Index Terms BER, modulation techniques, SNR, NRZ, [625618]

Index Terms —BER, modulation techniques, SNR, NRZ,
improvement.

I. INTRODUCTION
Optical fibers are widely used in fiber optic
communications which permits transmission over longer
distances and at higher bandwidths than other forms of
communication. Optical transmission networks based on
wavelength division multiplexing (WDM) architecture is
dominating the all-optical data transportation with bit rates
exceeding several terabit-per-second rates to serve the ever
increasing demand of Internet Protocol (IP) networks. Some
of the main TCP/IP networking functions such as routing,
add-drop multiplexing and demultiplexing and wavelength
conversion, need to be functional to encapsulate the IP packet
requirements into the Optical layer. The linear as well as the
nonlinear characteristics of the optical fiber at higher bit rates,
seriously limit the data transmission performance and it is
therefore becoming necessary to develop approaches to
improve regeneration of transmitted data. Experimental
investigations have shown a considerable progress in this
direction. These were based on compensation techniques,
filtering, developing optimized line coding, and further
dispensation of received signal. In a communication system,
the receiver side BER may be affected by transmission
channel noise, interference, distortion, bit synchronization
problem, attenuation, wireless multipath fading, etc.
The BER can be considered as an approximate estimate of the
bit error probability which is the expectation value of the
BER. The approximation is accurate for a long studied time
interval and a high number of bit errors [1].

II. BIT ERROR RATE AND SIGNAL -TO-NOISE RATIO
In telecommunication transmission, the bit error rate (BER)
is the percentage of bits that have errors relative to the total
number of bits received in a transmission. For example, a
transmission might have a BER of 10-6, meaning that, out of
1,000,000 bits transmitted, one bit was in error. The BER is
an indication of how often data has to be retransmitted
because of an error [1]. Too high a BER may indicate that a
slower data rate would actually improve overall transmission
time for a given amount of transmitted data since the BER
might be reduced, lowering the number of packets that had to
be present. The BER may be improved by choosing a strong
signal strength (unless this causes cross-talk and more bit
errors), by choosing a slow and robust modulation scheme or
line coding scheme, and by applying channel coding schemes
such as redundant forward error correction codes [2]. Th e
transmission BER is the number of detected bits that are
incorrect before error correction, divided by the total number
of transferred bits (including redundant error codes).
Normally the transmission BER is larger than the information
BER. The information BER is affected by the strength of the
forward error correction code. Sinusoidal driven resonators
having higher quality factors (Q) resonate with greater
amplitudes (at the resonant frequency) but have a smaller
range of frequencies around that frequency for which they
resonate; the range of frequencies for which the oscillator
resonates is called the bandwidth. Thus, a high Q tuned
circuit in a radio receiver would be more difficult to tune, but
would have more selectivity [3], [4]; it would do a better job
of filtering out signals from other stations that lie nearby on
the spectrum. High Q oscillators oscillate with a smaller
range of frequencies and are more stable. The quality factor
of oscillators varies substantially from system to system.
Tuning forks have quality factors around Q = 1000. The
quality factor of atomic clocks and some high- Q lasers can
reach as high as 1011 and higher [5].
Signal- to-noise ratio (often abbreviated SNR or S/N) is a
measure used in science and engineering to quantify how
much a signal has been corrupted by noise [5]. It is defined as
the ratio of signal power to the noise power corrupting the
signal. A ratio higher than 1:1 indicates more signal than
noise. While SNR is commonly quoted for electrical signals,
it can be applied to any form of signal (such as isotope levels
in an ice core or biochemical signaling between cells) [4]. In
less technical terms, signal- to-noise ratio compares the level
of a desired signal (such as music) to the level of background
noise. The higher the ratio, the less obtrusive the background
noise is. "Signal- to-noise ratio" is sometimes used informally
to refer to the ratio of useful information to false or irrelevant
data in a conversation or exchange. For example, in online Improvement of Bit Error Rate in Fiber Optic
Communications
Jahangir Alam S. M., M. Rabiul Alam , Hu Guoqing , and Md. Zakirul Mehrab
281International Journal of Future Computer and Communication, Vol. 3, No. 4, August 2014

