Perspectives on and the road towards 100 Gb/s TDM PON with intensity-modulation and direct-detection
Bibliographic record
Abstract
We assess the status of current generation 25G and 50G time division multiplexed passive optical network (TDM PON) technologies based on leveraging the cost efficiencies of the Ethernet intra-datacenter ecosystem. As a first step towards 100G TDM PON, we predict the real-world impact of a flexible modulation enhancement to 50G PON, whereby four-level pulse amplitude modulation (PAM4) symbols can be transmitted at the same symbol rate as 50 Gb/s PAM2, but only where excess margins permit. We find that sufficient margins are likely to exist to allow for a majority of future 50G PON optical network units to operate at 100 Gb/s PAM4. Next, we look at the options for a 100G PON capable of supporting the full loss budget and reach requirements. There is no technical risk if coherent technology is adopted, but intensity-modulation and direct-detection (IM-DD) will provide lower complexity, lower cost, and lower power dissipation. We evaluate this option and conclude that by following IM-DD Ethernet optics to 100 GBd, single wavelength IM-DD will continue to be feasible for 100G PON and will be a strong contender for the next generation of PON after 50 Gb/s.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".