Adaptive Cooperation Rate-Splitting Multiple Access for Integrated Satellite-Terrestrial Network
Bibliographic record
Abstract
This paper investigates the integrated satellite-terrestrial network (ISTN), which has become a trend in communication development. Since terminals share the same spectrum resources in ISTN, satellite and terrestrial base station jointly provide information service. To manage multiple access interference and provide seamless information, we propose the adaptive cooperation rate-splitting multiple access (AC-RSMA), which has flexible multiple access modes and robust interference management ability. In the AC-RSMA scheme, the satellite adaptively adjusts the level of assistance to the terrestrial base station according to actual needs. Furthermore, we formulate the joint optimization problem to improve the max-min rate. To address the non-convex optimization problem, we introduce an improved alternating optimization algorithm based on weighted minimum mean square error. Simulation results verify that the AC-RSMA scheme has obvious advantages over other baseline schemes.
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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 | 0.001 | 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".