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 scintillation-related 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.
Original language | English (US) |
---|---|
Pages (from-to) | 5083-5090 |
Number of pages | 8 |
Journal | Journal of Lightwave Technology |
Volume | 37 |
Issue number | 19 |
DOIs | |
State | Published - 2019 |
Bibliographical note
KAUST Repository Item: Exported on 2020-10-01Acknowledged KAUST grant number(s): BAS/1/1614-01-01, KCR/1/2081-01-01, GEN/1/6607-01-01, REP/1/2878-01-01
Acknowledgements: This work was supported by the King Abdullah University of Science and Technology (KAUST) baseline funding, BAS/1/1614-01-01; KAUST equipment funding, KCR/1/2081-01-01; GEN/1/6607-01-01; KAUST-KFUPM Special Initiative (KKI) Program, REP/1/2878-01-01.