Abstract—The bit error rate (BER) is the percentage of bits
that have errors relative to the total number of bits received in a
transmission. The different modulation techniques scheme is
suggested for improvement of BER in fiber optic
communications. The developed scheme has been tested on
optical fiber systems operating with a non -return -to-zero (NRZ)
format at transmission rates of up to 10Gbps. Numerical
simulations have shown a noticeable improvement of the system
BER after optimization of the suggested process ing operation
on the detected electrical signals at central wavelengths in the
region of 1310 nm.
Manuscript received February 17, 2014 ; revised March 27, 2014.
Jahangir Alam S. M. and Hu Guoqing are with the Department of
Mechanical and Electrical Engineering, Xiamen University, China (e -mail:
jahangir_uits@ yahoo.com , gqhu@xmu.edu.cn ).
M. Rabiul Alam is with the Department of Electrical & Electronic
Engineering, Hamdard University Bangladesh, Bangladesh (e -mail:
alam2007@ mail.ru).
Md. Zakirul Mehrab is with the Spark Bangladesh Ltd. , Dkaka,
Bangladesh (e -mail: jakirul2001@yahoo.com).
DOI: 10.7763/IJFCC.2014.V3.312

discussion forums and other online communities, off-topic
posts and spam are regarded as "noise" that interferes with
the "signal" of appropriate discussion. In a digitized
measurement, the number of bits used to represent the
measurement determines the maximum possible
signal- to-noise ratio. This is because the minimum possible
noise level is the error caused by the quantization of the
signal ( quantization noise ) [6]. This noise level is non-linear
and signal-dependent; different calculations exist for
different signal models. Quantization noise is modeled as an
analog error signal summed with the signal before
quantization ("additive noise") [7].
This theoretical maximum SNR assumes a perfect input
signal. If the input signal is noisy, the measurement noise
may be larger than the quantization noise. Real
analog- to-digital converters also have other sources of noise
that further decrease the SNR compared to the theoretical
maximum from the idealized quantization noise. Although
noise levels in a digital system can be expressed using SNR,
it is more common to use Eb/No the energy per bit per noise
power spectral density. The modulation error ratio (MER) is
a measure of the SNR in a digitally modulated signal.

III. NOISE SOURCES , MODULATION AND CODING
Noise is a significant issue in every communication system.
In the optical world (especially in WDM) there are many
sources of noise. The good news is that most of the noise
sources are so small that may be ignored. In other cases the
action can take to mitigate one form of noise also mitigates
many others. The dominant noise sources in WDM systems
are amplifier noise (ASE) and thermal noise in the receivers.
However, in the design of any system it is very important to
be aware of all the potential sources of noise so that they can
be avoided or mitigated [8] .
Modulation is the process of conveying a message signal,
for example, a digital bit stream or an analog audio signal,
inside another signal that can be physically transmitted.
Modulation of a sine waveform is used to transform a base
band message signal to a pass band signal, for example, a
radio-frequency signal (RF signal). In radio communications,
cable TV systems or the public switched telephone network
for instance, electrical signals can only be transferred over a
limited pass band frequency spectrum, with specific
(non-zero) lower and upper cutoff frequencies [9]. In optical
communication, there are two major modulation techniques:
Electro-Absorption modulator and Mach-Zehnder
modulator.
Electro-Absorption Modulator (EAM). Electro-Absorption
modulator is a semiconductor device which can be used for
modulating the intensity of a laser beam via an electric
voltage. A change in the absorption spectrum caused by an
applied electric field, which changes the band gap energy
(thus the photon energy of an absorption edge) but usually,
does not involve the excitation of carriers by the electric field.
The EAM is candidate for use in external modulation links in
telecommunications [10]. They can be operated at very high
speed; a modulation bandwidth of tens of gigahertz can be
achieved, which makes these devices useful for optical fiber
communication. A convenient feature is that an EAM can be
integrated with distributed feedback laser diode on a single chip to form a data transmitter in the form of a photonic
integrated circuit. Compared with direct modulation of the
laser diode, a higher bandwidth and reduced chirp can be
obtained.
Mach-Zehnder Modulator. A Mach-Zehnder modulator is
a intensity modulating signal light, using a simple drive
circuit for the modulating voltage. The modulator includes
two waveguides with respective multiple quantum well
(MQW) structures. Well layers of the MQW structures of the
two optical waveguides have different thicknesses or are
made from different materials so the phase of light
propagating through one waveguide advances and through
the other waveguide is delayed in response to the same
applied voltage. The phase-changed light signals are
combined as an output light signal that is intensity
modulated.
There are different types of coding are used such as NRZ,
RZ, AMI, Manchester, Differential Manchester and
Multi-state Coding. If the bit stream is to be sent as simply
the presence or absence of light on the fiber (or as changes of
voltage on a wire) then the simplest NRZ coding is possible.
In this method a one bit is represented as the presence of light
and a zero bit is represented as the absence of light [3]. This
method of coding is used for some very slow speed optical
links but has been replaced by other methods for most
purposes. In RZ coding the signal returns to the zero state
every bit time such as, a “1” bit is represented by a “ON”
laser state for only half a bit time. In a restricted bandwidth
environment (such as in most electronic communications)
there are two different line states required to represent a bit
(at least for a “1” bit) and this type of coding is not desired.
AMI (Alternate Mark Inversion) is a synchronous clock
encoding technique which uses bipolar pulses to represent
logical 1 value. The alternating coding prevents the build-up
of a D.C voltage level down the cable. This is considered an
advantage since the cable may be used to carry a small D.C.
current to power intermediate equipment such as line
repeaters. Manchester encoding is a type of digital encoding
that is used in data transmission. Within the structure for
Manchester encoding, the data bits in the transmission are
represented by a series of states that occur in a logical
sequence. This approach to data transmission is somewhat
different, as many encoding methods tend to assign a high or
low state of voltage to each bit and use that information as the
criteria for affecting the transfer of the bits. Differential
Manchester encoding is a method of encoding data in which
data and clock signals are combined to form a single
self-synchronizing data stream. It is a differential encoding,
using the presence or absence of transitions to indicate logical
value. This gives it several advantages over standard
Manchester encoding. Multi-state codes is a method in the
electronic systems where both signal amplitude and phase are
used to create unique line states representing particular bit
combinations.

