A deep learning-based spectrum sensing detection method, device and equipment

Abstract

The present invention provides a spectrum sensing method, device and equipment based on deep learning, by obtaining the observation data set of the signal to be predicted; determining the covariance matrix of the prediction signal according to the observation data set of the prediction signal; inputting the covariance matrix into the trained spectrum The detection network model is used to obtain the predicted spectrum state value through the spectrum detection network model, wherein the spectrum detection network model is obtained by training based on the corresponding relationship between covariance matrix samples and spectrum state real values ​​corresponding to the covariance matrix samples. This embodiment discloses a method that uses the learning ability and data mining ability of deep learning to extract signal features from the received covariance matrix of the signal to be predicted, and detects the features to obtain the spectrum sensing state in the space-ground integrated network. The provided method can effectively improve the spectrum detection performance under low signal-to-noise ratio, and improve the spectrum gap efficiency detected by unauthorized users in the space-ground integrated network.

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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