Digital modulation signal identifying method under non-gaussian noise in cognitive radio

A digital modulated signal, cognitive radio technology, applied in the field of communication, can solve the problems of high computational complexity, unsuitable for cognitive radio systems, poor recognition performance, etc., to achieve low computational complexity, reduced computational complexity, and high recognition. rate effect

CN102882820AInactive Publication Date: 2013-01-16XIDIAN UNIV
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Authority / Receiving Office
CN · China
Current Assignee / Owner
Publication Date
2013-01-16
Estimated Expiration
Not applicable · inactive patent

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Abstract

The invention discloses a digital modulation identifying method based on fractional lower order cyclic spectrum related coefficient under the non-gaussian noise in a cognitive radio, and the digital modulation identifying method is capable of solving the problems of bad modulation identifying performance and high calculating complexity under the background of the non-gaussian noise in the cognitive radio. The method comprises the following steps: sampling received signals; calculating relative coefficients rho 1, rho 2, rho 3, rho 4 and rho 5 of projections of fractional lower order cyclic spectrums of the fractional lower order cyclic spectrum calculating signals of the sampled signals at a section of the cycle frequency epsilon=0, a section of frequency f=0, and the cycle frequency epsilon face, and the projection at the frequency f face; and arranging a judgment threshold of a signal set, and identifying the signals in different modulating manners through a classifier based on a judging tree. Under a non-gaussian alpha stably distributed noise, the digital modulation identifying method is relatively high in identification rate, good in stability, and lower in calculation complexity, and is more suitable for a cognitive radio system.
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Description

Technical field

[0001] The invention belongs to the field of communication technology, and specifically relates to a method for identifying digital modulation signals under non-Gaussian Alpha stable distribution noise, which can be used to identify the modulation mode type of digital modulation signals under Alpha stable distribution noise. Background technique

[0002] With the development of communication technology in the direction of wireless and broadband, spectrum resources are becoming increasingly scarce, CR (cognitive radio, cognitive radio) technology has become one of the key technologies to solve this problem. For CR spectrum sensing technology, spectrum sensing must not only accurately detect the appearance of authorized user signals, but also identify its modulation type, and then determine prior information such as authorized users’ business types and business strengths, so as to use these priors. The information enables CR users to discover and use idle spectrum m...

Examples

Embodiment Construction

[0024] The specific implementation steps of the present invention are as follows:

[0025] Step 1. Sampling the received signal y(t) to obtain y[n];

[0026] Step 2. Calculate the fractional low-order cyclic spectrum of y[n]

[0027] For T 0 Is a periodic cyclostationary random signal x(t), and its fractional low-order cyclic autocorrelation function is expressed as:

[0028] R x ϵ ( τ ) = 1 T 0 ∫ - T 0 / 2 T 0 / 2 [ x ( t + τ / 2 ) ] ( b ) [ x * ( t - τ / 2 ) ] ( b ) · e - j 2 πϵt dt

[0029] Where x (b) =|x| b-1 ·X * , * Means conjugate operation, this operation only changes the amplitude of the signal without changing the period information, so the cyclic frequency defined under the second-order cyclic correlation is also suitable for the fractional low-order cyclic correlation; 0 Fourier transform It is called the fractional low-or...