Analysis and experimental demonstration of novel 8PolSK-QPSK modulation at 5 bits/symbol for passive mitigation of nonlinear impairments
Bibliographic record
Abstract
We propose a new modulation format providing 5 bits of information per recovered symbol while maintaining constant the total optical power. The proposed format applies a simple power constrain to the DP-8QAM format. This modulation format provides a passive way to mitigate nonlinear impairments due to Kerr effects occurring during propagation, and most specifically in the first 40 km. This report presents, to the authors' knowledge, a new transmission format using solely phase and polarization as modulation methods. The performance of this format, named 8PolSK-QPSK, is experimentally compared with that of the DP-8QAM format as both require equal transmitter complexity and implementation penalty, at the expense of a 20% increase in signaling baud rate. The greater nonlinear tolerance of this format is experimentally demonstrated. Moreover, thorough analysis of the Manakov-PDM propagation equation applied to both formats provides analytic explanation of the 8PolSK-QPSK's improved performance. The constant power property of the symbol set of the proposed format mitigates self- and cross-phase modulation (SPM, XPM) nonlinear effects and is experimentally validated over a long-haul transmission system in a WDM scenario. A total throughput of 7 × 129 Gbps is maintained for the transmission format comparison. Simulation of the same transmission system allows separate analysis of the strength of SPM, XPM and Cross-Polarization Modulation (XPolM) nonlinear effects and demonstrate reduced nonlinear impairments for the proposed format in the first span. We show an experimental reduction of the required OSNR for a BER threshold of 1.4 × 10(-2) of 0.5 dB for 8PolSK-QPSK compared to DP-8QAM in back-to-back. After 1920 km of SMF fiber, we demonstrate a required OSNR (ROSNR) diminution for increasing launch power, allowing a ROSNR relief of 0.95 dB at optimal launch power of -1 dBm for the proposed format. Using the same threshold, we show an increased reach by more than 34%, or 975 km, at optimal launch power. We also demonstrate that the relative reach increase for 8PolSK-QPSK compared to DP-8QAM monotonically increases with increasing BER threshold and that the BER growth with distance, after the first span, is equal for both formats.
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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) | 0.001 | 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".