Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Method for identifying common digital modulation signal based on cyclic spectrum correlation

A technology of digital modulation signal and identification method, which is applied in the field of common digital modulation signal identification based on cyclic spectrum correlation, and can solve the problem that the field of communication signal modulation identification is not popularized.

Inactive Publication Date: 2016-06-29
徐州中矿康普盛通信科技有限公司
View PDF3 Cites 11 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Although the theory of cyclic spectrum correlation has been widely used in the analysis of non-stationary signals in various fields, it is not popular in the field of communication signal modulation recognition at present.

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
  • Method for identifying common digital modulation signal based on cyclic spectrum correlation
  • Method for identifying common digital modulation signal based on cyclic spectrum correlation
  • Method for identifying common digital modulation signal based on cyclic spectrum correlation

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0065] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0066] like figure 1 As shown, the specific implementation steps of the commonly used digital modulation signal identification method based on cyclic spectrum correlation of the present invention are as follows:

[0067] (1) Since the present invention introduces the link of accumulating and calculating the average in the original spectrum correlation estimation algorithm, it is necessary to carry out equal parts after the original signal is sampled, and the sampling frequency is set to T S Is the sampling interval in the time domain, and generally takes 1024 sample points for each equal portion of the signal;

[0068] (2) Cyclic spectrum correlation theory is a theoretical tool proposed by Gardner for non-stationary signal analysis, and its estimation algorithm based on frequency domain smoothing is defined as:

[0069] ...

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 invention discloses a method for identifying a common digital modulation signal based on cyclic spectrum correlation. The reliability of signal analysis is improved by utilizing the noise-proof feature of a signal cyclic spectrum; the steps of alpha section wavelet de-noising and averaging through superposition are introduced into a calculation process of a signal spectral correlation function, so that the random fluctuation caused by the limited sampling number and the external disturbance in an original spectrum correlation estimation algorithm result is effectively weakened to facilitate identification and extraction of modulation features; and meanwhile, an alpha section and an f section of an obtained spectral correlation diagram are computed by utilizing signal spectral correlation, and appropriate features and parameters (such as a ratio of maximum absolute values of spectral correlation functions, namely the alpha section and the f section, the number of intense lines of the alpha section, a coefficient of fluctuation of the alpha section, the normalized area of the f section, a predominance ratio of spectral lines of the alpha section and the like) are selected to construct a classification method to identify the modulation mode of the communication signal.

Description

technical field [0001] The invention belongs to the field of communication signal modulation identification, in particular to a common digital modulation signal identification method based on cyclic spectrum correlation. technical background [0002] The identification of the modulation mode of communication signals is an important link between signal acquisition and demodulation. It plays an important role in both military and civilian communication fields, especially in the management of dynamic radio spectrum and the identification of unknown interference. middle. In addition, the identification of the modulation mode of communication signals is also the basis for building software radio or cognitive radio applications, and also provides technical support for multi-system communication interconnection applications. [0003] Signal power spectrum analysis based on Fourier transform is a common and classic analysis method for stationary signals. Through the power spectrum...

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 Applications(China)
IPC IPC(8): H04L27/00
CPCH04L27/0012
Inventor 李世银沈胜强
Owner 徐州中矿康普盛通信科技有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com