Training-Aided Joint Frame and Frequency Synchronization for THP FTN Coherent Optical Systems
Bibliographic record
Abstract
A joint frame and frequency synchronisation algorithm is proposed for Tomlinson-Harashima precoding-based faster-than-Nyquist (FTN) coherent optical systems. The algorithm is developed by using training sequences based on Golay complementary sequences. Simulation results of a 32-Gbaud FTN system show that the algorithm provides accurate estimates over an optical signal-to-noise ratio (OSNR) range from 10 to 25 dB. When considering the first-order polarisation mode dispersion and using these same training sequences for the equaliser, the algorithm works properly and gives performance similar to when the frequency offset is perfectly known. The required OSNR at a bit error rate of 2×10−2 is about 13 dB and 18.8 dB for 4-QAM and 16-QAM systems, respectively.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".