IV. ERROR DETECTION AND CORRECTION METHODOLOGY
The general idea for achieving error detection and
correction is to add some redundancy (i.e., some extra data)
to a message, which receivers can use to check consistency of
the delivered message and to recover data determined
282International Journal of Future Computer and Communication, Vol. 3, No. 4, August 2014

erroneous. Error-detection and correction schemes can be
either systematic or non-systematic. In a systematic scheme,
the transmitter sends the original data, and attaches a fixed
number of check bits (or parity data), which are derived from
the data bits by some deterministic algorithm . If only error
detection is required, a receiver can simply apply the same
algorithm to the received data bits and compare its output
with the received check bits; if the values do not match, an
error has occurred at some point during the transmission. In a
system that uses a non-systematic code the original message
is transformed into an encoded message that has at least as
many bits as the original message. If the channel capacity
cannot be determined or is highly varying, an error-detection
scheme may be combined with a system for retransmissions
of erroneous data. This is known as automatic repeat request
(ARQ) and is most notably used in the Internet. An alternate
approach for error control is hybrid automatic repeat request
(HARQ) which is a combination of ARQ and
error-correction coding [3] .
Error detection is most commonly realized using a suitable
hash function (or checksum algorithm). A hash function adds
a fixed-length tag to a message, which enables receivers to
verify the delivered message by recomputing the tag and
comparing it with the one provided. There exists a vast
variety of different hash function designs. However, some are
of particularly widespread use because of either their
simplicity or their suitability for detecting certain kinds of
errors (e.g., the cyclic redundancy check 's performance in
detecting burst errors ). Random error correcting codes based
on minimum distance coding can provide a suitable
alternative to hash functions when a strict guarantee on the
minimum number of errors to be detected is desired.

