Unlock instant, AI-driven research and patent intelligence for your innovation.

A Modulation Mode Recognition Method Based on Deep Learning Applicable to Changing Scenes

A technique of modulation identification and deep learning, applied in the field of modulation identification based on deep learning

Active Publication Date: 2021-08-31
HUAQIAO UNIVERSITY
View PDF8 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to overcome the deficiencies of the prior art, to provide a deep learning-based modulation method identification method suitable for changing scenes that is used to solve the problem of modulation identification in variable SNR scenarios

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A Modulation Mode Recognition Method Based on Deep Learning Applicable to Changing Scenes
  • A Modulation Mode Recognition Method Based on Deep Learning Applicable to Changing Scenes
  • A Modulation Mode Recognition Method Based on Deep Learning Applicable to Changing Scenes

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0048] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments.

[0049]In order to solve the deficiencies existing in the prior art, such as relying on existing prior knowledge and having high computational complexity, the recognition result is easily disturbed, or the recognition accuracy is low, the present invention provides a modulation method recognition based on deep learning suitable for changing scenes method, mainly using the idea of ​​scene division and scene judgment to effectively solve the problem of modulation mode recognition in changing scenes.

[0050] Such as figure 1 As shown, the deep learning-based modulation method recognition method suitable for changing scenarios described in the present invention, considering N C different signal-to-noise ratio SNR, the wireless environment is divided into N C different SNR scenarios For each SNR scenario, different deep learning network models ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The present invention relates to a deep learning-based modulation mode identification method suitable for changing scenarios, which fully considers the variability of SNR in the wireless environment, and effectively solves the problem of variability by applying the two key steps and ideas of scene division and scene judgment. The identification of modulation methods in SNR scenarios has made key progress in dealing with signal analysis and processing in complex and changeable communication systems. The recognition accuracy of the present invention is quite high in the changing SNR scene, which is very close to the recognition accuracy in the specific SNR scene.

Description

technical field [0001] The present invention relates to the field of communication technologies, and more specifically, to a method for identifying modulation modes based on deep learning that is applicable to changing scenarios. Background technique [0002] The purpose of modulation mode identification is to accurately identify the modulation type of the received signal during channel transmission, and provide an important reference for subsequent signal demodulation and analysis. The task of modulation mode identification of communication signals is the most important task in the communication field A critical part, especially in software defined radios and military applications. [0003] Traditional modulation recognition research can be roughly divided into two categories, one is based on decision theory, and the other is based on statistical models. The former relies on existing prior knowledge and has high computational complexity, while the latter has simple theoret...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): H04L27/00
CPCH04L27/0012
Inventor 彭盛亮谢小娟倪艳琴
Owner HUAQIAO UNIVERSITY