Characteristics of Optical Channel for an Underwater Optical Wireless ...

Australian Journal of Basic and Applied Sciences, 9(23) July 2015, Pages: 437-445 ISSN:1991-8178

Australian Journal of Basic and Applied Sciences

Journal home page: www.ajbasweb.com

Characteristics of Optical Channel Communications Based on Visible Light

for

an

Underwater

Optical

Wireless

Mazin Ali A. Ali AL-Mustansiriyah Univ. / College of Science / Physics Department, Iraq. ARTICLE INFO Article history: Received 12 March 2015 Accepted 28 June 2015 Available online 22 July 2015 Keywords: Underwater communications, optical wireless communications, bit error rate performance, optical channel, line–of–sight.

ABSTRACT In this paper, we investigate the effect of water attenuation on an underwater optical wireless communication based on LOS model. We take into account some parameters including the chlorophyll concentration, receiver aperture area and also discuss the choice of suitable wavelength for underwater optical wireless communication. Using analytical expressions and calculating the Jerlov water type attenuation, the received signal power, and signal to noise ratio are studied. The characteristics of bit error rate for four kinds of optical modulation techniques (OOK, 2FSK, 2DPSK, and L-PPM) are analyzed. The results show that the performance of OOK and 2DPSK is more suitable for the underwater optical wireless communication. On the other hand, the wavelength 450nm is the better compared with the wavelength 600nm.

© 2015 AENSI Publisher All rights reserved. To Cite This Article: Mazin Ali A. Ali., Characteristics of Optical Channel for an Underwater Optical Wireless Communications Based on Visible Light. Aust. J. Basic & Appl. Sci., 9(23): 437-445, 2015

INTRODUCTION The performance of an optical wireless communication system is highly dependent on the channel through which it propagates. In the underwater domain, current studies have shown how slight variations in the composition of seawater lead to local changes in attenuation and recently these ideas have been used to determine the attenuation as a function of depth (Johnson, L.J., 2014). Optical communication is a viable method for short range underwater communication (Cox, W.C., 2007; Hanson, F., S. Radic, 2008) when the application requires high data rates, low latency or quiet operation. While such systems will always be limited by scattering and absorption in the underwater environment, for clear water 100-200 meter operations appears feasible (Pontbriand, C., 2008). Recently, underwater optical communication has witnessed a surge in interest from developments in blue-green sources and detectors. The advantage of the “blue-green optical window” of relatively low attenuation of blue-green wavelengths of the electromagnetic spectrum underwater is shown in fig. (1) (Pontbriand, C., 2008; Dunley, S.O., 1963). Underwater optical wireless communication a suitable candidate which satisfies the demand for increased broadband wireless data transmission (Kumar, N., N. Rafael, 2010). The challenges of underwater optical wireless communications

originate from light propagation in water, two mechanism ways that attenuate water are absorption and scattering. Absorption is a process when the photon energy is lost due to transfer of energy during the interaction with water molecules and particles (Arnon, S., et al, 2012). Minimum absorption occurs at the wavelengths of blue-green light, i. e. 430570nm (Woodward, A., H. Sari, 2008). Scattering is a process where a photon's path is deflecting due to the interaction with a particular matter in water, but there is no change in energy (Mobley, C.D., 1994). Absorption coefficient  () and scattering coefficient  () in units of an inverse meter are used to determine the energy loss of non-scattered light caused by absorption and scattering, respectively. The attenuation coefficient indicates the total effects of absorption and scattering on energy loss are shown in fig. (2)( Gawdi, Y.J., 2006). The values of c ( ) depend on both the wavelength  as well as turbidity of water (Tang, S., 2013). II. Channel model: When a photon is transmitted through the water, there are two mechanisms that prevent it from reaching a receiver further along the channel. The first is absorption  () and the second is scattering  () . The overall attenuation loss coefficient c ( ) is given by (Jerlov, N.G., 1976):

Corresponding Author: Mazin Ali A. Ali, AL-Mustansiriyah Univ. / College of Science / Physics Department, Iraq. E-mail: [email protected]

438

Mazin Ali A. Ali, 2015 Australian Journal of Basic and Applied Sciences, 9(23) July 2015, Pages: 437-445

(1)

c ( )   ( )   ( )

The absorption coefficient can be expressed as (Haltrin, V.I., 1999; Vavoulas, A., 2013).

