Bibliographic record
Abstract
This paper proposes two blind carrier frequency offset (CFO) estimation schemes for differentially modulated orthogonal frequency division multiplexing (OFDM) systems. The proposed schemes estimate the fractional part of the CFO with only two consecutive OFDM blocks, and they exploit two implicit properties associated with differentially modulated OFDM (DOFDM) systems, i.e., the channel keeps constant over two consecutive OFDM blocks, and the DOFDM systems employ an M-ary phase-shift keying constellation. One of the schemes is based on the finite alphabet (FA) constraint and the other one is based on the constant modulus (CM) constraint. They provide a trade-off between the performance and computational complexity. Furthermore, the FA based scheme can achieve better performance at high signal-to-noise ratios at the expense of some additional computational complexity as compared to the existing CM based subspace scheme. The constrained Cramer-Rao lower bound is also derived. Several numerical examples are presented to validate the efficacy of the proposed schemes.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".