On the Impact of User Scheduling on Diversity and Fairness in Cooperative NOMA
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Bibliographic record
Abstract
In this correspondence paper, we investigate the problem of user scheduling in a cooperative non-orthogonal multiple access (NOMA) system consisting of a base station, a weak user, and K intermediate users. During each transmission, an intermediate user is scheduled to receive its own message and forward the message destined for the weak user. For this type of cooperative NOMA system, a novel scheduling scheme is proposed to achieve full diversity and scheduling fairness simultaneously. With the consideration that all channels experience independent but non-identically distributed Rayleigh fading, outage probabilities of the weak user and the scheduled intermediate user are derived in closed-form expressions. It is theoretically shown that the proposed scheme provides full diversity for both the weak user and the scheduled intermediate user. Furthermore, theoretical results also demonstrate that the proposed scheme schedules each intermediate user with the same probability 1/K, demonstrating that scheduling fairness is also guaranteed.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it