High-speed data transmission method based on low-orbit satellite network

Through multi-dimensional resource collaborative optimization and predictive switching management, combined with anti-interference coding technology, the problems of low spectrum utilization, long switching interruptions and weak anti-interference capabilities in low-orbit satellite networks have been solved, achieving high-speed and reliable data transmission.

CN120614036APending Publication Date: 2025-09-09NINGXIA ZHONGKE RUIDA PHOTOELECTRIC TECH CO LTD
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Patent Information

Application Number
CN202510942093.8
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-07-09
Publication Date
2025-09-09

AI Technical Summary

Technical Problem

The existing low-orbit satellite network has low spectrum resource utilization, long switching interruption time, and weak anti-interference capability, resulting in spectrum fragmentation, switching delays, and high bit error rates, making it impossible to achieve high-speed and reliable transmission.

Method used

Through multi-dimensional resource collaborative optimization, predictive switching management and anti-interference coding technology, deep reinforcement learning is used for spectrum perception and dynamic resource allocation, combined with distributed intelligent routing and predictive switching, extended Kalman filtering is used for orbit prediction, and polar code cascade coding and interference cancellation technology are combined to improve transmission reliability.

Benefits of technology

The end-to-end transmission rate has been increased by more than 40%, the spectrum utilization rate has been increased to 70%, the switching interruption time has been shortened to 10ms, the bit error rate has been reduced to 10-6, and the transmission delay has been reduced by 35%.

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Abstract

The invention provides a high-speed data transmission method based on a low-orbit satellite network, and relates to the technical field of satellite communication, and the method comprises the following steps: S1, multi-dimensional spectrum sensing and dynamic resource distribution: constructing a three-dimensional interference matrix through a satellite-borne sensor and ground station data, and achieving the dynamic distribution of subcarriers through deep reinforcement learning; a satellite collects the signal power spectral density (PSD) of the current frequency band in real time through a spaceborne sensor, the precision reaches 0.1 dBm / Hz, meanwhile, interference temperature data (the resolution is smaller than or equal to 2 GHz) reported by a ground station are received, interference modeling is strong, and learning distribution is achieved; according to the method, the spectrum efficiency is improved, the spectrum utilization rate is improved from 45% to 75% through dynamic resource allocation, and the single-carrier transmission rate is improved by 60 Mbps; the switching performance is optimized: the interruption time is shortened to 8ms by predictive switching, and the service continuity is improved by 95%; and the anti-interference capability is enhanced: the bit error rate is reduced to 10 <-6 > in a strong interference environment through joint coding modulation, and is improved by one order of magnitude compared with the traditional method.
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