Optical Wireless Communication System

instance, two tall buildings using OWC system on top of their buildings to

establish connections. Sometimes, these buildings are bound by dynamic wind

causes to sway along it during the day or even the slight thermal expansion or

shrinking of building’s frame might cause small misalignment for the transmitter

and receiver. Every misalignment of the devices poses a threat to OWC’s QoS

[12]. As this phenomenon occurs randomly, the performance of the system will be

Journal of Engineering Science and Technology Special Issue 2/2016

100 J. L. Y. Chieng and I. Hassan

affected at uncertain time. Because OWC employs “point and shoot” approach,

and errors of alignment will introduce signal fading. One possible solution is to

develop a pointing error mechanism that able to feedback the alignment error and

readjust its transmission and receiving behaviour with intelligent protocols, more

research has to be done on this area [12].

Besides that, Ahmed Nabih [13] mentioned that weather conditions like rain,

snow, fog or even clouds may absorb the light wave propagation and small

water particles from the rain can also cause particles scattering. This will cause

the OWC system performance to be affected like particle scattering will result

in signal attenuation and distortions. Therefore, it is important to maintain a

clear line of sight between the transmitter and receiver, especially when LOS

link type is used. Sometimes, the LOS can also be interfered by foreign objects

such as birds or airplanes, making it a possible threat for temporary do wntime

of transmission.

Ambient light and artificial light can result in background noise which can

degrade receiver’s performance. Moreira et al. [14] performed testing on

various ambient light sources and developed a model to describe background

noises. One of the largest noise sources is the sun itself. Sunlight is

unmodulated and has wide spectral width. It is the major noise source in any

photo detection devices. However, artificial light source noise does not produce

background current (micro-amperes) as high as the sun (mili-amperes) but it

still does contribute to noise background [14]. Bocouvalas [15] and other

researchers have done significant amount of work on experimenting optical

source noises and proposed advanced signal processing filters to remove many

types of such noises and improve overall performance.

The research question for this project: What is the impact of Optical Wireless

Communication System to the quality of service (QoS) such as bit error rate, signal-

to-noise ratio, Q-factor, receiver’s voltage output; identify challenges and

suggestions for improvement?

2. Method

The hardware’s results will be obtained by collecting the receiver’s output and

feed it to the multimeters and digital oscilloscopes. By manipulating the

propagation distance between the transmitter and receiver, the receiver’s outp ut

voltage, current and signal waveforms will be collected. Due to the limited

equipment in the engineering lab, Optiwave OptiSystem software will be used

to produce a simulated circuit and calculate the model’s BER. As for SNR,

MATLAB software will be used to calculate it. The following subchapters will

discuss more details.

2.1. System model

The transmitter circuit (Fig. 1) is intended to be designed such a way that it can

transmit wirelessly to the receiver. The input signal is an audio signal that will fed

by the audio generator. The laser is responsible to transmit the light at a distance.

The photo transistor at the receiver’s end supposed to be directed Line of Sight

(LOS) link to the transmitter’s laser beam.

Journal of Engineering Science and Technology Special Issue 2/2016

Optical Wireless Communication System 101

The receiver circuit (Fig. 2) is proposed to use phototransistor to receive laser

signals from the transmitter. As the received signals produce voltages, it is further

amplified with the signal amplifiers. Then it will be converted back to audio signals

and to be heard by the speaker. The speaker has an in built gain or volume dial to

further boost the signal amplification.

DC Supply

Audio

Generator

Transistor

Driver Stage

Laser

Diode

Fig. 1. The audio is transmitted by a laser diode.

Phototransistor

Gain Control

Audio

Demodulator

Signal

Amplifier

Speaker

Fig. 2. The audio is being received by the photo transistor.

Table 1 shows the fixed parameters for both the experimental and software

OWC model to reduce fluctuations of the results.

After identifying the project hardware specifications Fig. 3 introduces the

experimental model of the OWC system and Fig. 4 introduces the simulation model

of the OWC system using OptiSystem software.

Table 1. OWC system parameters for this project.

