Reconfigurable Intelligent Surfaces in UOW-UAC Integrated Network: A Performance Analysis for the Internet of Underwater Things

Reconfigurable intelligent surfaces (RISs) have the potential to revolutionize underwater communications and contribute to the field of Internet of Underwater Things (IoUT) by dynamically controlling wireless channels to meet the advanced specifications of 6G networks. In this context, this paper proposes a practical model for mixed RIS-assisted underwater optical wireless (UOW) - underwater acoustic communication (UAC) network. The UOW link is modeled using the mixture Exponential Generalized Gamma distribution, while the UAC channel is characterized by a K- distribution model. Closed-form analytical expressions for outage probability (OP), average bit error rate (ABER), and average channel capacity (ACC) are derived. Numerical results show that incorporating RIS into the UOW link significantly mitigates the impact of fading on the UAC link, improving the signal strength. Furthermore, it is demonstrated that the implementation of the heterodyne detection technique reduces the effect of pointing error at the UOW receiver. Finally, Monte Carlo simulations are conducted to validate the accuracy of the analytical findings. Simulation results show an 88.36% improvement in OP at 42 dB, a 71.47% reduction in ABER at 45 dB, and a 69.03% enhancement in communication performance in freshwater conditions.