Practical Fiber Dispersion-Induced Limitations for 1.6 Tbps (4× 400 Gbps/$\lambda$) O-Band IM/DD Transmission Systems Over 2, 10, 20 and 40 km
Why this work is in the frame
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Bibliographic record
Abstract
With the unprecedented growth of internet traffic, driven mainly by the recent surge of artificial intelligence and data-intensive applications, the need to address the demand for higher capacity datacenter interconnects is pressing. This invited article presents a study and experimental demonstration for achieving the future generation of 1.6 Tbps Ethernet standards. More specifically, this work presents an empirical demonstration of 1.6 Tbps at 2 and 10 km using the 4<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\lambda$</tex-math></inline-formula> LAN-WDM grid with cost and power effective uncooled DFB lasers, sub-1V driving voltages, low half-wave voltage and high-bandwidth TFLN modulators and quantum-dot SOAs. At 2 km, 1.33 Tbps was achieved using 210 GBaud PAM4 under the 25% OH SD-FEC threshold, 1.6 Tbps using 200 GBaud PAM6 under the 25% OH SD-FEC threshold, and 160 GBaud PAM8 under the 20% OH SD-FEC threshold. At 10 km, due to larger CD, 1.6 Tbps was achieved with asymmetrical channel loading where the edge-most channel used 130 GBaud PAM8 while the remaining three channels used 170 GBaud PAM8 where combined provide an aggregate net throughput of 1.6 Tbps under the 20% OH SD-FEC threshold. These results are followed by an analysis of the impacts of CD-induced power fading on data transmission at 2, 10, 20, and 40 km for channel rates of 100, 200, and 400 Gbps. This analysis reveals that channel rates of 400 Gbps are implementable at distances up to 10 km using WDM grids wide enough to accomodate for the use of uncooled lasers, but are practically unfeasible at distances larger than 10 km. Instead, for these longer reaches, channel rates of 100 Gbps are favorable due to lower accumulated CD.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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