3D MIMO-OFDM system channel estimation method based on convolutional neural network

A technology of 3DMIMO-OFDM and convolutional neural network, which is applied in the field of channel estimation of 3DMIMO-OFDM system based on convolutional neural network, can solve the problems of poor estimation accuracy and occupation of pilot resources, and achieve the effect of improving accuracy

Active Publication Date: 2019-09-20
UNIV OF ELECTRONIC SCI & TECH OF CHINA
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Problems solved by technology

The existing 3D MIMO-OFDM system expands the vertical dimension of the channel on the original MIMO-OFDM system, making the wireless channel more complicated than other situations. If the existing conventional LS algorithm is used (the LS algorithm obtains the

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  • 3D MIMO-OFDM system channel estimation method based on convolutional neural network

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[0045] The specific embodiments of the present invention are described below so that those skilled in the art can understand the present invention, but it should be clear that the present invention is not limited to the scope of the specific embodiments. For those of ordinary skill in the art, as long as various changes Within the spirit and scope of the present invention defined and determined by the appended claims, these changes are obvious, and all inventions and creations using the concept of the present invention are included in the protection list.

[0046] refer to figure 1 , figure 1 Shows the flow chart of the 3D MIMO-OFDM system channel estimation method based on the convolutional neural network; as figure 1 As shown, the method 100 includes steps 101 to 104.

[0047] In step 101, the LS estimated value is calculated by using the pilot value received in the 3D MIMO-OFDM system, and the LS estimated value is preprocessed to obtain a graphical representation of the ...

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Abstract

The invention discloses a 3D MIMO-OFDM system channel estimation method based on a convolutional neural network. The method comprises the following steps: calculating an LS estimation value according to the pilot frequency value received in the 3D MIMO-OFDM system, and preprocessing the LS estimation value to obtain a real part graphical representation and an imaginary part graphical representation; taking the real part graphical representation and the imaginary part graphical representation as the input of a trained real part CECNN model and a trained imaginary part CECNN model respectively, and outputting a complete channel graphical representation respectively; performing normalized reverse operation on the two complete channel imaging representations respectively to obtain real part data and imaginary part data; splicing the real part data and the imaginary part data to obtain a complete channel response value of the 3D MIMO-OFDM system.

Description

technical field [0001] The invention belongs to the technical field of information and communication engineering, and relates to a channel estimation method for a 3D MIMO-OFDM system based on a convolutional neural network. Background technique [0002] Channel estimation is the process of estimating model parameters of an assumed channel model from received data, and the accuracy of channel estimation will directly affect the performance of the entire system. The existing 3D MIMO-OFDM system expands the vertical dimension of the channel on the original MIMO-OFDM system, making the wireless channel more complicated than other situations. If the existing conventional LS algorithm is used (the LS algorithm obtains the channel Response H at the pilot frequency, and interpolating H to obtain a complete channel response value) to perform channel estimation on it, there are defects such as poor estimation accuracy and large occupation of pilot frequency resources. Contents of th...

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Application Information

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IPC IPC(8): H04L25/02
CPCH04L25/0204H04L25/022H04L25/0232H04L25/0254
Inventor 武畅闫康旭金雪敏高璇陈阳吴鹏
Owner UNIV OF ELECTRONIC SCI & TECH OF CHINA
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