Modeling a shallow water acoustic communication channel using environmental data for seafloor sensor networks
Bibliographic record
Abstract
Abstract Development of communication channels for underwater sensor networks holds many unique challenges. Communication near the bottom of the ocean is no exception as the effects of reflection and refraction greatly affect how acoustic waves travel between a source and an intended receiver. Deployment and testing in the ocean are difficult and expensive; thus there is a strong reliance on models to aid in design and development of a potential network. Since each ocean region can present very unique challenges, it is of great value to model an environment based on real environmental parameters whenever available. A well prepared channel model will provide the ability to show channel capacity as it relates to node positions, as well as showing the performance of modulation techniques to an environment with propagation characteristics and path arrivals. This channel model will also be implementable into a simulation package to allow for high quality simulation of higher level protocols. The proposed method has proved to be a useful tool in modeling a particular environment and provides insight into underwater sensor node placement and modulation. Copyright © 2009 John Wiley & Sons, Ltd.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".