Simple and efficient frequency offset tracking and carrier phase recovery algorithms in single carrier transmission systems
Bibliographic record
Abstract
In this paper, we propose a low-complexity and efficient carrier recovery algorithm for single carrier transmission systems that is capable of tracking frequency offset (FO) variations. Working as a FO tracking estimator, the algorithm demonstrates good accuracy in simulation and a FO drift of up to 200 MHz/μs can be compensated with minimal degradation in a QPSK system. In 112 Gb/s dual polarization (DP) QPSK experiments, the algorithm recovers a data sequence having >80 MHz of FO drift within 250 μs, providing better performance than a one-time estimator. In a regime that utilizes parallel processing of the data, we further demonstrate FO tracking and carrier phase recovery (CPR) using only one of the streams in a parallelized configuration, and we apply the carrier information to recover neighbouring streams directly. Consequently, the complexity of both the FO tracking and the CPR is further reduced.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".