Cross‐layer design of T‐ARQ and adaptive modulation and coding in a spectrum sharing with cooperative relaying system
Bibliographic record
Abstract
This study presents an analysis for a cross‐layer design of a combined adaptive modulation and coding (AMC) with a truncated automatic repeat request (T‐ARQ) scheme in an underlay spectrum sharing cognitive radio employing an amplify‐and‐forward cooperative relaying system. The considered AMC employs a coded M‐ary quadrature amplitude modulation scheme combined with a T‐ARQ to improve the performance of the secondary user (SU) system in the considered cognitive radio. To establish the performance analysis, the cumulative distribution function (CDF) of the end‐to‐end signal‐to‐noise‐ratio at the receiver side of the SU system is derived. Then, using the derived CDF, closed‐form expressions are derived for three important performance metrics: the average spectral efficiency, the average packet‐error‐rate, and the outage probability. To evaluate the performance of the considered system, numerical results obtained from the derived closed‐form formulas are presented and compared. In addition, to verify the validity of the analysis, Monte–Carlo simulation results are also provided.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".