A Weighted Queue-Based Model for Correlated Rayleigh and Rician Fading Channels
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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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".