Performance bounds for diversity receptions over a new fading model with arbitrary branch correlation
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Bibliographic record
Abstract
Abstract The performance of a new (Beaulieu-Xie) fading model is analyzed using bounds. This recently proposed fading model can be used to describe both line-of-sight and non-line-of-sight components of a fading channel having different diversity orders. We consider the outage probability and error rate performance of maximal ratio combining, equal-gain combining, and selection combining over arbitrarily correlated Beaulieu-Xie fading channels. Closed-form expressions for upper and lower bounds to the outage probability and error rate are obtained, and it is shown that these bounds are asymptotically tight in the high signal-to-noise ratio regime. The analytical results are verified via Monte Carlo simulations. It is shown that the Beaulieu-Xie fading model can be more useful than the Ricean and Nakagami- m fading models in characterizing environments with both line-of-sight and multiple reflected specular components.
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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 | 0.000 |
| 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