Impact of Backreflections on Single-Fiber Bidirectional Transmission in WDM-PONs
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Bibliographic record
Abstract
We analyze the system impairment due to beat noises between backreflections and the upstream signal in bidirectional single-fiber wavelength-division-multiplexing passive optical networks (WDM-PONs). The relative intensity noise (RIN), the power penalty caused by the beat noises and the optimum optical network unit (ONU) gain that minimizes this penalty are investigated. In addition to the transmission line loss (TLL), we find that these parameters are also dependent on the linewidth of the seed light, the chirp effect at the ONU and the receiver bandwidth. Different types of laser sources at the optical line terminal (OLT) and various wavelength-independent ONU configurations are intensively investigated to explore those dependencies. It is also found that the systems with remodulation configurations are more tolerant to the backreflections.
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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 | 0.001 |
| 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