Closed-Form Error Analysis of Dual-Hop Relaying Systems over Nakagami-m Fading Channels
Bibliographic record
Abstract
In this paper we investigate the end-to-end performance of dual-hop relaying systems over non identical-Nakagami-m fading channels. Our analysis considers channel state information (CSI-) assisted relays that just amplify and retransmit the information signal also known as "non-regenerative" relays. New closed-form expressions for the average bit error probability (ABEP) are derived. The proposed expressions apply to general operating scenarios with distinct Nakagami-m fading parameters and average signal to noise ratios (SNRs) between the hops. When the fading parameter is an odd multiple of one half, the ABEP is expressed in terms of hypergeometric functions. When m takes any real non integer value, the obtained results involve the fourth Appell's hypergeometric function. For an arbitrary fading parameter, an analysis of such a scheme is performed using the well known moment-based approach.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".