Fig. 1: Relative absorption spectrum for distilled water.

Fig. 2: Absorption and scattering coefficients of water with 1mg/m3 of chlorophyll concentration.  ( )  aw



C 0 ( )  ac ( ).  00 C  c

   

0.602 0

Where aw ( ) is the pure water absorption coefficient have values equal to 0.0145 m-1 and 0.244m-1 for 450nm and 600nm respectively (Haltrin, V.I., G.W. Kattawar, 1991; Smith, R.C., K.S.

Baker,

1981);

(2)

0

 af C f exp(  k f . )  ah C h exp(  k h . )

ac0 ( ) is the spectral

absorption coefficient of chlorophyll with values equal to 0.025m-1, 0,007m-1 for 450 nm and 600nm

chlorophyll concentration (Pontbriant, C., 2008): 

 C c    C 0   c     C c   C h  0.19334C c exp0.12343  C 0   c  

C f  1.74098C c exp0.12327

Cc

as

follows (3) (4)

Where the constants with a value equal 0

 35.959 m / mg and

to Cc = 1 mg/m3 and Cc is the total concentration

ah  18.828m / mg are the specific absorption coefficient of fulvic acid and humic acid,

of chlorophyll, which have different values depend on categories of jerlov water types are shown in table 1 on the other hand, scattering mechanism arises from pure water βw(λ) as well as from small 0 0 particle  s ( ) and large particle  l ( ) . Small particles have a refractive index equal to 1.15 while large particles have a refractive index of 1.03 (Arnon, S., D. Kedar, 2009). The scattering coefficient is expressed as (Haltrin, V.I., 1999).

0 af

respectively; 0

2

2

respectively; C f and C h are the concentration of the fulvic acid and humic acid, correspondingly; while k f and k h are constants with values are 0.0189nm-1, 0.01105nm-1 respectively. The concentration of C f and C h are expressed in the

Table 1: Chlorophyll concentration for different Jerlov water types (Mobley, C.D., et al, 2004). Jerlov Water Types Concentration of Chlorophyll mg/m3 I 0.03 IA 0.1 IB 0.4 II 1.25 III 3

439

Mazin Ali A. Ali, 2015 Australian Journal of Basic and Applied Sciences, 9(23) July 2015, Pages: 437-445 0

0

 ( )   w ( )   s ( ).C   l ( ). C s l

(5)

where Cs and Cl are the concentrations of small and 0 large particles, respectively, and βw(λ),  s ( ) and 0  l ( ) are the scattering coefficients by the pure water, small particles, and large particles, given by (Haltrin, V.I., 1999)  0.4     

4.322

 w ( )  0.005826

,m

1

1.7  0.4  0 2  s ( )  1.151302  , m /g

(6)

 0.4     

0

0.3

(8)

2 , m /g

Where Cs and Cl are the total concentration of small and large particles in g/m3, respectively given by (Pontbriant, C., 2008): 

 C c   , g / m3  C    l    C c   , g / m3  0.76284C c . exp 0.03092  C   l  

C s  0.01739C c . exp 0.11631

Cl

(9) (10)

III. Analysis of a Link Model: A. Link Budget: To estimate of the receiver optical power Pr under line of sight (LOS) conditions is determined through empirical path loss models. The optical signal reaching the receiver is obtained by multiplying the transmitter power, telescope gain, and losses and given by (Arnon, S., D. Kedar, 2009) as  A r cos( ) d  (11) P  P   exp c ( ) . r

T T R

 