V. OPTICAL FIBER
An optical fiber is a thin, flexible, transparent fiber that
acts as a waveguide , or "light pipe", to transmit light between
the two ends of the fiber. Optical fibers are widely used in
fiber-optic communications , which permits transmission over
longer distances and at higher bandwidths (data rates) than
other forms of communication. There are two basic types of
fiber: Single Mode Optical Fiber and Multi Mode Optical
Fiber. Multiple color coded 900 um tight buffered fibers can
be packed tightly together in a compact cable structure, an
approach widely used indoors; these cables are called tight
buffered cables [3]. Tight buffered cables are used to connect
outside plant cables to terminal equipment, and also for
linking various devices in a premises network. Multi-fiber,
tight buffered cables often are used for intra-building, risers,
general building and plenum applications. Tight-buffered
cables are mostly built for indoor applications, although some
tight buffered cables have been built for outdoor applications
too. Elements in a tight buffered fiber optic cable: Multiple
900 um tight buffered fibers (stranded around the central
strength member), Central strength member (in the center of
the cable), Ripcord (for easy removal of outer jacket), Outer
jacket (also called sheath, PVC is most common for indoor
cables because of its flexible, fire-retardant and easy
extrusion characteristics).
On the other hand multiple (up to 12) 250 um coated fibers
(bare fibers) can be put inside a color coded, flexible plastic tube, which usually is filled with a gel compound that
prevents moisture from seeping through the hollow tube.
Buffer tubes are stranded around a dielectric or steel central
member. Aramid Yarn is used as primary strength member.
Then an outer polyethylene jacket is extruded over the core
[9]. These cables are called loose tube cables. Loose tube
structure isolates the fibers from the cable structure. This is a
big advantage in handling thermal and other stresses
encountered outdoors. Loose-tube cables typically are used
for outside-plant installation in aerial, duct and direct-buried
applications. Elements in a loose tube fiber optic cable:
Multiple 250 um coated bare fibers (in loose tube), one or
more loose tubes holding 250um bare fibers [10]. Loose
tubes strand around the central strength member.
Moisture-blocking gel is used in each loose tube for water
blocking and protection of 250 um fibers. Central strength
member (in the center of the cable and is stranded around by
loose tubes). Aramid Yarn as strength member and Ripcord
for easy removal of outer jacket. Outer jacket (Polyethylene
is most common for outdoor cables because of its moistur e
resistant, abrasion resistant and stable over wide temperature
range characteristics).

TABLE I: GENERATED OTDR’S REPORT INFORMATIONS
General Information
Filename: Qubee0042c2_1310.sor Cable ID: 20133bd
Test date: 6/14/2010 Fiber ID: oou13d d
Test time: 9.49 PM(GMT+06.00) Job ID: A1
Location A: ABB Location B: CDC
Unit model: FTB -7300D -236B -E1 Unit’s s/n: 372208
Results
Span length: 7.2554 km Average Space loss: 0.102 dB
Span loss: 3.067 dB Maximum Space loss: 0.264 dB
Average loss: 0. 426 dB/km Span ORL: <18.76 dB
Test Parameters
Wave length: 1310 nm (9 um) Duration: 30 s
Range: 10,0000 km High Resolution: Yes
Pulse: 10,000 ns Resolution 0.319 m
Test Settings
IOR: 1.467700 Space loss threshold: 0.020 dB
Backscatter: -79.44 dB Reflectance threshold: -72.0 dB
Helix factor: 0.00% End of fiber threshold: 5.00 dB

VI. OPTICAL SIGNAL LOSS AND BIT ERROR RATE ANALYSIS
A. Optical Signal Loss Analysis
In optical fiber light is represented as signal and this signal
carry individual bit. Bit error is totally dependable on signal
loss. To find out the bit error correction in optical fiber the
practical works is accomplished in Link-3 to observe the
signal loss in fiber optics communication. Optical Time
Domain Reflectometer (OTDR) device has been used in this
regard and three individual distances (1.01km, 53.045km,
and 98.61km) is considered finding out the error [3]. The
example (based on a practical experience at Link-3 fiber
network) states the signal loss particularly. The object of the
fiber optic network is to calculate the attenuation – limited
fiber length based on a power budget equation then to
simulate and verify that is meets the performance objectives.
The power budget equation states that the transmitted power
minus the receiver sensitivity must be greater than or equal to
the sum of the power losses plus the power margin as:
283International Journal of Future Computer and Communication, Vol. 3, No. 4, August 2014

T R F C AP S AL L L M    

where,
TP
is the transmitter,
RS
is the receiver sensitivity,
A
is the fiber attenuation,
FL
is the fiber length,
CL
is the
coupling loss,
AL
is the additional know losses and
M
is
the power margin.
B. Fiber Signal Losses Calculation
In the experiment, the fiber’s length, attenuation and splice
loss of a relatively short unknown optical fiber link are
measured using the OTDR at 1310 operating wavelengths.
An example of OTDR generated report is shown in Table I
and the results are depicted in Fig. 1 and ODTR event table is
shown in Table II. The general information of Table II is shown in Table III.
In the event Table II, Number (Num.), Location/Length
(Loca./L), Reflection (Refl.), Attenuation (Atten.),
Cumulative (Cumul.), Launch Level (LL), Non-Reflective
Fault (NRF), Reflective Fault (RF), Positive Fault (PF) are
shown.

