A simulation study of wi max based communication system using deliberately clipped ofdm signal

IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
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Volume: 03 Issue: 03 | Mar-2014, Available @ http://www.ijret.org 704
A SIMULATION STUDY OF WiMAX BASED COMMUNICATION
SYSTEM USING DELIBERATELY CLIPPED OFDM SIGNAL
Mazid Ishtique Ahmed1
, Chowdhury Muktadir Rahman2
, Sabiha Sattar3
1
Lecturer, Faculty of Science & Technology, Atish Dipankar University of Science and Technology, Dhaka, Bangladesh
2
Specialist, PS Core Planning, Robi Axiata Limited, Dhaka, Bangladesh
3
Engineer, Electronics Division, Bangladesh Atomic Energy Center, Dhaka, Bangladesh
Abstract
WiMAX is a highly sophisticated technology in the broadband wireless access communication system. Scalable Orthogonal Frequency
Division Multiple Access (OFDMA) is a key technology behind mobile WiMAX and it is also expected to play a key role in 3GPP
Long Term Evolution (LTE) standards. Designers and OEMs have to concentrate on flexibility, scalability and stability of the overall
Orthogonal Frequency Division Multiplexing (OFDM) system along with its proper data processing and channeling process to
achieve high performance and competitiveness. In this paper, the performance of a strictly band limited OFDM signal is examined
using deliberate clipping method, one of the simplest signal distortion based way to reduce high Peak to Average Power Ratio (PAPR)
and its effect on the resultant Bit Error Rate (BER) against Signal to Noise Ratio (SNR) performance. A simulation program using
MATLAB software was developed to investigate performance of OFDM signal by optimization of different parameters such values of
FFT size, Cyclic Prefix co-efficient (CPC) and The Voltage Clipping Ratio (VCR). The simulation results show that with the increment
of VCR at optimized parameter values of FFT size and CP, the performance of BER vs SNR improves compared to the results found
without clipping.
Keywords: WiMAX, PAPR, OFDM, CPC, Voltage Clipping Ratio, Deliberately Clipped
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1. INTRODUCTION TO WIMAX TECHNOLOGY
Wireless communications have become increasingly popular
and broadly required in today’s fast paced world, specially for
the people of developing countries like Bangladesh. Instant
access to virtually unlimited information and resources has
become the way of life for individuals in different sector of
living and earning their livelihood. Access to various forms of
information such as image, data, voice, video and multimedia
in an easily communicable, securely and in cost effective
manner are the basic requirements of modern day technology
savvy society.
Wi-Fi (IEEE Standards based 802.11) has dominated as the
most popular wireless access technology within the home and
office since 2005 due to its cheaper hardware price, easy to
use and interoperability within a range of 30 meters. When
used in Metropolitan Area network (MAN) the operation of
Wi-Fi started to face challenges for its range, QoS and
security. Standard Wi-Fi technology is limited to 100m range
in Line-of-Sight (LOS) environment which in the pre-release
versions of 802.11n got standardized to 250m by the use of
MIMO Antenna at both Access Point and The Subscriber
Station [1]. Despite all the developments, Wi-Fi remains
limited to LAN space in terms of range and depends on WAN
technologies to bridge the last miles to access internet and
external connectivity.
Broadband Cellular Wireless (BCW) system thus appears as
the technique to satisfy this rapidly growing demand of
communication systems. A key benefit of it is the ability to
use bidirectional antennas which results in improved strength
of signal on both directions. The standards 802.16d and
802.16e popularly known as WiMAX (Worldwide
Interoperability for Microwave Access) become a key
technology in mitigating the previous issues of range. Since
the late 90s, WiMAX technology based communication
system has been addressed y the IEEE802.16 group which was
formed in 1998 to develop an air-interface standard for
wireless broadband. The original 802.16 standard was based
on single carrier physical (PHY) layer with a burst Time
Division Multiplexed (TDM) Machine Access Control (MAC)
layer. After that the IEEE 802.16 group subsequently
produced 802.16a (an amendment to the standard), to
introduce NLOS applications in the 2GHz~11GHz band, using
OFDM based PHY layer with addiotnal support of OFDMA in
the MAC layer. In December 2005, the IEEE group completed
and approved IEEE 802.16e-2005, an amendment which
added mobility support and forms the basis for the WiMAX
solution for mobile applications referred as mobile WiMAX
[2]. And the WiMAX forum has been formed to promote the
interoperability between manufacturers and vendors for the
conformance to the standard.