SNR 

I p2 M 2

cos( )  2 d 2 1  cos(0 )

Where Pt is the transmitted optical power, T

R are the optical efficiency of the Tx and Rx respectively, c ( ) is the attenuation coefficient, d is and

the perpendicular distance between the T x plane and Rx plane, θ0 is the Tx beam divergence angle, θ is the angle between the perpendicular to the Rx plane and the Tx-Rx trajectory, and Ar is the receiver aperture area. B. Detection of optical radiation: When transmitted optical signals arrive at the receiver, they are converted into electronic signals by photodetectors. There are many types of photodetectors in existence, photodiodes are used almost exclusively in optical communication applications because of their small size, suitable material, high sensitivity, and fast response time 20. The types of photodiodes are the PIN photodiode and the avalanche photodiode (APD) because they have good quantum efficiency and are made of

(12)

2

2q (I p  I D )M F (M )Be  4k BTBe / R

I p is the average photocurrent

Where (7)

  

 l ( )  0.3411

semiconductors that are widely available commercially. For optimal design of the receiver system, it is important to understand the characteristics of these photodiodes and the noise associated with optical signal detection (Keiser, G., 2000). The signal to noise ratio which given by (Trisno, S., 2006)

generated by a steady photon stream of average optical power, and equal to I p  Pr , where the average optical power received to the photo detector is Pr and  is the responsivity for Si PIN

photodiode,  equal to 0.6 A/W. The gain is designated by M, and noise figure F(M) is equal to 1(Keiser, G., 2004; Ghassemlooy, Z., 2013). The dark current ID, bandwidth frequency Be, and the resistor R, are equal to 10nA, 0.7GHz, and 50k Ω, respectively. C. Optical modulation techniques: There are different types of modulation techniques which are suitable for optical communication systems such as On-Off key (OOK), pulse position modulation L-PPM, differential phase shift key (M-DPSK) and frequency shift key (NFSK). Since the average emitted optical power is always limited, the performance of modulation techniques is often compared in terms of the average received optical power required to achieve a desired BER at a given data rate. The formulas of BER can be expressed as a function of a signal to noise ratio SNR as follows (Sui, M., X. Yu, 2009). 1  SNR  (13) BER  erfc OOK

2

  2 2

 SNR  1 BER 2FSK  erfc   2 4  

BER 2DPSK  erfc BER L  PPM 

SNR 2

(14)

 1 SNR  1  erfc  2   2

1 1  1 k  erfc  L 2 2 2

(15)

 L 1  k  L .SNR   erfc  L .SNR   2  2 2 

(16) Where L is modulation levels of the PPM, and k is the threshold and taken as 0.5 (Ding, Y., 2013). IV. Numerical Results: In this section, based on previous equations we present a set of analytical results to study the characteristics of the underwater optical channel. The values of the simulation parameters are given in table 2.

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Table 2: Parameters Used in Numerical Calculation (Arnon, S., 2010; Vavoulas, A., 2014). Parameter Transmission Wavelength λ (nm) Transmitter power PT(mw) Optical efficiency of transmitter T

Value 450,600 50 0.9

R

0.9

Laser beam divergence angle(θ0) Transmitter inclination angle (θ) Receiver aperture area A(m2)

600 5 0.01

Optical efficiency of receiver

A. Received optical power as a function of distance: Let us first see the effect of the attenuation coefficient c ( ) on the received optical power Pr employing line of sight model (LOS). We have shown in Fig. (3, 4) curves of Pr as a function of distance d for five Jerlov water types specified in Table 1 and two extreme cases of λ = 450 nm and 650 nm. Let us assume a tolerable loss of −200 dBm beyond which the signal is not detectable at the

receiver. We notice that, for λ =650 nm, the transmission range is limited to 8 and 30m for Jerlov type III, I waters, respectively, for instance. When the wavelength is decreasing λ = 450 nm increases dramatically these ranges, obviously, it allows range limits increases to 40m for Jerlov type IB and more than 100m for Jerlov type I, IA respectively. When working in Jerlov type II, III waters the high attenuation makes communication range limited to less than 18 m.

