A Novel Postfix Synchronization Method for OFDM Systems
Bibliographic record
Abstract
This paper presents a novel synchronization method for OFDM systems that uses preambles containing two identical training parts followed by a flipped postfix (FlP). Specifically, the proposed preamble for AWGN channels consists of a flipped cyclic prefix (FCP) and two identical training parts followed by a FlP The preamble for ISI and fading channels is similar except that the FCP is replaced by a zero padding prefix (ZPP). By using these FlP-based preambles, the accuracy of the timing offset estimator is highly improved without increasing the computation complexity. Performance of the proposed method is evaluated by simulation over AWGN, ISI and fading channels in terms of the mean and variance of the time offset and carrier frequency offset (CFO) estimators. Results show the new time offset estimator has a quite small variance and its mean value is quite close to the exact start point. Comparison to Schmidl-Cox and Minn's classical synchronization methods illustrates the advantages of the proposed method.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".