Impact of Turbulent-Flow-Induced Scintillation on Deep-Ocean Wireless Optical Communication

Abstract

The use of autonomous underwater vehicles (AUVs) is highly desirable for collecting data from seafloor sensor platforms within a close range. With the recent innovations in underwater wireless optical communication (UWOC) for deep-sea exploration, UWOC could be used in conjunction with AUVs for high-speed data uploads near the surface. In addition to absorption and scattering effects, UWOC undergoes scintillation induced by temperature-and salinity-related turbulence. However, studies on scintillation have been limited to emulating channels with uniform temperature and salinity gradients, rather than incorporating the effects of turbulent motion. Such turbulent flow results in an ocean mixing process that degrades optical communication. This study presents a turbulent model for investigating the impact of vehicle-motion-induced turbulence via the turbulent kinetic energy dissipation rate. This scintillationrelated parameter offers a representation of the change in the refractive index (RI) due to the turbulent flow and ocean mixing. Monte Carlo simulations are carried out to validate the impact of turbulent flow on optical scintillation. In experimental measurements, the scintillation index (SI) and signal-to-noise ratio (SNR) are similar with (SI = 0.4824, SNR = 5.56) and without (SI = 0.4823, SNR = 5.87) water mixing under uniform temperature channels. By introducing a temperature gradient of 4 °C, SI (SNR) with and without turbulent flow changed to 0.5417 (5.06) and 0.8790 (3.40), respectively. The experimental results show a similar trend with the simulation results. Thus, turbulent flow was shown to significantly impact underwater optical communications.

Performance Evaluation of Underwater Wireless Optical Communication System by Varying the Environmental Parameters

“…In addition, the temperature distribution is nonuniform in the water tank and the optical propagation path. Prior work [18] demonstrated, lower scintillation index, higher signal-tonoise ratio, and lower BER at 25 • C water temperature. Simultaneously, the eye diagrams shown in Figure 6a,b indicates that the system has better performance at 25 • C water temperature compared to 50 • C, with larger eye-opening and less time jitter.…”

A Comprehensive Comparison and Analysis of Several Intensity Modulations Based on the Underwater Photon-Counting Communication System

“…where I 0 is the mean received light energy in the time interval [0, T s ]. For plane-wave, the scintillation index (S.I), σ, can be expressed as [34]: where σ 2 r is the Rytov variance; the classical Kolmogorov spectrum model can be given [35]:…”

Reinforcement Learning Based Underwater Wireless Optical Communication Alignment for Autonomous Underwater Vehicles

“…Unlike acoustic signals, the underwater optical beam has limited propagation distance and strong directivity. Generally, the effective range of the UWOC link is about 1 -100 meters, which is affected by various factors such as absorption, scattering, turbulence, light source, and hardware configuration [6] [25] [26]. The limitations in optical signal transmission require maintaining the LOS link for underwater communication.…”

“…The required duration will be increased by one timestep after every 2 × 10 6 sample data are learned. The coefficients of the reward function are given in Equation (25) and Equation (26). All the sample data are collected from the simulator defined in Section IV-B.…”