channel modeling of underwater wireless optical

CHANNEL MODELING OF UNDERWATER WIRELESS OPTICAL COMMUNICATION Zahra Vali Supervisors: Asghar Gholami, Masood Omoomi David G. Michelson, Zabih Ghassemlooy

2015

Content Introduction to Underwater Communications • Recent publications • Sound, RF & optical waves • Applications

Effective Phenomena in Channel Modeling • • • • •

Loss Spatial Dispersion Temporal Dispersion Turbulence Other

Model • Monte Carlo Simulation 2

• Introduction to Underwater Communication • Recent Publications

Approximate number of publications “Underwater optical wireless communication” 45 40 35 30 25 20 15 10 5 0 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 3

• Introduction to Underwater Communication • Comparison of different waves

Sound

RF

Optic

• Low absorption in low frequency • long range • Low speed, high delay • Low frequency, low bandwidth • Low data rate (Kbps) • Harmful for animals

• High speed in high frequency • Higher frequency, More bandwidth • High absorption in high frequency, short length (Conductivity of water)

• High speed • High data rate, High bandwidth in green wavelengths (Gpbs) : 1 Gbps in meters and 10 Mbps in hundreds of meters • Absorption: RF>optic>sound, Short length

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• Introduction to Underwater Communications • Applications

sampling data of oceans by Underwater sensor Networks, gathering information related to oceanography, marine archeology preserving oil equipment, searching oil fields, investigating mineral stores monitoring environments such as ports, pollution, oceanic flows, fish tracing

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• Introduction to Underwater Communications • Applications

 communication of submarine to lands, submarines to submarines, ships, divers, search & rescue processes  investigating water boundaries of countries for attacks  navigation: investigating rocks underwater, sunk objects

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•Effective Phenomena in Channel Modeling •Loss

• Absorption & scattering cause loss • Absorption: water, phytoplankton • Scattering: described as a process where a photon’s path is changed due to interaction with particulates or water (refractive index changes) • Wavelength dependent • Minimum loss in pure water : 400-500 nm • Minimum loss in ocean water: 450-550 nm

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• Effective Phenomena in Channel Modeling • Loss

How to model loss? • Beer Lambert Law

• 𝐼 𝜆, 𝑧 = 𝐼0 𝑒 −𝑐 𝜆 𝑧 𝑎 𝜆 +𝑏 𝜆 =𝑐 𝜆 • Beer’s Law only accounts for non-scattered photons • It does not hold for large attenuation lengths as scattered light is captured by the receiver and underestimating the system’s performance in harbor environments

• [Cochenour, 2008] • ƞ is the percentage of scattered light collected by the receiver relative to all of the light that has been scattered on its way to the receiver. For cz>30 it is compatible with monte carlo results. • 𝐼 𝜆, 𝑧 = 𝐼0 𝑒 −𝐾𝑧 𝑎 𝜆 + (1 − ƞ)𝑏 𝜆 = 𝐾 8

• Effective Phenomena in Channel Modeling • Spatial Dispersion

• • • •

What is spatial dispersion? Effect of spatial dispersion in turbid waters Effect of FOV & receiver's aperture [Cochenour, 2008] BSF method

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• Effective Phenomena in Channel Modeling • Spatial Dispersion

BSF method • The power distribution is known as beam-spread function (BSF). Although analytical computation of the BSF requires solving the complex radiative transport equation (RTE), several assumptions have been made so that the RTE can be solved analytically. • Small angle approximation (SAA): • Scattering events occur at small forward angles • The power distribution is symmetric about the beam axis.

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• Effective Phenomena in Channel Modeling • Spatial Dispersion

BSF method  E0 Hankel transform of a laser power distribution in free space  where p(v) is the Hankel transform of the scattering phase function

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• Effective Phenomena in Channel Modeling • Spatial Dispersion

Deficiency of BSF method • Formula accounts for all photons incident on the plane within the assumptions of the SAA • Not accounting a finite field of view, specific receiver angular orientation out of the plane • Not accounting temporal dispersion.

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•Effective Phenomena in Channel Modeling •Temporal Dispersion

• What is temporal dispersion? • When it is not negligible: long distance, high turbidity, high divergent beam • How to model it? Impulse response

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•Effective Phenomena in Channel Modeling •Temporal Dispersion

Impulse response Sermsak 2008 Gabriel 2013 Tang 2014

• Vector tadiative transfer (VRT) equation

• Monte carlo

• Monte carlo + double gamma function

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• Effective Phenomena in Channel Modeling • Temporal Dispersion

[ Tang 2014]

• The focus is on the impulse response modeling of coastal and harbor water • The double Gamma functions has been firstly adopted to model the impulse response in clouds where attenuation length is no less than 20.

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• Effective Phenomena in Channel Modeling • Temporal Dispersion

[ Tang 2014] • The closed-form expression of the double Gamma functions is:

• where C1 , C2 , C3 and C4 are the four parameters to be solved by nonlinear least square criterion . Δt = t − t0 and t0 = L/v is the direct propagation time.

• The results are matched well with monte carlo results.

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• Effective Phenomena in Channel Modeling • Turbulence

• What is Turbulence? Random fluctuation in refractive index due to the changes of temperature, salinity, pressure, oceanic flows, wavelength Ignored in most of previous works, however it can be impressive.

