Polarization-Time Code and 4$\,\times\,$4 Equalizer-Decoder for Coherent Optical Transmission
Bibliographic record
Abstract
A linear polarization-time code in conjunction with an adaptive multi-tap 4 4 joint equalizer-decoder is proposed to average the effects of polarization-dependent impairments on two polarizations. For the first time in the context of polarization-time coding, there is no assumption of polarization-dependent loss (PDL) of knowledge at the receiver. This method compensates the performance loss penalty due to polarization-dependent impairments in polarization division multiplexed coherent optical single-carrier systems. Using the proposed method, a 1.25-dB optical signal-to-noise ratio gain is achieved in the presence of 6-dB PDL. The proposed 44 joint equalizer-decoder has twice the complexity of conventional time-domain equalizers. Further changes at the receiver including the demodulator are not required. Since the outputs of the equalizer are noisy quadrature phase shift keying signals, adoption of the method to work with both hard and soft forward error corrections is straightforward.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".