A simple and efficient timing offset estimation for OFDM systems
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A simple timing offset estimation method for orthogonal frequency division multiplexing (OFDM) systems as a modification to Schmidl and Cox's method (see IEEE Trans. on Comms., vol.45, no.12, p.1613-21, 1997) is presented. By designing the training symbol, the timing metric plateau inherent of Schmidl et al. is eliminated and hence the performance is improved. The performances of the proposed method and of Schmidl et al. are evaluated by computer simulation in terms of the estimator variance. The timing offset estimator of Landstrom, Wilson, van de Beek, Odling and Borjesson (see Proc. Intl. Conf. on Communications, Vancouver, BC, Canada, p.500-5, 1999) is also included in the performance comparison as another reference. The simulation results show that the proposed method achieves significantly smaller estimator variance. Using more samples in calculation of the half symbol energy required in the timing metric is shown to give more robustness against a dispersive channel.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it