Fig. 3: Received signal power (dBm) as a function of distance for different water types, λ =650nm.

Fig. 4: Received signal power (dBm) as a function of distance for different water types λ =450nm. B. SNR for different water types: The SNR for different Jerlov water types is compared in Fig. (5, 6) for λ = 600 nm and λ = 450

nm. The SNR is decreasing with increasing distance link and decreasing wavelengths for different water types under study. It is achieved that I, IA water

441


types has presented the highest SNR compared with the other waters under the same operating conditions. On the other hand, it can be seen that the wavelength

λ = 450 nm is more suitable for underwater optical wireless communications than the others.

Fig. 5: SNR as a function of distance for different water types (λ =600 nm).

Fig. 6: SNR as a function of distance for different water types (λ =450 nm). Optical modulation characteristics for underwater optical communications We present here simulation results to compare the performances of the four optical modulation techniques. 1.

BER for different Jerlov water types: The BER for different Jerlov water types as a function of distance link are compared. Let us consider the modulation techniques are OOK, FSK,

DPSK and L-PPM employing to calculate the BER when a Si PIN PD is used. Fig. (7) Shows the curves of BER for the case of (OOK) modulation technique. If we consider a required BER 10 -8, the maximum distances for reliable data transmission about 16m and 13m for jerlov type I, IA and it decreases for chlorophyll concentration is increased as a jerlov water IB, II, III.

Fig. 7: BER as a function of distance for different water types under OOK modulation technique.

442


Now, consider the case where 2FSK is used as a modulation technique. Fig (8) shows the BER curves, for the target 10-8, the maximum distances for reliable data transmission are about the same values of the OOK technique in Jerlov water I, IA but differ

for type IB where it has value about 7.5m. Figure (9) shows the curves of BER when a 2DPSK is used as a modulation technique. In this case, the 2DPSK technique has similar behavior of the OOK technique for different Jerlov water types under study.

Fig. 8: BER as a function of distance for different water types under 2FSK modulation technique.

Fig. 9: BER as a function of distance for different water types under 2DPSK modulation technique. It is noticed that in fig. (10) a significant decrease in the link distance can be achieved by using the 2-PPM technique. If we required BER of 10-8, the maximum distance of reliable data transmission are about 11m and 9m for jerlov water

type I, IA respectively and 5.5m for IB water type. The sensitivity receiver of 2-PPM is lower than with the other modulation techniques, therefore the BER performance of 2-PPM is poor.

Fig. 10: BER as a function of distance for different water types under 2-PPM modulation technique.

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2. BER performance for different optical modulation techniques: To compare between OOK, 2FSK, DPSK and LPPM modulation techniques used an underwater optical communication system analytically. The BER for different modulation techniques when a Jerlov

water type I is used as a channel attenuation shows in fig. (11). It is clear that there is not a difference of BER curves for the optical modulation techniques under study when we used wavelength λ = 600 nm. In this case, for a target BER of 10 -8, the link distance is limited and reached to 5m.

Fig. 11: BER for water types I under different modulation techniques (λ = 600 nm). Another important simulation to evaluate the performance of BER for λ = 450 nm, fig. (12) shows the BER curves for Jerlov water type I. In this case, a significant improvement in the BER curves, therefore the modulation scheme is. The attainable link

distances are increased by about 10m in average. It should be noticed that the improvement in BER curves comes from the advantages of wavelength 450nm

Fig. 12: BER for water types I under different modulation techniques (λ = 450 nm). 3.

Effect of receiver aperture area: The effect of the receiver aperture area (A=0.1m2) on the BER is illustrated in fig. (13) for Jerlov water type I case and wavelength λ = 600 nm for different modulation techniques. Obviously, the use of larger receiver aperture area leads to the BER curves reached long distances. The BER curves have approximate values 7.5m average for different modulation techniques. On the other hand, when we used the wavelength λ = 450 nm are shown in fig.