Fig. 1. OTDR generated test results.
Fig. 2. The diagram of analyzed BER.
TABLE II: THE OTDR’ S EVENT TABLE
Type Num Loca./L
(km) Loss
(dB) Refl.
(dB) Atten.
(dB/km) Cumul.
(dB)
LL 1 0.000 -23.2 0.000
Section 0.321 0.080 0.250 0.080
NRF 2 0.321 0.284 0.364
Section 1.985 0.631 0.318 0.995
NRF 3 2.306 0.086 1.082
Section 0.904 0.280 0.310 1.362
NRF 4 3.210 0.158 1.520
Section 0.688 0.225 0.326 1.744
NRF 5 3.898 0.226 1.970
Section 1.157 0.497 0.429 2.467
NRF 6 5.055 0.172 2.639
Section 1.280 0.443 0.346 3.082
NRF 7 6.335 -0.317 -14.6 2.765
Section 0.921 0.322 0.350 3.087
RF 8 7.255 3.087
In Section II and V of the Table II, it is observed 0.28 dB
and 0.22 dB signal loss, respectively. The signal loss point
has to optimize the signal loss in fiber optic communication.
The near-end zone of fiber A is fully visible before this
reflection without any blinding by the front connector peak.
The marker and manual measurements information of the
Table II are shown in Table III.
C. Analysis of the BER
The BER may be analyzed using stochastic computer
simulations. If a simple transmission channel model and data
source model is assumed, the BER may also be calculated
analytically. In absence of available device for BER analysis,
Optical Time Domain Reflectometer (OTDR) has been used
for checking the signal loss in fiber optics and the
OptiSystem 9.0 for analyzing the BER. The circuit diagram
284International Journal of Future Computer and Communication, Vol. 3, No. 4, August 2014

of Fig. 2 has been used to do this analysis.

TABLE III: THE OTDR’ S EVENT GENERAL INFORMATION
Marker Information
A: 0.2588 km 18.459 dB B: 0.2895 km 18.437 dB
A: 0.1344 km 18.461 dB b: 0.5381 km 18.038 dB
B-A: 0.0306 km 0.023 dB
Manual Measurements
4-pt. ev. loss 0.127 dB A-B LSA att. -0.819 dB/km
A-B LSA loss -0.025 dB 3-pt. reflectance ………..
2-pt. sect. att. 0.733 db/km A-B ORL 54.70 B

D. The Components of the BER Diagram
Input bit sequence, Signal pulse generator: RZ pulse
generator and NRZ Pulse generator, Modulation Technique:
Mach-Zehnder and Electro -Absorption, Optical input power:
20 dB and 15 dB, cabl e 50 k m, A low pass filter, BER analyzer [6]. The following components of the BER diagram
vary the result: Signal pulse generator, Modulation technique,
Input optical Power. The four bits results are shown in Fig. 3
as well as in the Table IV whereas the eight bits results are
shown in Fig. 4 as well as Table V.

TABLE V: EIGHT -BITS RESULT FROM BER ANALYSIS
Input Bits Signal
Generator Modulation
Technique Optical
Power (dB) Min
BER
10101100 RZ MZ 20 7.94587× e-122
10101100 RZ EAM 20 0
10101100 NRZ MZ 20 3.09973× e-28
10101100 NRZ EAM 20 3.84761× e-28
10101100 RZ MZ 15 1.86539× e-59
10101100 RZ EAM 15 7.99419× e-132
10101100 NRZ MZ 15 1.06647× e-37
10101100 NRZ EAM 15 4.50779× e-53

Fig. 3. Four bits BER analysis.

Fig. 4. Eight bits BER analysis.
285International Journal of Future Computer and Communication, Vol. 3, No. 4, August 2014

For four bits input 1010, Signal Generator: RZ,
Modulation Technique: Mach Zehnder, Optical Power: 20
dB, Minimum BER would be 1.85389× e-197 which is shown
in Fig. 3 as well as Table I V.
For the eight bits input 10101100, Signal Generator: RZ,
Modulation Technique: Electro Absorption, Optical Power:
20 dB, Min BER would be 0 as in Fig. 4 as well as Table V.

