Bibliographic record
Abstract
Irregular low-density parity-check coding is studied for frequency selective channels and discreet multi-tone (DMT) systems that are used for power-line channels. To let a long block-length code with a practical buffer delay, we protect all the symbols that are transmitted in a DMT symbol with one code. The main challenge, therefore, is the varying signal to noise ratio in different frequency tones, which normally necessitates using different codes for different frequency tones (according to their signal to noise ratios). We show that if this non-uniformity is considered in the code design process, low-density parity-check codes that approach the capacity of such frequency selective channels can he found. Compared to codes that are designed for uniform channels, our codes have a significantly smaller gap from the capacity. As an extreme case, we focus on systems that - for reducing signalling and detection complexity - use only one non-binary modulation in all frequency tones. Therefore, the soft information at the receiver experiences a dramatic non-uniform quality from bit to bit. Surprisingly, even in this case, very close-to-capacity performance can be obtained
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".