Hierarchical Full-Duplex Underwater Acoustic Network: A NOMA Approach
Why this work is in the frame
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Bibliographic record
Abstract
Underwater acoustic is the prevalent technology in underwater wireless communications. The sum rate in underwater acoustic channels is limited by the underwater environment properties. This paper attempts to increase the sum rate of underwater channels without utilizing additional resources, through adding a relay and employing full duplex (FD) and non-orthogonal multiple access (NOMA) technologies. The adopted system model has two sensors and two robotic arms communicating with a buoy via a relay. Employing FD-NOMA allows multiple uplink and downlink transmissions to occur simultaneously, using the same time and frequency resources. The main challenge for this deployment is the interference between the transmissions. Interference cancellation techniques, successive interference cancellation and self-interference cancellation, are employed to mitigate the interference due to NOMA and FD, respectively. In order to maximize the sum rate, an optimization problem over the power is formulated and solved as a convex optimization problem. The performance of the system is benchmarked with the performance of the non-relay (NR) aided FD-NOMA and relay-aided (R) half duplex orthogonal multiple access (HD-NOMA). It is shown that R-FD-NOMA always has higher sum rate than NR-FD-NOMA, irrespective of the efficiency of interference cancelation. In addition, it is shown that at efficient interference cancellation, the sum rate of FD-NOMA is higher than HD-OMA.
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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