Predictive Optical Feeder Link (OFL) Planning in Space-Ground Integrated Optical Networks (SGIONs) Using Bipartite Matching Algorithms

Abstract

Optical feeder links (OFLs) are emerging as a promising solution to overcome the arising data bottleneck of conventional radio frequency (RF) feeder links in satellite-ground integrated optical networks (SGIONs). However, their deployment is challenged by cloud-induced outages and long acquisition times for reestablishing disrupted links. Assuming cloud coverage can be forecast reliably over short time horizons, this paper introduces a predictive link planning framework that dynamically optimizes OFL topology to maximize continuous data transfer while minimizing the number of link handovers. Real-world cloud coverage data from a ground station site are used to evaluate the approach. Simulation results show that the predictive link planning significantly extends the overall data transfer duration compared to non-predictive strategies, while maintaining performance close to that of fully flexible link reassignment. We consistently observe high network capacity with a low handover rate. These findings underscore the effectiveness of predictive, cloud-aware planning for mitigating weather-induced outages in future optical satellite communication systems.