Bibliographic record
Abstract
Powerline communication (PLC) channels present one of the harshest environments for efficient data transmission. In particular, asynchronous impulsive noise has been known to be one of the strongest impediments to error-free transmission over PLC channels. Most work aimed at ameliorating the degradation due to impulsive noise considers the noise impulses to be independent. In a realistic PLC channel, however, this is rarely true. This paper is concerned with the performance limits on communication over powerline channels where the noise has memory and is modeled using a partitioned Markov chain (PMC) that has been found to be well suited to describe the bursty nature of impulses of the low voltage PLC channel. In particular, expressions are derived for the cutoff rate and the bit error rate of a convolutionally coded narrowband system. They are then verified by comparing with simulation results employing typical PLC parameters, proving the utility of the expressions as a design tool.
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How this classification was reachedexpand
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) | 0.001 | 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 teacher head, 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".