Space-Air-Ground FSO Networks for High-Throughput Satellite Communications
Bibliographic record
Abstract
The next generation of satellite communication systems aims to achieve terabit-per-second throughput. Because of the limited spectrum available, traditional radio frequency (RF) communication links cannot provide such high throughput. Free-space optical (FSO) transmission is a possible alternative that has recently gained increased attention in the satellite community. However, FSO communications are vulnerable to the severe effects of atmospheric turbulence, such as beam-wandering-induced pointing errors and beam scintillation. To successfully remedy such effects, we propose a space-air-ground (SAG) FSO network with a strategically deployed high-altitude platform acting as a relay. We show that such a design can substantially mitigate the effects of atmospheric turbulence, especially when the satellite zenith angle is relatively high. Then we present a novel SAG satellite communication network that integrates the suggested SAG-FSO transmission and conventional hybrid single-hop FSO/RF transmission to improve overall system reliability and performance even further. The numerical results clearly show the potential of the proposed, highly innovative SAG-FSO network architecture.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".