Characterization of underwater optical data transmission parameters under varying conditions of turbidity and water movement

Mital, Matt Ervin; Michael, Cassia; Olarte, Vincent C.; Ong, Neil Brian S.; Ortega, Diane Clarisse F.; Uy, Mark Tristan R.; Rocamora, Josyl Mariela B.; Roxas, Edison A.; Cruz, Angelo R. dela; Vicerra, Ryan Rhay P.

doi:10.1109/icoict.2017.8074642

Cited by 5 publications

(3 citation statements)

References 8 publications

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“…The optimum link range of 35, 15, and 6 m, respectively, is realized 23 . The turbidity in the water is also varied, which leads to reduce the signal‐to‐noise ratio at the receiver and further worsens the system performance 24 . The characteristics of the turbulent UWOC channel under a wide range of temperature variations and flow rates are evaluated experimentally in a water pool.…”

Section: Introductionmentioning

confidence: 99%

“…23 The turbidity in the water is also varied, which leads to reduce the signal-to-noise ratio at the receiver and further worsens the system performance. 24 The characteristics of the turbulent UWOC channel under a wide range of temperature variations and flow rates are evaluated experimentally in a water pool. The probability density function (PDF) of the received power follows a Lognormal distribution over a link span of 12 m and a scintillation index up to 0.07.…”

Section: Introductionmentioning

confidence: 99%

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Statistical channel model to characterize turbulence‐induced fluctuations in the underwater wireless optical communication links

Singh

Kaur

et al. 2022

Int J Communication

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Summary Underwater wireless optical communication (UWOC) turns out to be a primary sought alternative to wireless technology, which can provide high data rate, enormous bandwidth, and low deployment cost and resolve the crowded radio frequency band issues. The performance of the UWOC link is significantly affected by the turbulent ocean environment. In this paper, the different turbulence scenarios such as salinity gradients, temperature gradients, and air bubbles are considered to model the turbulent nature of the ocean environment experimentally. These turbulent conditions induce severe intensity fluctuations in the received optical signal. These intensity fluctuations are modeled stochastically, and a novel turbulence channel model is proposed, which excellently fitted with the experimental data. The conformity of the proposed model is validated by performing a goodness of fit test in terms of R2 and root mean square error (RMSE) coefficients. The results show that for all the considered turbulent scenarios, the Gaussian mixture model better approximates the experimental observations than the Weibull distribution. As the strength of the turbulence increases, the chances of link outage and the probability of bit errors increase. At a flow rate of 4 L/min, the bit error rate (BER) of 10−20, 10−14, and 10−10 is recorded under clear water, salinity, and temperature gradient channel conditions, respectively. It is observed that the air bubbles have a significant impact on the propagating optical beam in comparison to temperature and salinity‐induced turbulence. Moreover, a close agreement between the proposed model and the experimental data is also observed, which makes the proposed model more appropriate to describe the turbulent ocean environment.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Statistical channel model to characterize turbulence‐induced fluctuations in the underwater wireless optical communication links

Singh

Kaur

et al. 2022

Int J Communication

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“…Optical communication relative to acoustic communication and RF waves has a higher bandwidth, better security and lower response time, so optical communication has been used photography and video transmission in real-time [9]. However, despite absorption, dispersion and disturbance, optical communications remain suitable for short-range communications of less than 100 meters [10][11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Experimental Study of Underwater Wireless Optical Communication from Clean Water to Turbid Harbor under Various Conditions

Adnan¹,

Hassan²,

Alchalaby³

et al. 2021

IJDNE

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In this paper, texts were experimentally transmitted by pulse width modulation (PWM) using an underwater wireless optical communication system (UWOC) in a channel containing water of varying salinity as a result of changes in the concentration of sodium chloride (NaCl). Mathematical equations are used using a MATLAB program to compare theoretical and practical results at different slop angle (θ0). (NaCl) concentration was changed from (0% w/v) to (90% w/v) to achieve different salinity of water (i.e., from clear water to turbid water). A diode laser with a power of 30 mW and a wavelength of 532 nm has been employed in the transmitter. The experimental results show that the extinction coefﬁcient or the overall attenuation C(λ) is equal to (0.083/m) in the water containing a low concentration of (NaCl) which is consistent with pure seawater. Additionally, the obtained optical power (PR) and the signal to noise ratio (S/N) decreases to (27.6) mW and (23.99) dB, respectively. Furthermore, it was found that the water had a maximum total attenuation C(λ) equal to (2.565/m) in the water containing a high concentration of (NaCl) which was compatible with turbid harbour water, as well as the received power and (S/N) decreases to (2.306) mW and (13.2) dB, respectively. The theoretical results were similar to the practical results when the slope angle of the target or detector relative to the optical transmitter was (zero).

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Neural Network Implementation of Divers Sign Language Recognition based on Eight Hu-Moment Parameters

Mital

Villaruel

Dadios

2018

2018 2nd International Conference on Informatics and Computational Sciences (ICICoS)

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Characterization of underwater optical data transmission parameters under varying conditions of turbidity and water movement

Cited by 5 publications

References 8 publications

Statistical channel model to characterize turbulence‐induced fluctuations in the underwater wireless optical communication links

Statistical channel model to characterize turbulence‐induced fluctuations in the underwater wireless optical communication links

Experimental Study of Underwater Wireless Optical Communication from Clean Water to Turbid Harbor under Various Conditions

Neural Network Implementation of Divers Sign Language Recognition based on Eight Hu-Moment Parameters

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