Computational analysis demonstrates improved capacity in mobile underwater acoustic networks, indicating that two-stage stochastic programming effectively mitigates marine interference.
Key Points
To develop a unified resource allocation framework for mobile underwater acoustic networks that accounts for uncertain marine-animal presence, channel variability, and Doppler effects.
Formulated a two-stage scenario-based stochastic programming model incorporating a hybrid risk approach to balance network performance and marine impact.
Assigned channel selection in the first stage and implemented adaptive power allocation in the second stage after environmental uncertainties manifest.
Evaluated performance against deterministic expected-value benchmarks across identical simulated mobility and marine presence scenarios.
Improved the optimization objective value by 6% to 19% relative to the deterministic expected-value formulation under identical scenarios.
Raised mean network capacity by an indicative 14% over a benchmark deterministic study under average marine-animal presence conditions.
Enhanced communication robustness across worst-case and mixed-application scenarios at the cost of a modest increase in transmit power.