Probabilistic Shaping in Time-Frequency-Packed Terabit Superchannel Transmission
Bibliographic record
Abstract
To combine the individual benefits of probabilistic-shaping (PS) and time-frequency-packing (TFP), we consider for the first time PS-TFP wavelength-division multiplexing (WDM) superchannels. However, TFP introduces inter-symbol interference (ISI) and/or inter-carrier interference (ICI). Moreover, the presence of reconfigurable optical add-drop multiplexers in the fiber links may further degrade the system performance. In this letter, we efficiently handle such challenges to present PS-TFP superchannels enabling Terabit-per-second data rates. For this, we perform a joint ISI and ICI channel estimation in tandem with turbo equalization to mitigate the interference. We investigate optimizing the parameters in the shaping and packing dimensions to achieve a desired target spectral efficiency. We show through our numerical results that such an optimized PS-TFP transmission leads up to 1.2 dB performance improvement over an unshaped Nyquist WDM system under similar conditions.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".