Unified Performance Analysis of Two Hop Amplify and Forward Relaying
Bibliographic record
Abstract
Abstract—Wireless relay networks have been studied extensively in the recent literature. Amplify and forward (AF) is one of the most widely used type of relaying. Even though special cases such as channel-noise-assisted, channel-assisted and blind relay modes have been analyzed, a unified performance analysis seems to be not available. In this paper, we present unified performance analysis results for two-hop AF relaying over Nakagami-m fading nonidentical source-to-relay (S→R) and relay-to-destination (R→D) links. A general model for the received signal-to-noise ratio, which covers channel-noise-assisted, channel-assisted and blind relay configurations as special cases, is developed. Closed-form expressions are then derived for the cumulative distribution function (cdf), probability density function (pdf), and moment generating function (mgf). Exact results are derived for symbol error rate of special cases. All results are verified through Monte Carlo simulation. I.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".