Coverage Analysis of Cooperative NOMA in Millimeter Wave Networks
Bibliographic record
Abstract
This letter analyzes the coverage probability of a cooperative non-orthogonal multiple access (NOMA) millimeter wave (mmWave) network consisting of source (S) and destination (D) pair without a direct link. A cooperative relay (R), which is selected from a set of active users, helps D to receive its data. The transmission from S to R is based on NOMA, by which R can receive its own data and D's data simultaneously. Two relay selection schemes are developed. For each scheme, the favorable users that meet a rate threshold are selected to be in the decoding set. Then from the decoding set, a relay is selected that is nearest to S (in the 1st selection scheme), or nearest to D (in the 2nd selection scheme). For both schemes, we characterize the spatial density (location dependent) of decoding sets and derive the coverage probability. Both schemes outperform orthogonal multiple access. We also derive the coverage of randomly picking a relay (i.e., no selection) to quantify the benefits of relay selection in mmWave NOMA.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".