Method for recognizing digital modulation signals under Alpha stable distribution noise

Abstract

A method for recognizing digital modulation signals under Alpha stable distribution noise comprises the following steps that received signals x(t) are subjected to preprocessing, baseband signals y(t) are obtained; the generalized second-order cumulant GC 20 and the generalized fourth-order cumulants GC 40 and GC 42 of y(t) are solved; the maximum value gamma max of the spectrum density of a generalized instantaneous phase based on fractional order Fourier transform is solved, and a judging threshold delta of a signal set is set; the feature that F1 is equal to GC20 and a minimum mean square error classifier are used for dividing signals into two types of {2PSK} and {MSK, QPSK and 8PSK}; gamma max and the set threshold delta are used for dividing the signal set of {MSK, QPSK and 8PSK} into two kinds of {MSK} and {QPSK and 8PSK}; and the feature that F2 is equal to GC40 / GC42 and the minimum mean square error classifier are used for recognizing the signals QPSK and 8PSK. According to the method, good recognizing performance on signals containing Alpha stable distribution noise under a low mixing signal to noise ratio can be achieved.

Description

technical field [0001] The invention belongs to the technical field of communication, and in particular relates to a method for identifying digital modulation signals under Alpha stable distributed noise. It can be used to identify BPSK signals, QPSK signals, 8PSK signals and MSK signals under Alpha stable distributed noise. Background technique [0002] The modulation identification of communication signals is the process of determining the modulation mode of the noise-containing signal in a given signal alternative set. This process has important applications in electronic countermeasures in military communications and spectrum monitoring in civil communications. Most existing modulation recognition algorithms in the literature assume that additive noise obeys a Gaussian distribution. However, experimental studies have shown that the man-made electromagnetic noise, natural noise and their joint noise in most radio wave channels often exhibit non-Gaussian properties, and ...

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Problems solved by technology

However, the recognition performance of this method is not ideal under the condition of low signal-to-noise ratio (Liu Mingqian, Li Bingbing, Cao Chaofeng. Digital modulation signal recognition method under non-Gaussian noise [J]. Journal of Electronics and Information Technology, 2013,35(1): 85- 91.)

Zhao Chunhui et al. used the generalized quartic spectrum to conduct modulation recognition research, but the QPSK recognition performance of this method is very poor under the condition of low signal-to-noise ratio (Zhao Chunhui, Yang Weichao. Research on MPSK signal modulation recognition algorithm under Alpha stable distribution noise [J]. Journal of Shenyang University, 2013, 25(1): 10-14.)

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