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Erschienen in:
2021 | OriginalPaper | Buchkapitel
Application of Machine Learning in Space–Air–Ground Integrated Network Data Link
verfasst von : Shaofan Zhu, Shuning Wang, Jia Chen
Erschienen in: Communications, Signal Processing, and Systems
Verlag: Springer Singapore
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Abstract
The space–air–ground integrated network is an emerging network architecture integrated by satellite, aerial network, and ground communication, which can provide seamless connection on a global scale. However, the limited energy and spectrum resources cannot meet the growing communication needs, and its high heterogeneity, complex variability affect the reliable and efficient end-to-end transmission of services. In addition, machine learning is widely used. Using machine learning algorithms to solve problems in the space–air–ground integrated network is a new research idea for us. Therefore, this paper first introduces the concept and characteristics of apace–air–ground integrated network, summarizes, and analyzes the application of machine learning algorithms in solving the problems of resource allocation, attack detection, target recognition and location and security authentication of the space–air–ground integrated network, and looks forward to its prospects for development in space–air–ground integrated network.