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2. ORTHOGONAL FREQUENCY DIVISION
MULTIPLEXING (OFDM)
Mobile WiMAX uses OFDM as a multiple access technique
which is a joint process of modulation and multiplexing.
Fig-1: Functional Block Diagram of OFDM Signal Generation
In OFDM, multiplexing operation is performed on
independent signals which are a sub-set of the one main
signal. The signal first itself is split into independent channels,
modulated by data and then multiplexed to create the OFDM
carrier.
The main concept in OFDM is Orthogonality of the sub-
carriers. As all the sub-carriers are sine or cosine wave, area
under one period of sine or cosine wave is zero and the area
under a sine wave multiplied by its own harmonic is always
zero. Thus orthogonality allows simultaneous transmission on
a lot of sub-carriers in a restricted or tight frequency space
without being interfered with each other. In this way, it is
quite similar to the technique adapted in CDMA where codes
are used to make data sequences independent (also
orthogonal) and allowing many independent users to transmit
in same space successfully.
2.1 Applications and Parameters of real OFDM
System
OFDM is a vastly adapted data multiplexing technique for
high speed networks and has gradually increased in
commercial usage over the last decade. It is now proposed for
radio broadcasting such as in Eureka 147 standard and Digital
Radio Mondiale (DRM) [3]. OFDM is used for modem/ADSL
application where it co-exists with phone line which is called
Discrete Multi Tone (DMT). OFDM also forms the basis for
the Digital Audio Broadcasting (DAB) standard in European
Market [4].
Table -1: Parameters of real OFDM system
Data rates 6 Mbps to 48 Mbps
Modulation BPSK, QPSK, 16 QAM and
64 QAM
Coding Convolutional concatenated
with Reed Solomon
FFT Size 4 with 52 sub-carriers. 48
for data and 4 for pilots.
Sub-carrier Frequency
Spacing
20 MHz divided by 64
carriers
FFT Period 3.2 µsec
Guard Duration 0.8 µsec
Symbol time 4 µsec
2.2 OFDMA (Orthogonal Frequency Division
Multiple Access)
OFDMA is a multi user version of the popular OFDM digital
modulation scheme. Multiple Access is achieved by assigning
subsets of sub-carriers to individual users. This allows
simultaneous low data transmission rate from several users.
OFDMA is fast growing in several applications which are the
heart of next generation of wireless communication. Apart
from WiMAX, it is adapted for the IEEE 802.20 mobile
Wireless MAN standard which is commonly referred as
MBWA following to the Evolved UMTS Terrestrial Radio
Access (E-UTRA). Figure 2-2, illustrates an overview of the
Physical Layer (PHY) for WiMAX base-station with scalable
OFDMA based on IEEE 802.16e-2005 [5].
Fig -2: Overview of IEEE 802.16e-2005 Scalable OFDMA
Physical Layer for WiMAX Base-stations

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3. PEAK TO AVERAGE POWER RATIO (PAPR)
PROBLEM IN OFDM SYSTEM AND SOLUTIONS
In advanced mobile communication, OFDM has brought
unique features such as high spectral efficiency, robustness to
channel fading, immunity to impulse interference and
capability of handling very strong multipath fading and
frequency selective fading without having to provide power
channel equalization [6]. On the other hand, an OFDM signal
responses with higher instantaneous peak value with respect to
the average signal level causing large amplitude swings when
time domain signal travels from a low instantaneous power to
high power waveform. As a result, unless the transmitter’s
power amplifier exhibits an extremely high linearity across the
entire signal level range, high Out-Of-Band (OOB) harmonic
distortion of power waveform becomes significant which
potentially causes interference with adjacent channel. That is
why; large Peak to Average Power Ratio (PAPR) is marked as
a major issue associated with OFDM signal generation which
leads to system performance degradation due to distortions
introduced by power amplifiers (PA) or other non-linear
devices of the transmitter block.
3.1 PAPR Definition and Mathematical
Representation
PAPR (Peak to Average Power Ratio) is a measurement of
waveform, calculated from the peak amplitude of the
waveform divided by the RMS value of the waveform. It
implies that the PAPR is the maximum instantaneous power
normalized by the average power among all possible data
patterns. This definition is especially important for the system
in which some special coding is employed that has some
constraints in the data sequences control the PAPR very low.
