Low-Complexity Grouping Precoding Based on RSMA for Multibeam Satellite System (Invited Paper)
Bibliographic record
Abstract
Multibeam satellite system can provide seamless information service with high spectrum efficiency (SE). However, adjacent beams will cause severe inter-beam interference due to the reuse of spectrum resources in each beam. The existing interference management schemes regard multibeam satellite system as terrestrial multi-antenna system, and then apply precoding technology to mitigate inter-beam interference, which neglects the characteristics of beam gain attenuation. Meanwhile, the traditional precoding technology for all users will significantly challenge satellites with limited computational resources. Motivated by this, we design a low-complexity grouping precoding (GP) scheme to simultaneously consider beam gain and complexity. Combined with the promising rate-splitting multiple access (RSMA), we further maximize the weighted sum rate (WSR). Then, an alternating optimization algorithm is proposed. Simulation shows that the proposed GP scheme based on RSMA has higher WSR and lower computational complexity than other baseline access modes.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".