Optical feeder links (OFLs) are a key enabler for high-capacity satellite-ground integrated optical networks (SGIONs), but their performance in geostationary earth orbit (GEO) systems is strongly limited by cloud-induced outages and long acquisition and handover times. This paper investigates predictive OFL scheduling in GEO SGIONs where both satellites and optical ground stations are equipped with multiple transceivers, enabling enhanced spatial diversity. We propose a centralized link scheduling framework that exploits short-term cloud forecasts to maximize network capacity while maintaining operational stability under multi-aperture constraints. The resulting scheduling problem is formulated as a mixed-integer linear program (MILP) and incorporates a link-retention mechanism to reduce handovers across scheduling epochs. Simulation results based on real cloud coverage data show that multi-transceiver architectures significantly improve average capacity and robustness. Moreover, achievable capacity scales nearly linearly with the number of transceivers per node, revealing a tunable trade-off between capacity and stability.
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Optical feeder links (OFLs) are a key enabler for high-capacity satellite-ground integrated optical networks (SGIONs), but their performance in geostationary earth orbit (GEO) systems is strongly limited by cloud-induced outages and long acquisition and handover times. This paper investigates predictive OFL scheduling in GEO SGIONs where both satellites and optical ground stations are equipped with multiple transceivers, enabling enhanced spatial diversity. We propose a centralized link scheduli...
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