There thus appear two definitions largely accepted of PAPR
for OFDM signal, one of that definition is to assume the
PAPR can be expressed in deterministic value [7] [8], that is –
D − PAPR = sup
−∞<t∞
ζ(t) = sup max
0≤t≤Tu
ζ1 t … … … … … (1)
3.2 PAPR in OFDM System
The PAPR in OFDM system increases exponentially with the
number of sub-carriers. To evaluate that, let, A = [A0, A1,
…….. , A(N-1)] to be modulated data sequences of the length
N during the time interval of [0,T], where Ai is a symbol from
a signal constellation and T is the OFDM symbol duration.
Then the complex envelope of the baseband OFDM signal for
N carriers is given by [8],
s t = An
N−1
n=0
exp jω0nt … … … … … … … … … … … … (2)
Where, ω0 =
2π
T
and j = p-1
In practical systems, a guard interval (cyclic prefix) is inserted
by the transmitter in order to remove inter-symbol interference
(ISI), and inter-channel interference (ICI) in multi-path
environment. However in can be ignored since it does not
affect PAPR The PAPR of the transmit signal s(t) in equation
2, is the ratio of the maximum instantaneous power and the
average power [9], that is –
PAPR A =
max |s(t)|2
E {|s(t)|2}
… … … … … … … … … … … … … (3)
Where, E {.} denotes the expectation operator.
Usually the continuous time PAPR of s(t) is approximated
using the discrete time PAPR shown in equation 3, is obtained
from the samples of the OFDM signal.
3.3 Techniques to reduce PAPR in OFDM system
Several schemes have been proposed to reduce PAPR. These
techniques can mainly be divided into two categories [6].
Those are –
A) The Signal Scrambling techniques are all variations
on how to scramble the codes (or modify the phases)
to decrease the PAPR. Golay complementary
sequences, Shapiro-Rudin sequences, M-sequences,
Baker codes can be used to efficiently reduce the
PAPR. However, with the increase in the number of
carriers, the overhead associated with the exhaustive
search or the best code would increase exponentially.
More practical solutions of the scrambling
mechanism are block coding, selective mapping and
partial transmit sequences. Selective mapping and
partial transmit sequences are two probabilistic
schemes to reduce PAPR.
B) The Signal Distortion techniques reduce higher
peaks directly by distorting the signal prior to
amplification. Clipping the OFDM signal before
amplification is a simple method to limit PAPR.
More practical solutions are Peak Windowing, Peak
Cancellation, Peak Power Suppression, Weighted
Multi-Carrier transmission, Companding and
Deliberate Clipping.
3.4 PAPR Reduction by Deliberate Clipping
If the number of subcarriers increases however, the peak-to-
average power ratio (PAPR) of the OFDM signal also
increases. In many wireless applications, both the peak power
efficiency and the bandwidth efficiency are the two most
important factors [10]. In strictly band-limited systems, the
OFDM signal exhibits a prohibitively high PAPR; and without
use of any PAPR reduction technique, efficiency of power
consumption at the transmitter becomes very poor.

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The deliberate clipping method may be one of the simplest
solutions when the number of sub-carriers is large [11], [12].
The clipping operation causes degradation due to the nonlinear
operation, which requires some compensation the deliberate
clipping is performed followed by the band pass filter, and the
resultant performance degradation is compensated by the BCH
codes [13]. On the other hand, the OFDM signal sampled at
the Nyquist rate is clipped and the degradation is compensated
by the iterative decision-aided reconstruction of the original
OFDM signals [14].
When the clipping is performed on the oversampled OFDM
signals, it generally causes the out-of-band radiation of the
clipped power, and the band pass filter is required to suppress
the out-of-band radiation. The problem of this scheme is the
significant PAPR regret due to the band pass filtering [11]. On
the other hand, when the clipping is performed on the signals
at Nyquist sampling rate, all the distortion noise falls in-band,
avoiding the out-of-band radiation due to the deliberate
clipping, assuming that the signal is linearly amplified [11],
[14].
Fig-3: Band Limited OFDM system with Nyquist-rate
Clipping
Therefore, in the latter case, the band pass filter for removal of
out-of-band radiation is not required. However, probably less
recognized is the fact that the ideal low-pass (interpolation)
filter (LPF) after clipping illustrated on figure 3, which is
necessary for strictly band-limited communications systems,
also considerably enlarges the PAPR [15]. Consequently, in
such systems the PAPR after the ideal LPF should be taken
into account for the evaluation of the PAPR.