Transmitter Front End (Laser +

Modulator)

Operating

Wavelength

Class

Average Optical

Output Power

650 nm

Class 3A

5 mW

Bit Rate

320 kbps

Receiver Front End (Photodetector +

Amplifiers)

Type of

Photodetector

(PD)

PD Responsivity

PIN Photodetector

(Solar Cell)

0.233A/W

0.5 cm2

PD active area

Amplifier

Frequency

Response

100 Hz - 10 khz

Input Signal

Transmitter

Aperture

Diameter

Audio Song

(Pseudo-

Random NRZ

bits)

0.2 cm

Amplifier Power

Output

200 mW

Receiver Aperture

Diameter

0.8 cm

Journal of Engineering Science and Technology Special Issue 2/2016

102 J. L. Y. Chieng and I. Hassan

Receiver

Transmitter

Fig. 3. Experimental model of OWC system.

Journal of Engineering Science and Technology Special Issue 2/2016

Optical Wireless Communication System 103

Fig. 4. OWC system in OptiSystem.

2.2. System efficiency between simulated and experimental model

Comparison will be made between the simulated data by using OptiSystem and

experiment data. The manipulated variable will be the propagation link distance

given a 320 kbps audio signal. The responding variable will be the output power

produced at the PIN photodetector. Once the comparison is made, the efficiency of

both the transmitter and receiver circuit can be calculated in terms of output, refer to

Eq. (1). Repeat the whole process again by manipulating the propagation distance

between the transmitter and receiver from 0.5 meter to 15 meters.

(1)

2.3. Signal-to-noise ratio (SNR)

Signal-to-noise ratio is a measure of how a certain signal is being corrupted by

noise. Defined as the ratio of signal power to the noise power along the signal, a

ratio of more than 1 indicates more signal than noise. In communication system,

higher SNR is favourable. Eq. 2 shows that the SNR in decibels (dB) [16]. For this

project, SNR will be calculated with MATLAB by using Eq. 2 [16] because there is

a limitation of tools to measure background noise power.

(2)

2.4. Quality factor (Q-Factor)

In optical communication, the common existence of signals are power and noise.

That is why SNR is an important parameter for any communication systems. Q-

factor is a dimensionless measurement where it simply indicates quality factor of

the system whether it is underdamped or overdamped [17]. Given SNR, Q-factor is

able to be calculated as shown in Eq. 3 [18]. T is the bit period and Bopt is the

bandwidth of the optical filter used. In Optisystem, the Q-factor are calculated based

on this equation.

(3)

2.5 Bit error rate (BER)

Bit error rate is usually a standard data given by any transmission devices. BER is

the number of bit errors received by the total bits of the transmission media. These

bit errors are usually due to noises or other interferences. The BER formula for this

OWC system is shown in Eq. 4 [18]. This project will be built and simulate in

OptiSystem software in order to get the BER and the Q-Factor using the BER

analyser tool as shown in Figs. 5 and 6.

Journal of Engineering Science and Technology Special Issue 2/2016

%100,efficiency systemsimulatedalexperimentooPPnoisesignaldBPPSNR10log10SNRTBSNRQopt2112

104 J. L. Y. Chieng and I. Hassan

(4)

Fig. 5. BER analyser tool is connected to the simulation model output.

Journal of Engineering Science and Technology Special Issue 2/2016

2/2/QerfcBER

Optical Wireless Communication System 105

Fig. 6. BER graph in the analyser tool.

3. Results and Discussion

The project prototype has successfully built and various experiments have been

done to obtain the data for analysing. After performing experiments with the project

prototype, the model is being built and simulated in OptiSystem software to further

validate, verify and compare the actual experimental results. More details will be

discussed in the subchapters.

3.1. Receiver’s power output vs. link distance

An audio signal that has a bit rate of 320 kbps was made as input of the transmitter.

The laser then transmit light to the receiver at a distance ranging from 0.2 m to 15

m. A multimeter was tapped onto the output of the receiver’s circuit for data

collection. Once the experiment is done, a simulated model was performed using

OptiSystem 12. The power output of the simulated design is also being recorded.

From Fig. 7, results have shown that the receiver’s power output is experiencing

a decrease as the propagation link distance increase; just as expected in the initial

proposal. At 0.2 m, the experimental receiver managed to give an output of 3.35

mW, the highest recorded; while the simulation model gives 4.91 mW. Bear in

mind that the transmitter is sending a signal power 5 mW. At close proximity, the

sound amplifier gives a very clear and loud audio sound. This is a classic trend in

any audio wireless signal system where it shows that power signals become weak as

propagation distance increases. At 9 m and beyond, the power loss became very

obvious when the sound amplifier produced a very faint and soft audio sound.

