Outage Analysis of Multi-Relay NOMA-Based Hybrid Satellite-Terrestrial Relay Networks
Bibliographic record
Abstract
This article investigates the outage performance of a novel two-user multi-relay non-orthogonal multiple access (NOMA)-based hybrid satellite-terrestrial relay network (HSTRN), in which one user has a direct link to the satellite (termed as the direct-link user), while the other user (termed as the relay-aided user) seeks the help of the direct-link user or the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$K$</tex-math></inline-formula> dedicated decode-and-forward (DF) relays to acquire its desired signal. A relaying protocol and a three-stage relay selection strategy are proposed for minimizing the whole system outage probability (WSOP) and providing full diversity order (DO) for both users. Exact and asymptotic outage probabilities of the considered network are derived, showing that under the proposed relay selection strategy, the relay-aided user, the direct-link user and the whole system each can achieve a DO of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$K + 1$</tex-math></inline-formula> . Finally, numerical results are presented to verify the theoretical analyses, manifest the impacts of key parameters on the system performance, and demonstrate the advantages of our proposed relay selection scheme over other benchmarks.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".