Channel model for wideband time-varying underwater acoustic systems
Bibliographic record
Abstract
In this paper a wideband underwater acoustic (UWA) channel simulator is developed based on the geometry of the system deployment and by considering the statistics of the random amplitude variation of the channel. This channel simulator is capable of modeling any relative motion between the transmitter and receiver. The delays of multipath arrivals are calculated based on the geometrical and physical parameters of the deployment. The time-varying fractional delay line (TVFDL) is utilized as a flexible and low-complexity software tool to model time-scaling observed on individual paths. The fading characteristics of the channel which is extracted from the measurements is utilized to model the time-varying amplitudes of paths. Also, an orthogonal frequency division multiplexing (OFDM) system is tested throughout a sea trial. The geometrical and statistical parameters of the sea trial are utilized to test the OFDM system using the proposed channel simulator. The bit error rate (BER) of the system is calculated in both measurements and simulations and it will be shown that the assessment of the communication performance realized using simulations is very close to that of the measured performance.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".