Unless the transmitter source increases its signal power, the receiver will suffer

from poor signal power reception. In the case of laser, it is challenging to increase

transmitting power because of the eye safety regulations that are in place. A higher

power laser may cause harm and damage to human eyes.

Journal of Engineering Science and Technology Special Issue 2/2016

106 J. L. Y. Chieng and I. Hassan

By comparing the simulated and experimental output, the overall system

efficiency is at 66.3%. Generally, hardware components are bound by power losses

such as heat dissipation, power supply fluctuations, minor current and voltage

leakage, conversion rate of input signal to output signal. However, the major factor

of such drop in efficiency is the atmospheric effect. Dust particles found in

atmosphere can cause particle absorption and scattering. Thus, the drop in receiver’s

ability to achieve maximum 5 mW power given by the transmitter.

Fig. 7. Receiver’s output power vs. link distance.

3.2. SNR vs. Link distance

To aide calculations, MATLAB algorithms has been used to find out the SNR at

link distance of 0.2 m to 15 m. Figure 8 shows the results of SNR vs. link

distance curve.

The SNR results demonstrated in Fig. 8 that SNR decreases as the link

distance increases. As explained in the research methodology, it is known that

SNR is the ratio of signal power over noise power. Logically as the link distance

increases, the receiver’s output power would decrease too. As a result, the signal

power diminish quickly and the noise power steadily increases. Hence, the SNR

has decreased in respect of link distance just as expected. Poor SNR is a major

concern in communication systems; therefore it is a priority to find ways

improving the performance. Other than keeping the transmitter and receiver

distance at closer range, the introduction of signal processing filters at both ends

are good methods to curb noise signals.

3.3. Q-Factor vs. Link distance

Quality Factor (Q-factor) is a very useful parameter to indicate the performance

of any communication systems. As mentioned in the research methodology, Q-

factor at different link distance is being recorded by using the OptiSystem model.

The BER Analyser tool measured both BER and Q-Factor. Figure 9 shows the

results of this OWC system Q-factor at distance of 0.2 m to 15 m.

Journal of Engineering Science and Technology Special Issue 2/2016

Optical Wireless Communication System 107

Fig. 8. SNR vs. Link Distance.

Fig. 9. Q-Factor vs. Link Distance.

The Q-Factor of this OWC system reflects the same trend as the BER and SNR.

As explained in the previous chapter, Q-factor is a way of measure the quality

performance of any communication system. Just as expected in the initial proposal,

the Q-factor decreases as link distance. However at 0.2 m to 15 m, the Q-factor

decreases at a very small rate. Just like the BER results (refer 3.4); the laser optical

properties do not have immediate impact towards the system performance at such

ranges of link distance. According to the simulated model, the system’s non-

functional point is at 600 meters. That is when the Q-Factor approaches 0.

3.4. BER vs. Link distance

With the implementation of this OWC system in OptiSystem, the BER of this

OWC system is able to be collected. Simply by connecting a BER Analyser

Tool to the model’s output, readings such as the eye diagram, BER and Q-

Factor are able to be displayed.

From Fig. 10, higher BER indicates that the data signal has higher probability of

error in its propagation. This is not favourable in all communication systems.

However in this project, the BER is still within the range of 10-5 at 0.2 m to 15

meters. It was initially expected to increase exponentially but it shows that it

increased steadily instead. This is due to the property of laser diode at a narrow 1

nm optical bandwidth, which is less prone to particle scattering and fading signals

Journal of Engineering Science and Technology Special Issue 2/2016

108 J. L. Y. Chieng and I. Hassan

compared to IR LEDs. Figure 10 illustrates the trend of the BER vs. Link Distance

from 0.2 m to 15 m. It shows a linear increase in the BER as link distance increases.

Since the range of 0.2 m to 15 m did not display a significant decrease in

performance, a larger link distance range (250 m - 600 m) has been investigated.

In order to investigate the maximum distance when the BER is 1 for this system,

the simulated model in OptiSystem was used. When BER is 1, it signifies that

the probability of error in this system is unavoidable. According to Fig. 11

output results, it is found that the maximum distance for this system to achieve

BER=1 is 600 meters. From the results, it is inevitable that BER increases as

link distance increases.