TABLE IV: FOUR BITS RESULT FROM BER ANALYSIS
Input
Bits Signal
Generator Modulation
Technique Optical
Power (dB) Min.
BER
1010 RZ MZ 20 1.85389e-197
1010 RZ EAM 20 0
1010 NRZ MZ 20 0
1010 NRZ EAM 20 0
1010 RZ MZ 15 0
1010 RZ EAM 15 0
1010 NRZ MZ 15 1.28085 e-203
1010 NRZ EAM 15 0

VII. CONCLUSION
In this study, a signal post processing approach has been
suggested and tested on ODTR data signals that have been
transmitted through single mode transmission system. The
methods proposed to calculate the true average signal loss in
the fiber optic communication; the single ended measurement
offers a huge advantage in terms of time, logistics, result
reliability and processing effort. The optimum solution
reduces the bit error rate by using RZ signal generator
through Electro Absorption modulation techniques.
Numerical simulation shows a noticeable improvement of the
system BER after optimization of the suggested processing
operation on the detected electrical signals at central
wavelengths in the region of 1310 nm. The operation of
optical transmission networks will be most important features
in the near future to serve the ever increasing demand of IP
networks. However, a lot of research works needs to be
carried out to improve the increasing effective data
transmission through these systems.
ACKNOWLEDGMENT
Warm expression and sincere thanks to Link3
Technologies Ltd., and system engineer Wahid Ferdous of
Fiber optic department for his support to the experiment.
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[4] Signal- to-Noise Ratio. [Online]. Available:
http://en.wikipedia.org/wiki/Signal- to-noise_ratio [5] Techlib . [Online]. Available: http://www.techlib.com/reference/q.html
[6] I. B. Akca, A. Dana, A. Aydinli et al ., “Electro-optic and
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[7] Fixed-Point vs. Floating-Point DSP for Superior Audio , Rane
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286International Journal of Future Computer and Communication, Vol. 3, No. 4, August 2014
S.M. Jahangir Alam has been completed B.Sc. in
computer science and engineering from Dhaka Intl.
Univ., and he received his M.S degree in
telecommunications from the Univ. of Info. Tech. &
Sci. (UITS), Dhaka, Bangladesh. He is a PhD candidate
(June, 2014) in the Dept. of Mech. & Electrical Engg. at
Xiamen University, China.
He was a lecturer of electronic and communicati on engg. & coordinator of
the School of Comp. Sci. & Engg. at UITS from 2006 to 2010. He is
interest edin vision & image processing , TFT -LCD display defect detection ,
time series analysis ,detection t echnology , and automation .
M. Rabiul Alam has been completed M.S. and awarded
Ph.D. in electrical engineering from Moscow State
Mining University, Moscow, Russia. From 2004 to 2006
he was a post-doctoral researcher (energy management)
at the same University.
He is an associate professor and the head of the
Department of Elect. & Electronic Engg. at Hamdard
University Bangladesh from 2012. During 2008 -2012, he
was an associate professor and the head of the Dept of Electrical and
Electronic Engineering and dean of the School of Comp. Sci. and
Engineeri ng at Univ. of Info. Tech. and Scie. (UITS), Dhaka, Bangladesh.
During 2007 –2008 he was an associate professor of the Dept. of Electrical &
Electronic Engineering at International Univ. of Business Agriculture and
Tech. (IUBAT), Dhaka, Bangladesh. His fiel d of interest is power
engineering, renewable energy and energy management.
Guoqing Hucompleted his B.S. and M.S. in the Dept .
of Automation Control from Northwestern
Polytechnical Univ. China and was awarded Ph.D. in
mechanical engineering from Sichuan Univ. (PRC). In
1993 -1995, he was a post -doctoral researcher in the
Dept. of Mechanical Engineering, Shanghai Jiaotong
University (PRC).
He isa professor of the Dept. of Mech. & Elect. Engg. at Xiamen
University, China since 1995 .During 1993 -1995, he was an associate
professor in the Dept. of Mech. Engg., Shanghai Jiaotong Univ. In Jan
2000 -Feb 2001, he was a visiting professor in the Dept. of Elect. Engg. &
Comp. Sci, Elect. De sign Center, Case Western Reserve University (USA) .
From February 2002 to August 2002 he was a visiting professor in the Dept.
of Automation & CAE at The Chinese Univ. of Hong Kong (Hong Kong).
Hismajor research area s are advanced sensors, electromechanical control,
mems, high temperature measure & detection technology, industrial
automation and robot, fluid transmission and control , etc.
Md. Zakirul Mehrab has completed his BSc in Engg.
from Dhaka Intl. Univ., Dhaka, Bangladesh and MS in
telecommunications from UITS, Dhaka, Bangladesh.
He is an executive of Spark Technologies &
Consultancy Ltd., Bangladesh. His field of interest is
data communications .