Channel estimation method, medium and device based on compressed sensing and deep learning
A technology of compressed sensing and channel estimation, applied in the field of communication, can solve the problem of a large amount of noise in the channel, achieve the effect of reducing the number of pilots, improving spectrum utilization, and reducing the amount of calculation
Active Publication Date: 2021-11-19
XI AN JIAOTONG UNIV
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[0004] Traditional methods based on compressed sensing, such as Orthogonal Matching Pursuit (OMP) and Compressive Sampling Matching Pursuit (CoSaMP), require prior knowledge of the known channel, such as channel sparsity, etc. , while the estimated channel still contains a lot of noise
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[0043] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.
[0044] It should be understood that when used in this specification and the appended claims, the terms "comprising" and "comprises" indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude one or Presence or addition of multiple other features, integers, steps, operations, elements, components and / or collections thereof.
[0045] It should also be understood that the terminology used ...
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The invention discloses a channel estimation method, medium and equipment based on compressed sensing and deep learning. The base station of the OFDM system sends signals to the user terminal in the downlink in the form of a comb pilot; the downlink The user terminal in the road obtains the received pilot signal y and feeds it back to the base station; the base station of the OFDM system uses the structured sparse characteristics of the sparse channel in the delay domain according to the received pilot signal y , carry out channel estimation based on the AS-JOMP algorithm based on compressed sensing, and obtain the initial estimated channel. Build a noise reduction neural network based on deep learning, use the existing samples to train the DnNet network, and obtain the network parameters Θ; according to the initial estimation obtained by the DnNet network The channel is denoised to obtain the final estimated channel state information. The present invention adopts a lightweight network to make the training process faster, reduce the amount of calculation, and finally obtain accurate CSI estimation.
Description
technical field [0001] The invention belongs to the field of communication technology, and in particular relates to a channel estimation method, medium and equipment based on compressed sensing and deep learning. Background technique [0002] In a Frequency Division Duplexing (FDD) system, since the channel does not have reciprocity, downlink channel information cannot be directly obtained through uplink estimation. In order to obtain downlink channel state information (channel state information, CSI), downlink pilot training must be performed on the downlink channel. In this scenario, the base station sends a pilot to the user, and the user estimates channel information after receiving the pilot and feeds it back to the base station, or the user directly feeds back the received pilot information to the base station, and the base station jointly performs channel estimation. In this case, in order to obtain more accurate channel information, traditional channel information a...
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IPC IPC(8): H04L25/02G06N3/04G06N3/08
CPCH04L25/0254H04L25/0224H04L25/0242H04L25/0256G06N3/08G06N3/048G06N3/045
Inventor 范建存梁培哲
Owner XI AN JIAOTONG UNIV