Method for effectively recognizing digital modulating signals in non-Gaussian noise

A digitally modulated signal and non-Gaussian noise technology, applied in the field of communication, can solve the problems of inability to identify digitally modulated signals simply and effectively, poor universality, etc.

Inactive Publication Date: 2013-12-18
XIDIAN UNIV
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Problems solved by technology

[0004] The present invention provides a method for effectively identifying digitally modulated signals under non-Gaussian noise, aiming to solve the prob

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  • Method for effectively recognizing digital modulating signals in non-Gaussian noise
  • Method for effectively recognizing digital modulating signals in non-Gaussian noise
  • Method for effectively recognizing digital modulating signals in non-Gaussian noise

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[0041] In order to make the purpose, technical solution and advantages of the present invention more clear, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the invention.

[0042] figure 1 The implementation flow of the method for effectively identifying digitally modulated signals under non-Gaussian noise provided by the embodiment of the present invention is shown.

[0043] The identification methods include:

[0044] Step S101, performing nonlinear transformation on the received signal s(t);

[0045] Step S102, calculate the generalized first-order cyclic cumulant of the received signal s(t) and generalized second-order cyclic cumulants By calculating the characteristic parameters of the received signal s(t) and using the minimum mean square error classifier to...

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Abstract

The invention discloses a method for effectively recognizing digital modulating signals in non-Gaussian noise. Non-linear transformation is performed on a received signal s(t); the generalized first-order cyclic cumulant and the generalized second-order cyclic cumulant of the received signal s(t) are calculated, and a 2FSK signal is recognized by calculating the characteristic parameters of the received signal s(t) and utilizing a minimum mean square error classifier; the generalized second-order cyclic cumulant of the received signal s(t) is calculated, and by calculating the characteristic parameters of the received signal s(t) and utilizing the minimum mean square error classifier, the number of spectral peaks of a generalized cyclic cumulant magnitude spectrum is detected so that a BPSK signal and an MSK signal can be recognized; the generalized fourth-order cyclic cumulant of the received signal s(t) is calculated, and a QPSK signal, an 8PSK signal and other signals are recognized through the calculated characteristic parameters and the minimum mean square error classifier. The method for effectively recognizing digital modulating signals in non-Gaussian noise solves the problem that signals in Alpha stable distribution noise do not have second or higher order statistics, effectively recognizes the digital modulating signals and can be used for recognizing the modulation mode of the digital modulating signals in the Alpha stable distribution noise.

Description

technical field [0001] The invention belongs to the technical field of communication, in particular to a method for effectively identifying digital modulation signals under non-Gaussian noise. Background technique [0002] Digital signal modulation recognition has very important applications in both military and civilian fields. Traditional digital modulation recognition assumes that the background noise obeys a Gaussian distribution, but in actual wireless communication systems there are often some non-Gaussian distributed noises, which have significant spike-like waveforms and thick probability density function tails. The researchers found that a more effective noise model to describe such non-Gaussian random signals is the Alpha-stable distribution model. Therefore, it is of great practical engineering significance to study the digital signal modulation recognition method under the background of Alpha stable distributed noise. [0003] In recent years, scholars have don...

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Application Information

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IPC IPC(8): H04L27/00
Inventor 李兵兵马洪帅刘明骞杨吉
Owner XIDIAN UNIV
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