
Application of 6G Technology in Satellite-Terrestrial Communications
- 1 Hangzhou Changhe High School, Hangzhou, China, 310052
* Author to whom correspondence should be addressed.
Abstract
In the contemporary digital era, the accelerated dissemination of data and pervasive interconnectivity have emerged as pivotal drivers of social advancement. The increasing demand for high-performance satellite-terrestrial communications systems, which are vital for achieving seamless global coverage, presents a significant challenge. The advent of 6G technology offers a promising avenue for addressing the current limitations of satellite-terrestrial communications. This paper presents a comprehensive review of the potential applications of 6G technology in satellite-terrestrial communication systems, with a particular focus on its capacity to transform these systems. By achieving seamless global connectivity, 6G technology is positioned to address the limitations of current communication technologies and enhance communication speeds, reliability, and efficiency. This research indicates that the integration of satellite and terrestrial communication networks through 6G not only improves the overall efficiency and coverage of the communication network, but also addresses existing challenges such as limited coverage, high latency and scarce spectrum resources. As research and development progresses, it will be essential to facilitate the widespread adoption and evolution of 6G technology in satellite-terrestrial communications through strengthened global cooperation and standardisation.
Keywords
6G, Satellite-terrestrial communication, Dynamic Spectrum Sharing, RIS, LEO.
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Cite this article
Li,L. (2024). Application of 6G Technology in Satellite-Terrestrial Communications. Applied and Computational Engineering,112,15-21.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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Volume title: Proceedings of the 5th International Conference on Signal Processing and Machine Learning
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