Communication signal modulation identification method based on improved entropy cloud characteristics

Abstract

The invention discloses a communication signal modulation identification method based on improved entropy cloud characteristics, which comprises the following steps: carrying out fast Fourier transform on a signal to be identified, and extracting Shannon entropy, exponential entropy and norm entropy to form a three-dimensional characteristic vector; calculating a digital feature of each entropy feature of the signal to be identified by using a cloud model theory, and obtaining a final entropy cloud feature by using a comprehensive cloud formula; generating a data set by utilizing the characteristics, performing normalization processing, and randomly generating training samples and test samples of each type of modulation signals to obtain a training sample set, a test sample set and a classlabel set; and training an extreme learning machine classifier, and inputting the obtained test sample set into the trained classifier to obtain a final communication signal average identification rate. The method is suitable for feature extraction of analog signals and digital signals at the same time, the calculated amount is small, and obtained signal features are relatively stable. The cloudmodel theory is utilized, so that the signal characteristics are more stable, and the inter-class separation degree is better, and the signal characteristic anti-noise performance is good.

Description

technical field [0001] The invention relates to a communication signal modulation identification method based on feature extraction, in particular to a communication signal modulation identification method with improved entropy cloud features, belonging to the field of communication technology. Background technique [0002] In recent years, wireless communication technology is being widely used in various fields, and plays an important role in both military communication and civilian communication. In this era of rapid development of information technology, in order to adapt to the continuous improvement of people's requirements for information transmission, communication signals need to be transmitted after a series of processing such as modulation. Different wireless communication systems use different modulation methods according to different application backgrounds and needs. . Therefore, the modulation mode of communication signals is one of the most important features...

AI Technical Summary

Problems solved by technology

However, at present, the problem of modulation identification of communication signals under the condition of low signal-to-noise ratio has not been well solved. In the face of the current complex communication environment, the signal is greatly affected by noise. How to extract representative signals under low signal-to-noise ratio The stability characteristics of the

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