)

5

-

0

1

x

(

R

E

B

5.0

4.0

3.0

2.0

1.0

0.0

1.0E-01

8.0E-02

6.0E-02

4.0E-02

R

E

B

2.0E-02

0.0E+00

-2.0E-02

-4.0E-02

Bit Error Rate

Linear (Bit Error Rate)

0

3

6

9

12

15

Link Distance (m)

Fig. 10. BER vs. Link Distance (0.2 m-15 m).

Bit Error Rate

Linear (Bit Error…

250

300

350

400

450

500

550

600

Link Distance (m)

Fig. 11. BER vs. Link Distance (250 m-600 m).

3.5. Beam divergence, misalignment and particle absorption

In LEDs and lasers, the optical source is subjected to beam divergence due to

its optics property. Likewise, this experimental model has faced the same

Journal of Engineering Science and Technology Special Issue 2/2016

Optical Wireless Communication System 109

issue but with minimal impact to its output results due to the low laser power

output at 5 mW. Figure 12 shows the beam divergence at 0.2 m and 15 meters.

It can be seen that the laser beam aperture diameter has increased from 1

centimetre to 2.5 centimetres as link distance increases at 0.5 meter to 15

meters. One of the method to overcome this challenge is to increase the

larger aperture lasers.

receiver’s photodetector active area to receive

Throughout the experiment, there were difficulties to align the laser

propagation especially when the link distance increases. No signal or weak

signal is received whenever misalignment of laser occurs.

At 0.2 m

At 15 m

Fig. 12. Laser beam divergence occur at 0.2 m and 15 m at the receiver.

For experimental and investigation purposes, water spray has been

introduced during the propagation of signal between the transmitter and

receiver. As the water is being sprayed perpendicularly to the propagated laser

path, the receiver’s sound amplifier produced distorted signals and fading

signals such as hissing and thunder sounds. Such distortion is caused by

particle absorption. Where photons’ energy did not successfully channel to

the receiver but absorbed by the particles in the atmosphere such as dust and

water droplets. Figure 13 shows the water spray is being introduced to the

system for experimentation.

Journal of Engineering Science and Technology Special Issue 2/2016

110 J. L. Y. Chieng and I. Hassan

Fig. 13. Water is being sprayed at the laser beam propagation path.

4. Conclusion

This OWC system has clearly demonstrated the expected outcome that

was initially raised in the project proposal. From the results collected, it can

be seen that the efficiency of experimental vs. simulation model is at 66.3%.

As the link distance increases, the BER increased, SNR and Q-Factor

decreased. These outcomes are in line with hypothesis. According to the

OptiSystem simulated model, this OWC system has a break down limit at

600 meters; where the BER is at 1 and Q-Factor at 0. There are also some

challenges faced during the experiment. Laser beam divergence is a common

issue and usually a larger receiver active area is one of the immediate ways

to overcome it. Particle absorption phenomena has also been demonstrated

in this experiment, as well as noise signals from the ambience light can

be heard as link distance increases. It is proposed that the implementation

of signal processing noise filters can help to improve signal quality. In

order to overcome random errors throughout the experiment, a few attempts

of data recording has also been done. The average mean of the results are used

in this report. Table 2 shows a summary table of all the results collected in

this project.

Table 2. Summary of OWC results.

Link

Distance

(m)

0.2

1.0

3.0

Output

Power from

Experiment

(mW)

3.35

Output

Power from

Simulation

(mW)

4.91

2.63

2.17

4.18

3.20

Bit

Error

Rate

(x 10-5)

2.13

2.23

2.53

SNR

(dB)

Q-

Factor

291.2

260.9

227.9

4.09

3.97

3.95

Journal of Engineering Science and Technology Special Issue 2/2016

Optical Wireless Communication System 111

5.0

7.0

9.0

11.0

13.0

15.0

1.88

1.49

1.30

0.98

0.63

0.39

2.78

2.22

2.03

1.50

0.94

0.60

2.65

2.75

2.75

3.36

4.47

4.59

208.8

195.6

188.6

180.7

174.3

168.16

3.96

3.97

3.95

3.91

3.92

3.91

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