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• Effective Phenomena in Channel Modeling • Turbulence

Korotkova 2012

Liu 2015

• Calculation of scintillation index for clear water in the absence of scatterers, on the basis of temperature-salinity changes

• Clear water, absorption (MC) + turbulence • SIMO with LED

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•Effective Phenomena in Channel Modeling •Turbulence

[Korotkova, 2012] Power spectrum for computing scintillation index for homogeneous and isotropic oceanic water:

This new spectrum allows for more accurate predictions in the ocean than the Kolmogorov spectrum  XT is the rate of dissipation of mean-square temperature  w (unitless) is the relative strength of temperature and salinity fluctuations  Ɛ is the rate of dissipation of turbulent kinetic energy per unit mass of fluid

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•Effective Phenomena in Channel Modeling •Turbulence

[Korotkova, 2012] The scintillation index of a plane wave vs. propagation distance

Salinity, Temperature

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•Effective Phenomena in Channel Modeling •Turbulence

[Liu, 2015]

 Kolmogorov spectrum  Aperture averaging  log normal distribution

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•Effective Phenomena in Channel Modeling •Turbulence

[Liu, 2015]

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•Effective Phenomena in Channel Modeling •Other

 Random sea surface • •

wind multiple reflection

 Background noise • •

Sun, Bioluminescence, Fluorescence, Manmade machines Water as a filter → hard detection

 LOS or non-LOS link • •

Total internal reflection Extra reflection from surface

 Variable environmental composition • Chlorophyll distribution: 15 m in coastal region 200 m in open ocean

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• Model • Monte Carlo Simulation Numerical method vs. analytical methods  Approximations and analytical models of the underwater light-field do not consider all the parameters  Numerical method are accurate but computationally complex  Numerical method are compatible for different geometries  Numerical method should consider large number of photons to show reliable results

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• Model • Monte Carlo Simulation

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• Model • Monte Carlo Simulation Photon path length

Initial direction

Scattering angle

New position

Radial scattering angle

New direction

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• Model • Monte Carlo Simulation How to compute SPF?  The angular distribution of scattering power, called the volume scattering function, is defined as

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• Model • Monte Carlo Simulation How to compute SPF? • By integrating β over all angles, we arrive at an expression for b(λ) • If β is normalized by b, scattering phase function reaches which expresses the angular probability of scattering as a probability density function (PDF)

• Measured: low accuracy especially for high angles, difficult 28

• Model • Monte Carlo Simulation

Attenuation length

Received normalized power

1.00E+00 1.00E-01

5

10

1.00E-02 1.00E-03

1.00E-04 1.00E-05

15

1 2 4 8 16

45

1.00E-06

90

1.00E-07

180

1.00E-08

8mm Aperture, number of photon= 1E7, C=1.1

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• Model • Monte Carlo Simulation FOV (degree)

Received normalized power

1.00E+00 1.00E-01

aperture 0.008

1.00E-02

0.0254

0.0508 1.00E-03

0.0762 0.1016

1.00E-04 1.00E-05

number of photon= 1E7, C= 4.4, attenuation length= 10, L=2.3

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• Model • Monte Carlo Simulation

Received normalized power

Attenuation length=10, c=1.1, 4 inch receiver aperture

1.2

1

1

2

0.8

4

0.6

8

0.4

16 45

0.2

90

0

0

0.05

0.1

0.15

0.2

0.25

0.3

180

FOV

Receiver distance offset (m) 31

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• Reference • A. Laux, R. Billmers, L. Mullen, B. Concannon, J. Davis, J. Prentice, and V. Contarino, “The abc’s of oceanographic LIDAR predictions: A significant step toward closing the loop between theory and experiment,” J. Modern Opt., vol. 49, no. 3/4, pp. 439–451, 2002. • Gabriel, C., Khalighi, M.A., Bourennane, S., Leon, P., Rigaud, V., “Monte-carlo-based channel characterization for underwater optical communication systems”, J. Opt. Commun. Netw., Vol. 8, No. 1, pp. 1–12, 2013. • Tang, S., Dong, Y., Zhang, X., “Impulse response modeling for underwater wireless optical communication links”, IEEE Transactions on communications, Vol. 62, No. 1, pp.226-234,2014. • Hanson, F. , and Radic, S., “High bandwidth underwater optical communication”, Appl. Opt., Vol. 47, No. 2, pp. 277–283, 2008. • Korotkova, O., Farwell, N., and Shchepakina, E., “Light scintillation in oceanic turbulence”, Waves in Random and Complex Media, Vol.22, Iss.2, pp.260266, 2012. • Farwell, N., Korotkova, O., “Intensity and coherence properties of light in oceanic turbulence”, Optics Communications, Vol.285, Iss.6, pp.872–875, 2012.

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• Reference •

Liu, W., Xu, Z., and Yang, L., “simo detection schemes for underwater optical wireless communication under turbulence”, Photon. Res., Vol.3, No.3, 2015. • Cochenour, B. M., Mullen, L. J., and Laux, A. E., “Characterization of the beam-spread function for underwater optical communications links,” IEEE J. Ocean. Eng., Vol. 33, No. 4, pp. 513-521, 2008. • Wei, W., Xiao-hui, Z., Yue-yun, C., Xue-jun, Z., “An analytical model of the power spatial distribution for underwater optical wireless communication”, Optica Applicata, Vol.42, No.1, pp. 157-166, 2012. • Jaruwatanadilok, S., “Underwater wireless optical communication channel modeling and performance evaluation using vector radiative transfer theory,” IEEE Journal on Selected Areas in Communications, Vol. 26, No. 9, pp. 1620–1627, 2008.

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