On the Performance of Cooperative-Diversity Networks with the Nth Best-Relay Selection Scheme
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Bibliographic record
Abstract
In this letter, we consider the adaptive decode-and-forward (DF) and amplify-and-forward (AF) cooperative-diversity systems with the N <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sup> best-relay selection scheme. In the best-relay selection scheme, from the set of M relays the best relay only forwards the source signal to the destination. However, the best relay might be unavailable; hence we might resort to the second, third or generally the Nth best relay. We derive closed-form expressions for the symbol error probability, outage probability and asymptotic error probability. In particular, we derive a closed-form expression for the probability density function (PDF) of the signal-to-noise ratio (SNR) of the relayed signal at the destination node. Then, we find a closed-form expression for the moment generating function (MGF) of the output SNR at the destination. This MGF is used to derive the closed-form expressions of the performance metrics. All these expressions are derived over identical and non-identical Rayleigh fading channels. Results show that with the N <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sup> best relay the diversity order is equal to (M - N + 2) where M is the number of relays.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 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 it