DSP-free ‘coherent-lite’ transceiver for next generation single wavelength optical intra-datacenter interconnects
Bibliographic record
Abstract
. In addition, we perform a detailed experimental parametric study of the coherent-lite system in which various system parameters are swept such as baud rate, reach, laser power and laser linewidth. Our results verify that the coherent-lite system can be realized using low-cost DFB lasers with linewidths of a few hundred kHz. Moreover, we compare the performance of the coherent-lite system with that of a conventional coherent transceiver leveraging the full DSP stack. Then, we evaluate the power consumption savings achieved by the coherent-lite scheme relative to a classic DSP-based coherent system. Assuming a CMOS node ranging from 28 to 7 nm for DSP implementation, our estimate shows that the coherent-lite scheme can save 95 to 78% of the power consumed by the following subsystems: analog-to-digital converters, chromatic dispersion compensation, 2 × 2 MIMO polarization demultiplexing and carrier recovery. Finally, we compare the power consumption of the coherent-lite scheme with more standard 400G IM-DD systems utilizing either eight or four parallel WDM lanes (8 × 50G and 4 × 100G). The coherent-lite system is found to have similar module power consumption requirements as a corresponding 4 × 100G IM-DD system while bringing the benefits of coherent detection including improved sensitivity and higher spectral efficiency leading to fewer light sources per transceiver module. To the best of our knowledge, this work represents the first experimental demonstration of a DSP-free coherent-lite system for single channel 400G datacenter 10 km interconnects, a potential attractive solution due to its scalability to future 800G and 1.6T intra-datacenter optical interconnects.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".