On-Chip 4×10 GBaud/s Mode-Division Multiplexed PAM-4 Signal Transmission
Bibliographic record
Abstract
Emerging 5G mobile networks and cloud computing applications are driving the demand for an ever-increasing capacity of short-reach optical communications. To meet this demand, mode-division multiplexing (MDM) has been proposed to scale up the bandwidth density by leveraging the spatial modes of an optical waveguide for transmitting multiple optical signals. On the other hand, the use of multi-level pulse amplitude modulation (PAM) can also increase the transmission bandwidth. Therefore, on-chip MDM in conjunction with PAM is an approach to enhance the transmission capacity in a photonic integrated circuit. In this paper, we report a silicon photonic integrated four-channel MDM circuit for high data rate on-chip communications with a low channel crosstalk and small insertion loss. To make the circuit have a small size that supports broadband operation, a mode multiplexer and demultiplexer are realized with the use of cascaded asymmetrical directional couplers on rib waveguides. By incorporating the MDM circuit in an optical communications system, the transmission of a 4 x 10 GBaud/s OOK and PAM-4 signal is experimentally demonstrated. The performance in terms of eye diagrams and power penalties is evaluated. The power penalties for the four-channel OOK transmission are 4.31, 2.38, 1.44 and 3.5 dB at a BER of 10-9. For the four-channel PAM-4 transmission, the power penalties are 7.98, 1.10, 0.66 and 5.14 dB. The required received optical power at a BER (-3) of the 7% overhead-hard decision FEC is -2.6 dBm. The key advantage of the approach is that high-capacity on-chip communications is enabled by the photonic integrated MDM circuit with a small footprint. Since the MDM circuit is implemented on a silicon photonic platform, the system holds high potential for full integration on a single chip.
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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 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".