A Weighted Queue-Based Model for Correlated Rayleigh and Rician Fading Channels
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Bibliographic record
Abstract
A new channel model for binary additive noise communication channel with memory, called weighted queue-based channel (WQBC), is introduced. The proposed WQBC generalizes the conventional queue-based channel (QBC) such that each queue cell has a different contribution to the noise process, i.e. the queue cells are selected with different probabilities. Suitably selecting the modeling function, the generalization introduced by the WQBC does not increase the number of modelling parameters required compared to the QBC. The statistical and information-theoretical properties of the new model are derived. The WQBC and the QBC are compared in terms of capacity and the accuracy in modeling a family of hard decision frequency-shift keying demodulated correlated Rayleigh and Rician fading channels. It is observed that the WQBC requires a much smaller Markovian memory than the QBC to achieve the same capacity, and provides a very good approximation of the fading channels as the QBC for a wide range of channel conditions.
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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 | 0.000 | 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