Two-Color Scheme for a Multi-Beam Satellite Return Link: Impact of Interference Coordination
Bibliographic record
Abstract
The return link of broadband satellite systems has recently received more attention due to the spread of multi-beam antennas which enable spatial frequency reuse, and thus increase drastically the number of users that can potentially be served by one satellite. While interference isolation has so far been the way to go, with regular four-color frequency reuse scheme, there is a growing interest in densifying the frequency usage as is being done in cellular networks. In this paper, we address the return link radio resource allocation challenges, from spectral resource allocation to user scheduling, including modulation and coding scheme (MODCOD) selection. Our contributions highlight the potential gains of a two-color scheme and shed light on several levers to reap its benefits through interference management. We first consider the possibility to use a two-color scheme, while keeping the MODCOD selection and the scheduling local to each beam and we show that even though it yields a potential performance gain (+16%) with respect to the state of the art (SoA) (based on four colors), it is not viable due to a very high-block loss rate. Therefore, we propose a simple-yet fast and efficient-coordinated MODCOD selection process that alleviates the need of estimating interference and reduces drastically decoding failures. This coordination step offers significant gains (+58%) over the SoA, while leaving the per beam scheduler unchanged. Finally, we formulate a joint user scheduling and MODCOD selection problem across all beams and propose an offline heuristic to solve it efficiently. We obtain a 83% gain with respect to the SoA, but with higher computational complexity. Still, it confirms the great potential of coordinated scheduling.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".