(14) noticed that the BER curves have improved in distances about 10 m by increasing (A) from 0.01m2 to 0.1m2. From fig. (14) the BER of OOK is similar to 2DPSK, therefore the conclusion can be got that the OOK, 2DPSK has better BER performance that the other modulation techniques. The BER performance of L-PPM will significantly improve; for example, the BER performance of 8-PPM is better that 4-PPM and 2-PPM.

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Fig. 13: BER for water types I under different modulation techniques (A=0.1m2, λ = 600 nm).

Fig. 14: BER for water types I under different modulation techniques (A=0.1m2, λ = 450 nm). 4.

BER versus SNR: The BER versus SNR for different modulation techniques under the parameters A=0.01m2, λ = 450 nm is given in fig. (15). We notice a BER decreases with increasing signal to noise ratio SNR for

different optical modulation techniques under Jerlov water type I. Also observed that OOK and DPSK modulation techniques have presented the lowest BER in comparison with other modulation techniques.

Fig. 15: BER versus SNR for Jerlov water types I under different modulation techniques. V. Conclusion: We have investigated the BER of an underwater optical wireless communication (UOWC) link with precisely aligned LOS geometry model for Jerlov water types. The attenuation coefficient of a laser

beam through the water have a significant effect on the performance of underwater communication systems. Therefore, the investigation of water attenuation is very important. The effect of water attenuation is compared with different Jerlov water

445


types. Also, the effect of wavelengths and chlorophyll concentration are investigated. The wavelengths have a strong influence on received optical power and SNR, which leads to a short distance link for 600nm compared with 450nm which reached long haul link. When a chlorophyll concentration increase causes a decrease in the received optical power and signal to noise ratio. The BER characteristics of the OOK, 2FSK, 2DPSK, and L-PPM are analyzed. The results show that the OOK and 2DPSK has a greater advantages than the others of Jerlov water type I under the condition 450nm. A receiver aperture area is taking into account in the simulation; therefore, when we used a receiver aperture area as large as 0.1m2 we showed that the maximum distance of reliable data transmission is reached long distances. From the presented result we noticed that 450nm can also consider as a more suitable choice for underwater optical wireless communications. REFERENCES Arnon, S., 2010. "Underwater optical wireless communication network", optical engineering, 49(1). Arnon, S., D. Kedar, 2009. "Non-Line-of-sight underwater optical wireless communication network", J. opt.soc. Am. A, 28(3). Arnon, S., et al, 2012. "Advanced optical wireless communication systems", Cambridge university press. Cox, W.C., 2007. “A1 Mbps Underwater Communication System Using a 405 nm Laser Diode and Photomultiplier Tube,” M.S. thesis, North Carolina State University, Raleigh, NC. Ding, Y., Q. Ding, Q. Lui, 2013. "Performance analysis of optical modulation in slant transmission", international journal of innovative computing, information and control, 9(9) 3799-3805. Dunley, S.O., 1963. "light in the sea", journal of the optical society of America, 53(2): 214-233. Gawdi, Y.J., 2006. “Underwater Free Space Optics,” M.S. thesis, North Carolina State University, Raleigh, NC. Ghassemlooy, Z., W. Popoola, S. Rajbhandari, 2013. "Optical wireless communications system and channel modeling with matlab", CRC press, Taylor & Frances Group. Haltrin, V.I., 1999. "Chlorophyll-based model of sea water optical properties", Applied Optics", 38: 6826-6832. Haltrin, V.I., G.W. Kattawar, 1991. "Effect of Raman scattering and fluorescence apparent optical properties of sea water", Texas A&M University. Hanson, F., S. Radic, 2008. “High bandwidth underwater optical communication”, Appl. Opt., 47: 277-283. Jerlov, N.G., 1976. "Marine optics", Elsevier science, 13-63.

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