Full-Duplex Cooperative NOMA With Signal Space Diversity: Minimizing SIC Operations
Bibliographic record
Abstract
In this letter, a novel signal-space-diversity-based full-duplex (FD) cooperative non-orthogonal multiple access (SFD-CNOMA) system is introduced for a multi-user scenario. In the proposed system, cell-centered and cell-edge users’ information will be multiplexed in the superimposed signal’s in-phase and quadrature components. This reduces successive-interference-cancellation (SIC) operations, detection delay, and complexity compared to conventional FD cooperative NOMA (CFD-CNOMA). An analytical framework is introduced to assess the average sum rate, outage probability, and diversity order for both perfect and imperfect SICs, considering order statistics. Comparative analysis demonstrates that SFD-CNOMA outperforms CFD-CNOMA under both perfect and imperfect SICs.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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 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".