Spectrum sensing detection method, device and equipment based on deep learning

Abstract

The invention provides a spectrum sensing method, device and equipment based on deep learning. The method comprises the steps of obtaining a to-be-predicted signal observation data set; determining acovariance matrix of the prediction signal according to the prediction signal observation data set; and inputting the covariance matrix into a trained frequency spectrum detection network model, and obtaining a predicted frequency spectrum state value through the frequency spectrum detection network model, the frequency spectrum detection network model being obtained by training based on a corresponding relationship between a covariance matrix sample and a frequency spectrum state true value corresponding to the covariance matrix sample. According to the method disclosed by the embodiment of the invention, the signal features are extracted from the covariance matrix of the received to-be-predicted signal by using the learning ability and the data mining ability of deep learning, and the features are detected to obtain the spectrum sensing state in the space-ground integrated network; according to the method provided by the embodiment of the invention, the spectrum detection performanceunder a low signal-to-noise ratio can be effectively improved, and the spectrum gap efficiency detected by unauthorized users in the space-ground integrated network can be improved.

Description

[0001] technology neighborhood [0002] The present invention relates to the field of communication technology, in particular to a deep learning-based spectrum sensing detection method, device and equipment. Background technique [0003] In order to supplement ground communication connections and realize the possibility of ubiquitous and unlimited connections, space-air-ground integrated networks (SAGIN) are proposed to provide seamless wide-area connections for improving and providing flexible end-to-end side service. In order to meet the needs of wireless devices and maximize the use of network resources, dynamic spectrum sharing is proposed to promote the application of underutilized spectrum to broadband communication services. Spectrum sensing, as the core component of dynamic spectrum access, aims to obtain the spectrum usage in geographical areas, so that unlicensed users can use the detected spectrum gaps to improve spectrum efficiency. [0004] In recent years, many...

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Problems solved by technology

[0006] In view of the deficiencies in the above-mentioned prior art, the purpose of the present invention is to provide a spectrum sensing method, device and equipment based on deep learning, which overcomes the problem of spectrum awareness in the space-ground integrated network under the low signal-to-noise ratio in the prior art. Defects with low detection accuracy

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