Underwater Optical Wireless Channel Capacity Under Oceanic Turbulence Using Spatial Diversity Techniques
Bibliographic record
Abstract
Conventional spatial diversity techniques do not reduce the severe impact of the main impairments in underwater optical wireless communication (UOWC) such as absorption and scattering. This paper addresses a complete comparison of Multiple-Input/Single-Output (MISO) UOWC systems by using spatial repetition coding (SRC) and transmit laser selection (TLS) strategies over salinity-induced oceanic turbulence in clear ocean and coastal waters. We consider an SRC system with sufficient space between sources to efficiently increase the total transmitted power while satisfying eye-safety requirements by assuming a maximum optical power per source in order to obtain the same ergodic capacity performance of a TLS system with the same number of sources. Novel closed-form expressions and asymptotic results are derived to compute such a performance and optimize the UOWC system design. The presented results demonstrate that MISO UOWC systems achieve a greater ergodic capacity as the number of laser sources increases in all kinds of waters. This improvement is greater when SRC scheme is adopted for all the presented UOWC scenarios except when extreme oceanic turbulence conditions are considered. Monte Carlo simulations verify analytical and asymptotic results.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".