Performance Analysis of Generalized Selection Combining for Amplify-and-Forward Cooperative-Diversity Networks
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Bibliographic record
Abstract
We consider an amplify-and-forward (AF) cooperative-diversity system where a source node communicates with a destination node directly and indirectly (through multiple relays), in this paper, we analyze the system where N multiple relays that have the strongest signal strength at the destination are selected out of M relays and forward their received data from the source node to the destination node. We derive closed-form expressions for the average symbol error probability, the outage probability, the average channel capacity, the average signal-to-noise ratio (SNR), the amount of fading, and the SNR moments. In particular, closed-form expression for the moment generating function of the SNR at the destination node is determined. Then, we find a closed-form expression for the probability density function (PDF) of the total SNR at the destination. This PDF is used to derive the closed-form expressions of the performance metrics. Simulation results are also given to verify the analytical results. Results show that increasing N will slightly improves the error performance and degrade the outage probability and average channel capacity. In particular, N = M gives the best performance in terms of error performance and N = 1 (the best relay) gives the best performance in terms of outage probability and average channel capacity.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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