Latency Versus Transmission Power Trade-Off in Free-Space Optical (FSO) Satellite Networks With Multiple Inter-Continental Connections
Bibliographic record
Abstract
In free-space optical satellite networks (FSOSNs), satellites connected via laser inter-satellite links (LISLs), latency is a critical factor, especially for long-distance inter-continental connections. Since satellites depend on solar panels for power supply, power consumption is also a vital factor. We investigate the minimization of total network latency (i.e., the sum of the network latencies of all inter-continental connections in a time slot) in a realistic model of a FSOSN, the latest version of the Starlink Phase 1 Version 3 constellation. We develop mathematical formulations of the total network latency over different LISL ranges and different satellite transmission power constraints for multiple simultaneous inter-continental connections. We use practical system models for calculating network latency and satellite optical link transmission power, and we formulate the problem as a binary integer linear program. The results reveal that, for satellite transmission power limits set at 0.5 W, 0.3 W, and 0.1 W, the average total network latency for all five inter-continental connections studied in this work levels off at 339 ms, 361 ms, and 542 ms, respectively. Furthermore, the corresponding LISL ranges required to achieve these average total network latency values are 4500 km, 3000 km, and 1731 km, respectively. Different limitations on satellite transmission power exhibit varying effects on average total network latency (over 100 time slots), and they also induce differing changes in the corresponding LISL ranges. In the absence of satellite transmission power constraints, as the LISL range extends from the minimum feasible range of 1575 km to the maximum feasible range of 5016 km, the average total network latency decreases from 589 ms to 311 ms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.004 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".