Theoretical analysis of the PAPR property of the clipped and
low-pass filtered OFDM signals appears quite involved, and
thus the PAPR property is studied by extensive computer
simulations. In this paper, the definitions and the theoretical
remarks that may be useful to describe the PAPR property of
the OFDM signals is described.
Let, sn, n=0,1,…..,N-1 denote the output of the N-point inverse
discrete Fourier transformer (IDFT), and let x(n) and y(n) be
the real and imaginary parts of sn, respectively. Since the
input data can be assumed statistically independent and
identically distributed, the x(n) and y(n) are uncorrelated.
Furthermore, for large N, the distribution of both x(n) and y(n)
approaches Gaussian with zero mean and variance, say σ2
, ,
due to the central limit theorem. Since the uncorrelated
Gaussian random variables are statistically independent x(n)
and y(n) are orthogonal, and x(n) and y(n) can be assumed, at
least asymptotically, statistically independent. Thus, in the
following, it is assumed that the x(n) and y(n) are Gaussian
random variables.
As a clipping model of the baseband signal, the soft envelope
limiter block shown in figure 3 is considered as the function of
clipping; the output sample is thus given by –
rn ≜ g rn =
rn ; rn ≤ Amax
Amax ; rn > Amax
… … … … … … … … … (4)
Where, rn ≜ s n = (xn
2 + yn
2 ) is the amplitude of the nth
sample of complex OFDM signal and Amax is the maximum
permissible amplitude over which the signal is clipped.
The clipping ratio 𝛾 is defined as,
𝛾 ≜
𝐴 𝑚𝑎𝑥
𝑃𝑖𝑛
=
𝐴 𝑚𝑎𝑥
2𝜎
… … … … … … … … … … … … … … … (5)
Where, Pin = 2σ2
is the input power of the OFDM signal before
clipping.
The total output power Pout, which is the sum of the signal and
distortion components, is given by,
𝑃𝑜𝑢𝑡 = 𝐸𝑟𝑛 𝑔2
𝑟𝑛 or,
𝑃𝑜𝑢𝑡 = 1 − 𝑒−𝛾2
𝑃𝑖𝑛 … … … … … … … … … … … … … … (6)
Normalizing the clipped signal by the rms output power, the
sample of the output amplitude is redefined as –
𝑟𝑛 =
𝑔(𝑟𝑛 )
𝑃𝑜𝑢𝑡
=
𝑔(𝑟𝑛 )
1 − 𝑒−𝛾2
𝑃𝑖𝑛
… … … … … … … … … (7)
It is to be noted that 𝛾 cannot be zero by the definition [16].
However, considering the amplitude normalized by the rms
output power, it can be defined that 𝛾 ≠ 0 by its limit as,
lim
𝛾→0
𝑟𝑛 ≤ lim
𝛾→0
𝐴 𝑚𝑎𝑥
𝑃𝑜𝑢𝑡
= lim
𝛾→0
𝛾
1 − 𝑒−𝛾2
𝑃𝑖𝑛
= 1 … (8)
That is, rn = 1 for all n, which corresponds to the hard
(constant) envelop limiter.

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4. SIMULATION RESULTS OF PERFORMANCE
ANALYSIS OF OFDM SIGNAL
In this section, result of the simulation study on the
performance is discussed. To study and find the optimizations,
an algorithm illustrated in figure 4, was simulated using
MATLAB simulation software. The total analysis is divided
into two different parts of which discussed in section 4.1
which deals to determination of optimum FFT size and cyclic
prefix co-efficient by analyzing the bit error rate vs signal-to-
noise ratio curves followed by results enlisted in section 4.2
which shows the difference or improvement of performance of
the baseband OFDM signal while voltage clipping ratio is
introduced and optimized.
Fig -4: Flow Chart of WiMAX based OFDM Signal for
Simulation
4.1 Optimization of Parameters
4.1.1 Determination of Optimum FFT Size
As shown in the flow chart in figure 4 and also illustrated in
figure 1, OFDM signal generation requires the IFFT block to
convert the signal from frequency domain to the time domain
representation which is essential for estimating the Signal-to-
Noise Ratio (SNR) of the OFDM signal. The SNR is a
function of the FFT size used for the conversion. In the
simulation, the performance of the generated OFDM signal is
analyzed in terms of BER to SNR by optimizing proper FFT
size.
