Impulse Response Modeling and Dynamic Analysis for SIMO UOWC Systems Enhanced by RIS-Equipped UUVs
Bibliographic record
Abstract
The marine environment has a large share of more than 70% of the earth, and there is a growing human need for marine information system construction. The existing underwater optical wireless communication (UOWC) has the advantage of high rate and low loss in close range, compared to acoustic and radio frequency (RF) signals with limited bandwidth or huge attenuation. Based on the UOWC framework, this work further introduces and investigates the deployment and dynamic effects of the reconfigurable intelligence surface (RIS) equipped unmanned underwater vehicle (UUV) over a vertical single-input multiple-output (SIMO) UOWC system. The proposed RIS-assisted vertical UOWC system is modeled and verified to solve the problems of beam steering, link obstruction, signal enhancement, and pointing errors. We established, for the first time, the impulse response models by Monte-Carlo ray tracing (MCRT) to study the RIS-assisted vertical underwater channel characteristics, which are further compared under specular reflection and beam steering scenarios. Then, the dynamic analyses of the structural parameters of the RIS-equipped UUV and UOWC system model, including vertical transmission distance, transmitter tilt angle, and RIS position on the link impulse response are analyzed. The MCRT simulation results are fitted with a gamma-gamma function that introduces a temporal splitting parameter to obtain a closed-form expression for the impulse response of the linear/reflective composite link of the RIS-assisted UOWC system. The response temporal dispersion, 3-dB bandwidth, and bit error rate (BER) performances are analyzed. The results show that the composite link of the RIS-assisted UOWC system can improve the 3-dB bandwidth by more than 0.5 times compared with the single linear propagation link, reduce the response temporal dispersion and improve the system BER performance. The proposed impulse response models of the dynamic RIS-assisted UOWC system provide a new perspective for the deployment and application of the future UOWC architecture in a vertical orientation.
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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 | 0.001 |
| 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 | 0.001 | 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".