🤖 AI Summary
This study addresses the challenges of weather-induced disruptions in free-space optical (FSO) links and stringent on-board cache and energy constraints in low Earth orbit (LEO) hybrid radio frequency (RF)/FSO satellite networks. To tackle these issues, the authors propose an interference-aware transmission scheduling mechanism that integrates a weather-dependent FSO outage model with finite-buffer queueing analysis to jointly optimize end-to-end throughput and cache capacity allocation. Innovatively, instead of increasing transmit power, the scheme dynamically adjusts scheduling priorities to maintain multi-hundred-Gbps data rates while substantially reducing buffer requirements and packet loss. Simulation results demonstrate that the proposed approach effectively enhances system throughput under practical operational constraints, enabling efficient and reliable high-speed data transmission.
📝 Abstract
Low Earth Orbit (LEO) satellite networks are increasingly adopting laser (Free Space Optics, FSO) links to provide high-capacity communications. Although laser inter-satellite links offer high throughput and low latency, RF up- and downlinks remain necessary to maintain connectivity during optical outages caused by adverse atmospheric conditions. In such hybrid link scenarios, satellite buffer design remains a key challenge, since up- and downlink traffic must be buffered and forwarded among satellite nodes. The hybrid RF/FSO scenario requires careful transmission scheduling, especially at envisioned optical transmission rates of 100Gb/s and beyond, making buffer sizing critical under strict onboard energy and weight constraints. Thus, this paper analyzes throughput performance and buffer sizing in hybrid RF/laser satellite networks with finite buffer capacity, interference-aware scheduling, and weather-dependent laser link outage probabilities. Numerical results indicate that laser communications bring significant performance gains. Instead of increasing the transmission power of the satellite to maximize the throughput, we can select a suitable transmission scheduling priority to achieve a maximum throughput, while minimizing the buffer requirement, and lowering packet loss probability under realistic operational conditions and constraints.