PDL Impact on Linearly Coded Digital Phase Conjugation Techniques in\n CO-OFDM Systems
Bibliographic record
Abstract
We investigate the impact of polarization-dependent loss (PDL) on the\nlinearly coded digital phase conjugation (DPC) techniques in coherent optical\northogonal frequency division multiplexing (CO-OFDM) superchannel systems. We\nconsider two DPC approaches: one uses orthogonal polarizations to transmit the\nlinearly coded signal and its phase conjugate, while the other uses two\northogonal time slots of the same polarization. We compare the performances of\nthese DPC approaches by considering both aligned- and statistical-PDL models.\nThe investigation with aligned-PDL model indicates that the latter approach is\nmore tolerant to PDL-induced distortions when compared to the former.\nFurthermore, the study using statistical-PDL model shows that the outage\nprobability of the latter approach tends to zero at a root mean square PDL\nvalue of 3.6 dB. On the other hand, the former shows an outage probability of\n0.63 for the same PDL value.\n
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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 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".