Systematic Performance Comparison of (Duobinary)-PAM-2,4 Signaling under Light and Strong Opto-Electronic Bandwidth Conditions
Bibliographic record
Abstract
We present a systematic comparison of PAM-2 (NRZ), Duobinary-PAM-2, PAM-4, and Duobinary-PAM-4 (duo-quaternary) signaling in the context of short-reach photonic communications systems using a Mach–Zehnder modulator as transmitter. The effect on system performance with a relaxed and constrained system’s opto-electronic bandwidth is analyzed for bit rates ranging from 20 to 116 Gb/s. In contrast to previous analyses, our approach employs the same experimental and simulation conditions for all modulation formats. Consequently, we were able to confidently determine the performance limits of each format for particular values of bit rate, system bandwidth, transmitter chirp, and fiber dispersion. We demonstrate that Duobinary-PAM-4 is a good signaling choice only for bandwidth-limited systems operating at relatively high speed. Otherwise, PAM-4 represents a more sensible choice. Moreover, our analysis put forward the existence of transition points: specific bit rate values where the BER versus bit rate curves for two different formats cross each other. They indicate the bit rate values where, for specific system conditions, switching from one modulation to another guarantees optimum performance. Their existence naturally led to the proposal of a format-selective transceiver, a component that, according to network conditions, operates with the most adequate modulation format. Since all analyzed modulations share similar implementation details, signaling switching is achieved by simply changing the sampling point and threshold count at the receiver, bringing flexibility to IM/DD-based optical networks.
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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 | 0.001 |
| 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) | 0.001 | 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 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".