Adaptive Pre/Post-Compensation of Cascade Filters in Coherent Optical Transponders
Why this work is in the frame
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Bibliographic record
Abstract
We propose an adaptive joint pre- and post-compensation to correct the filtering effects caused by cascading reconfigurable optical add drop multiplexers (ROADMs). The improvement is achieved without using additional hardware (HW) on the link or within the signal processor in the transponders. Using Monte Carlo simulations, the gradient-descent based method shows an improvement of 0.6 dB and 1.1 dB in the required optical signal-to-noise ratio (R-OSNR) at the threshold pre-decoder bit error rate (BER) of 0.02 versus pre-compensation only in the linear and nonlinear operating region of fiber respectively. We experimentally verified the method with lab measurements in the presence of heavy filtering and optical impairments. We observed a gain up to ~0.4 dB compared to typically used pre-compensation only. Additionally, other tangible system benefits of our method are listed and discussed.
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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 | 0.000 |
| 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