Adaptive hybrid modulation-control framework for energy-efficient and reliable underwater IoT communication networks

Abstract Underwater IoT (UIoT) communication networks suffer from severe attenuation, multipath fading, limited bandwidth, and high energy consumption, which reduce communication reliability and network lifetime. To address these challenges, this paper proposes an Adaptive Hybrid Modulation-Control Framework (AHM-CF) for energy-efficient and reliable underwater communication. The proposed framework integrates channel-aware adaptive modulation, dynamic transmission power adjustment, reinforcement learning-based duty-cycle scheduling, and energy-aware routing. Simulation results demonstrate that the proposed framework reduces energy consumption by 52.4%, improves throughput by 45.1%, increases packet delivery ratio by 47.3%, and extends network lifetime by 58.6% compared with conventional underwater communication approaches. Furthermore, the proposed framework reduces end-to-end delay by 35.8% through intelligent routing and adaptive duty-cycle optimization.