To overcome the problem of the Inter Symbol Interference
(ISI) anther parameter is defined as the Cyclic Prefix (CP). For
OFDM signal transmission with multiple carriers, CP is
appended. Mathematically, the relation is illustrated below –
Cyclic Prefix Co − efficeint = Gi =
Tcp
Td
… … … … … (9)
Where, Tcp = Cyclic Prefix Duration
Td = Guard Duration
Cyclic Prefix Co-efficient or Gi is the ratio of guard duration
to the cyclic prefix duration. While optimizing the FFT size,
the Gi value was kept constant to 0.25.
The values of different parameters used in the simulation for
optimization of FFT size is illustrated in table 2. The results
are illustrated in
Table-2: Different Parameters used in the simulation for
optimization of FFT Size
Parameters Values
Modulation Scheme QAM 16
FFT Size 4, 16, 64, 128
Data Sub-carriers 52
Guard Duration 64
Cyclic Prefix Co-efficient 0.25
Using the same simulation model, the optimum value of
Cyclic Prefix Co-efficient was determined too. Table 3 shows
the simulation model parameters for this optimization. For this
investigation, the result of the FFT size optimization was kept
constant.
Table-3: Different parameters used in simulation for
optimization of Cyclic Prefix Co-efficient
Parameters Values
FFT Size 64
Guard Duration 64
Cyclic Prefix Co-efficient 0.1,0.2,0.3,0.4,0.5,0.6,0.
7,0.8,0.9

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Fig-5: Performance study to optimize FFT Size
Fig-6: Performance study to optimize Cyclic Prefix
Figure 5 illustrates the simulation results for optimizing FFT
size for the baseband OFDM signal using QAM16 modulation
technique. As the FFT size was varied through a range of
values from 4 to 128, it was observed that initially the
simulation results differed largely compared to theoretical
results. When FFT size was increased to 64, there was
significant improvement and for FFT size value 128, it was the
near perfect output. But as the FFT size increases, it offers
higher complexity in system designing for hardware
implementation [18]. That’s why the optimum value for FFT
Size is determined to be 64.
Determining the optimization for Cyclic Prefix Co-efficient,
Gi the FFT size obtained by the illustration in Figure 5 was
fixed at 64 and the similar simulation model was used. The Gi
values were varied from 0.1 to 0.9. The analysis is illustrated
on figure 6 where it is visually clear that BER to SNR curve
improves with the increase to the value of Gi. The best
optimizations were found in a range of 0.4 to 0.7 and for
Gi=0.5, the results were closer to that of the theoretical values.
As a result, the Cyclic prefix Co-efficient was best kept at
Gi=0.5 for optimum performance.
4.1.2 Determination of Optimum Voltage Clipping
Ratio (VCR)
The main objective of this paper is to study a special type of
signal distortion type PAPR reduction scheme which is
Deliberate Clipping which is performed by distorting the
signal prior to amplification as illustrated in figure 3.
A significant advantage of clipping is it makes the
transmission power efficient. However extensive clipping may
cause large Out-of-Band (OOB) and In-band interference.
That’s why it is highly required to investigate the clipping and
understand its effect on overall performance of the baseband
OFDM signal. The modified model for this simulation is
illustrated in figure 7.
In the simulated model all the parameters i.e. Modulation,
Data Sub-carriers are kept at the IEEE 802.16 standard [19].
The FFT size and Cyclic Prefix co-efficient is set according to
the optimum value found in the earlier simulation illustrated in
the section 4.1.1
In this paper, a term called “Voltage Clipping Ratio (VCR)” or
Cp which is mathematically it is represented as –
Cp =
|Am |
A
… … … … … … … … … … … … … … … … (10)
Where, Am = Amax or Amin = Maximum or Minimum clipping
voltage and A = Clipping threshold voltage. The value of VCR
was varied in a range of 5% to 40% and observed in terms of
the improvement of BER vs SNR curve with respect to earlier
optimized results which were performed without clipping the
signal. Table 4 lists the parameters for the modified model of
simulation.
Table 4: Parameters to optimize the Voltage Clipping Ratio
Parameters Values
FFT Size 64
Guard Duration 64
Cyclic Prefix Co-efficient 0.5
Voltage Clipping Ratio (VCR) 5% - 40%

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Fig 7: Modified Block diagram of WiMAX based OFDM signal using Deliberate clipping
The results of simulation found by increasing VCR are shown in figures 8, 9, 10, 11, 12 and 13.
