDD) mo...

Claims

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