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Carrier frequency offset estimation method based on convolution neural network

A technology of convolutional neural network and carrier frequency offset, which is applied in the field of carrier frequency offset estimation based on convolutional neural network, can solve problems such as difficulty in adapting to digital communication signal modulation patterns, and facilitate training, improve training speed, and enhance adaptability Effect

Active Publication Date: 2019-01-25
36TH RES INST OF CETC
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Problems solved by technology

Most of the existing carrier frequency offset estimation methods are designed for special signal types, and it is difficult to adapt to all digital communication signal modulation styles

Method used

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  • Carrier frequency offset estimation method based on convolution neural network
  • Carrier frequency offset estimation method based on convolution neural network

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Embodiment Construction

[0029] Preferred embodiments of the present invention will be specifically described below in conjunction with the accompanying drawings, wherein the accompanying drawings constitute a part of the application and are used together with the embodiments of the present invention to explain the principle of the present invention.

[0030] A specific embodiment of the present invention discloses a carrier frequency offset estimation method based on a convolutional neural network. like figure 1 shown, including the following steps:

[0031] Step S1, acquiring signal sampling data;

[0032] Specifically, under each preset frequency offset, the complex baseband signal is simulated to form a sample, and the sample signal is converted from analog to digital by an analog-to-digital converter to form a digital signal, and then the digital signal is Sampling is carried out, the number of sampling points is L, and the complex baseband sampling signal is obtained, and the real part (in-pha...

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Abstract

The invention relates to a carrier frequency offset estimation method based on a convolution neural network, belonging to the technical field of signal processing, which solves the problem that the frequency offset in the prior art cannot be estimated accurately and is difficult to adapt to all digital communication signal modulation patterns. A carrier frequency offset estimation method based onconvolution neural network includes the following steps: acquiring signal sampling data; constructing a convolution neural network based on the signal sampling data; training the constructed convolution neural network to obtain a convolution neural network model based on carrier frequency offset; the signal carrier frequency offset is estimated using the convolution neural network model based on the carrier frequency offset. Accurate estimation of carrier frequency offset is realized, and it can be adapted to different modulation signals.

Description

technical field [0001] The present invention relates to the technical field of signal processing, in particular to a method for estimating carrier frequency offset based on a convolutional neural network. Background technique [0002] In the actual wireless communication system, due to the influence of the unstable oscillator, limited precision and Doppler frequency shift at the receiving end, the received signal has a certain frequency offset, which affects the performance of the receiver. Therefore, in order to effectively reduce the impact of frequency offset on system performance during coherent demodulation and recovery of transmitted unknown data, it is necessary to use an effective frequency offset estimation algorithm to accurately estimate and compensate the frequency offset value. Most of the existing carrier frequency offset estimation methods are designed for special signal types, and it is difficult to adapt to all digital communication signal modulation modes. ...

Claims

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Application Information

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IPC IPC(8): H04L27/00
CPCH04L27/0014H04L2027/0026
Inventor 郑仕链杨小牛周华吉
Owner 36TH RES INST OF CETC
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