Fig 8: Performance of Clipped OFDM signal for VCR=5%
Data
generation
Deliberate
Clipping
Serial to
Parallel
IFFT Parallel
to Serial
Grouping
into multi-
symbol
Zero
Padding
Appending
Cyclic
Prefix
Generated Gaussian
Noise
Zero
Removal
Received
Data
Added Noise
Removing
Cyclic
Prefix
Taking
FFT

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The clipping ratio is kept 5% in figure 8 and it can be seen
from the simulated result the performance has not increased
from the without clipped signal. When the clipping ratio is
increased to 10% in figure 9 the simulated results shows much
improvement than the 5% clipping ratio. In figure 10, clipping
ratio has been increased to 15% but the performance is
declining. As with 25% clipping ratio in figure 11, the
performance in most of the cases is same as without clipping
result with no improvement or increased performance. But in
figure 12 at 30% clipping ratio, the result is much improved
from without clipping and in some cases almost same as
without clipping. And finally at 40%, there is deviation from
the much improved results obtained for VCR at 30%. So, from
the simulated result it is obvious that the most optimum
clipping ratio for a wide range of SNR would be 30%. Which
gives a better performance for the simulated BER – SNR and
at the same time would also reduce the PAPR making it the
most optimum clipping ratio.
5. CONCLUSIONS
The nonlinear distortion effects in OFDM transmission have
been investigated in many research works. An analytical
expression for the output autocorrelation function based on
HPA modeling with Bessel series expansion is derived. By
using Fourier transformation, the output autocorrelation
function can provide information on the power spectral
density (PSD) at the HPA output, and at the same time, it
allows the analytical calculation of the power of the nonlinear
distortion noise [21]. The orthogonal polynomials provide an
intuitive means of spectral re-growth analysis and enable us to
derive a very simple analytical expression for the
autocorrelation function and hence the PSD of the nonlinear
noise. In this way, it is possible to derive an analytical BER
expression for the OFDM systems performance in presence of
nonlinear HPA in AWGN channels [20].
In this paper, in terms of observing the performance of OFDM
based WiMAX system, we limited our study within reducing
PAPR and improving the BER to SNR of OFDM signal by
Deliberate Clipping technique. On the other hand, the OFDM
signals are highly sensitive to non linear distortions introduced
by the High Power Amplifier (HPA). It has two effects on
transmission the first one, is the spectral re-growth of the
signal which leads to adjacent channel interference (ACI) and
the second one is the effect in the distortion of the signal in the
nominal frequency band which causes inter-symbol
interference (ISI).
Investigations in these directions are great attempts to
optimize OFDM performance enhancement and it is a matter
of utter satisfaction to conclude with the observations made
throughout the research work.
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BIOGRAPHIES
Mazid Ishtique Ahmed received his B.Sc. in
Electrical and Electronic Engineering degree
from Ahsanullah University of Science and
Technology, Dhaka, Bangladesh on 2010. For
following two years, he served as an It System
Support and Solution Design Engineer in data edge limited, a
system integrator and IT solution provider. He is in the
position of Lecturer in Atish Dipankar University of Science
and Technology and a graduate student in BRAC University,
Bangladesh. His research interest includes Advanced Wireless
Communication Technology fields of LTE and OFDM system
implementation with performance enhancement solutions.
Chowdhury Muktadir Rahman received his B.Sc.
in Electrical and Electronic Engineering degree
from Ahsanullah University of Science and
Technology, Dhaka, Bangladesh on 2010.
Currently positioned as Specialist, PS Core
Planning for Robi Axiata Limited, Bangladesh a renowned
GSM operator. He contains 5 years of professional experience
in IP technologies for GSM Carrier network in Mobile Back-
bone, GPRS, EDGE and HSPA+ technologies. He is an IP
technology expert with various vendor certifications in the
same field.
Sabiha Sattar completed her B.Sc. in Electrical
and Electronic Engineering degree from
Ahsanullah University of Science and
Technology, Dhaka, Bangladesh on 2010.
Currently positioned as Engineer, Electronics
Division, Bangladesh Atomic Energy Center (BAEC). She is
experienced and involved in Research and Development of
Micro-controller based embedded system.

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