Rigorous Performance Characterization of AI-Enhanced 6G Underwater Optical Wireless Networks: Link Budget Correction and Empirical Gain Validation

The incorporation of sixth-generation (6G) technologies into underwater optical wireless communication (UWOC) holds the potential for Gbps-class maritime connectivity; however, the field is presently affected by significant overestimations in the systematic link budget found in existing literature. Frequent modeling errors—such as replacing absorption with total beam attenuation, assuming coherent detection, neglecting Hermitian symmetry constraints, and applying laboratory-measured AI gains without scrutiny—have resulted in overinflated range projections by as much as two to three times. This study introduces a revised intensity-modulated direct-detection (IM/DD) framework for DC-biased optical OFDM (DCO-OFDM) that corrects for each of these issues. The net throughput is rigorously calculated to be 776 Mbps for QPSK, explicitly considering the 511 usable subcarriers dictated by Hermitian symmetry in a 1024-point transform. Symbol-level Monte Carlo simulations across 40.9 million bits per distance point confirm the analytical BER predictions within 0.3 orders of magnitude at error rates relevant to operational use, while an experimental setup with a controlled MLP equalizer demonstrates that the +4–6 dB gains often attributed to deep learning equalizers completely disappear when the channel state is known—this insight reveals that channel uncertainty, rather than intersymbol interference (ISI) complexity, is the essential condition for AI-assisted equalization. The revised framework offers a self-validated range of 44.8 m (only with MRC diversity) and a projected range of 46 m (assuming literature-based CSI prediction) at BER < 10−9 in clear ocean conditions. System-level evaluations of proton-exchange membrane fuel cells indicate that AI-driven load smoothing yields minimal efficiency improvements (<0.2 %) at average AUV power levels, confirming that the 1.8× endurance benefit over lithium-ion batteries is solely due to energy density rather than intelligent power management. By providing fully disclosed parameters and empirical validation for every asserted advantage, this research establishes a scientifically credible benchmark for future calibration of 6G subsea architectures