Extensive simulation of fibre non‐linearity mitigation in a CO‐OFDM‐WDM long‐haul communication system
Bibliographic record
Abstract
In this study, a performance comparison of fibre non‐linearity mitigation is performed in the context of 10 and 20 Gb/s coherent optical orthogonal frequency‐division multiplexing and wavelength division multiplexing (CO‐OFDM‐WDM). The authors compare two regression methods based on the third‐order Volterra series and least mean square algorithm in terms of the bit error rate (BER) for different transmission distances and modulation formats. They also evaluate the BER as a function of the number of OFDM subcarriers for the Volterra‐based non‐linear equaliser (VNLE). In addition, by increasing the order of the VNLE from third‐order to fifth‐order series, a significant increase of performance is obtained for 100 Gb/s CO‐OFDM‐WDM system. Likewise, a comparison study of 16‐QAM 40 Gb/s CO‐OFDM system is performed as a function of Q‐factor for support vector machine, Volterra equaliser and linear equaliser, respectively.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".