Experimental Evaluation of Performance of Underwater Free Space Optical Link in the Presence of Air Bubbles

Singh, Mandeep; Gill, Harpuneet Singh

doi:10.1109/wecon.2018.8782080

Cited by 4 publications

(5 citation statements)

References 17 publications

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“…Using ( 4) and ( 21) in (22) and applying the definition of Fox H-function, we get Finally, we use the transformation of random variable γ = γ 0 h 2 to get the PDF SNR in (6). To find the CDF of SNR under the combined channel, we use (6) to get the CDF of the SNR in (7), which concludes the proof of Theorem 1.…”

Section: Appendix Amentioning

confidence: 72%

“…where the set {M, δ, φ, q n } can specify a variety of modulation schemes. Using (7) and substituting exp(−q n γ) = (11) and representing the Meijer G-function into Fox-H function, we express (11) as…”

Section: Average Bermentioning

confidence: 99%

“…An analytic expression for the channel capacity of an orbital angular momentum (OAM) based free-space optical (FSO) communication in weak oceanic turbulence was developed in [6]. The effect of air bubbles on the UWOC was experimentally evaluated in [7]. The authors in [8], [11] analyzed the performance of multi-input and multi-output (MIMO) UWOC systems over log-normal turbulent channels.…”

Section: Introductionmentioning

confidence: 99%

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Optical Wireless Transmissions over Multi-layer Underwater Channels with Generalized Gamma Fading

Das¹,

Rahman²,

Zafaruddin³

2022

Preprint

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Underwater optical communication (UWOC) is a potential solution for broadband connectivity in oceans and seas for underwater applications providing high data rate transmission with low latency and high reliability. Recent measurement campaigns suggest generalized Gamma distribution as a viable model for oceanic turbulence. In this paper, we analyze the performance of a UWOC system by modeling the vertical underwater link as a multi-layer cascaded channel, each distributed according to independent but not identically distributed (i.ni.d.) generalized Gamma random variables and considering the zero bore-sight model for pointing errors. We derive analytical expressions for probability density function (PDF) and cumulative distribution function (CDF) for the signal-to-noise ratios (SNR) of the combined channel and develop performance metrics of the considered UWOC system using outage probability, average bit error rate (BER), and ergodic capacity. We also derive the asymptotic expressions for outage probability and average BER to determine the diversity order of the proposed system for a better insight into the system performance. We use Monte-Carlo simulation results to validate our exact and asymptotic expressions and demonstrate the performance of the considered underwater UWOC system using measurement-based parametric data available for turbulent oceanic channels.

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Section: Appendix Amentioning

confidence: 72%

Section: Average Bermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Optical Wireless Transmissions over Multi-layer Underwater Channels with Generalized Gamma Fading

Das¹,

Rahman²,

Zafaruddin³

2022

Preprint

View full text Add to dashboard Cite

show abstract

“…33 Moreover, in the real underwater environment, the turbulence-induced due to temperature and salinity variations not only affects the system performance, but air bubbles also affect the link performance more adversely at a larger scale. 34,35 They distort the amplitude and phase of the transmitted beam and induce intensity fluctuations in the received signal that deteriorate the underwater link performance. The discharge of different gases from the seabed, breaking surface waves, the wake of ship propellers, and other factors all contribute to the formation of air bubbles in the ocean.…”

Section: Introductionmentioning

confidence: 99%

“…41 Moreover, the bubble cross-sectional area along with the number of interacting bubbles to the transmitted beam is evaluated experimentally, and the PDFs of the intensity fluctuations are characterized using the Gaussian mixture model (GMM) while considering a link span of 1.56 and 7.8 m. 42 The numerous experimental studies focus on modeling the irradiance fluctuations produced due to air bubbles only without considering temperature and salinity variations. 34,[43][44][45] In addition, the effect of air bubbles in the temperature gradient channel is experimentally evaluated, and the PDF is characterized using exponential-generalized gamma (EGG) distribution. 46 To quantify the effect of turbulence in the UWOC system, some researchers have employed the Free Space Optics (FSO) channel model, that is, lognormal distribution.…”

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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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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Comprehensive experimental and statistical analysis of the effects of salinity gradient, temperature gradient, air bubbles on the performance of underwater wireless optical communication link

Singh

et al. 2022

Journal of Modern Optics

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Experimental Evaluation of Performance of Underwater Free Space Optical Link in the Presence of Air Bubbles

Cited by 4 publications

References 17 publications

Optical Wireless Transmissions over Multi-layer Underwater Channels with Generalized Gamma Fading

Optical Wireless Transmissions over Multi-layer Underwater Channels with Generalized Gamma Fading

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

Comprehensive experimental and statistical analysis of the effects of salinity gradient, temperature gradient, air bubbles on the performance of underwater wireless optical communication link

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