Evaluation of bit error rate for packet combining with constellation rearrangement
Why this work is in the frame
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Bibliographic record
Abstract
Abstract In this paper, we propose a method for evaluation of the bit error rate (BER) for packet combining based on constellation rearrangement (CoRe). Such mapping diversity scheme, adopted in the high speed downlink packet access (HSDPA), uses Gray‐mapped constellations and is based on suboptimal accumulation of the reliability metrics generated in each of the transmissions. We present an exact model for the logarithmic likelihood ratios (LLR) obtained by means of the so‐called max‐log approximation, and we show that their conditional probability density functions (pdf) are piecewise Gaussian. We then present the derivation of the uncoded BER and illustrate it with simulation results that confirm our formulation. Finally, we propose simplifications which significantly reduce the complexity of the evaluation method and provide results with a very good accuracy; an extension to transmissions over faded channel is also presented. Copyright © 2007 John Wiley & Sons, Ltd.
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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 | 0.003 | 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 | 0.000 | 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