Non-Orthogonal Broadcast and Unicast Transmission Based on Novel Centralized Frequency Reuse for Multibeam Satellite System
Bibliographic record
Abstract
The multibeam satellite system is crucial for the next generation communication, providing seamless and various information services, such as broadcast and unicast messages. However, catering to the burgeoning number of users within limited spectrum resources presents formidable challenges. In response, rate-splitting multiple access (RSMA) has emerged, leveraging non-orthogonal transmission and precoding strategies concurrently. Therefore, we devise the non-orthogonal broadcast and unicast (NOBU) joint transmission framework using RSMA. Furthermore, amalgamating traditional precoding with frequency reuse techniques, we propose a novel centralized frequency reuse strategy, exhibiting commendable performance alongside reduced computational complexity. Furthermore, we maximize the weighted sum rate (WSR) and introduce an improved alternating optimization algorithm, adept at converting intricate non-convex problem into tractable convex counterpart. Simulation outcomes demonstrate that our proposed schemes have significant improvements in WSR performance and are promising for various practical applications.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".