On the capacity of asynchronous cooperative NOMA in multibeam satellite systems
Bibliographic record
Abstract
In this paper, we investigate the effect of asynchronous reception in multibeam satellite system forward link using our previously proposed cooperative non-orthogonal multiple access (NOMA) technique. Our proposed system is in a dense frequency reuse scheme and based on the cooperation of transmitting beams by targeting one user terminal at a time. The jointly reception of data streams features multiple access channel (MAC), where both data will be recovered by devising successive interference cancellation (SIC). Herein paper we show that in case of asynchronous reception, the propagation of errors through SIC causes huge loss of data frames and throughput degradation. Hence, we propose the channel model of the asynchronous NOMA, and we investigate the system's capacity region, where the information theoretic results show that the asynchronous reception of the data streams can indeed improve the sum-rate upper bounds.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".