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QPSK System Simulation
Dr. Stavros Georgakopoulos
Digital Communication Systems II
Florida International University
April 21, 2011
Jovan Robinson
Hassan Chaudhary
Napalys Juodzevicius
David Sanchez
QPSK System Simulation
Page 2
Table of Contents 1.0 Abstract................................................................................................................................................. 3
2.0 Introduction .......................................................................................................................................... 3
3.0 Theory ................................................................................................................................................... 8
4.0 Project Objectives ............................................................................................................................... 13
5.0 Proposed Methods.............................................................................................................................. 14
6.0 Results................................................................................................................................................. 20
7.0 Conclusion........................................................................................................................................... 27
8.0 References .......................................................................................................................................... 28
QPSK System Simulation
Page 3
1.0 Abstract Digital communications is an emerging industry in today’s engineering world.
Communication methods have been generated and applied since the beginning of time. Since
the invention of the first communication device, telegraph in 1844 by Samuel Morse,
communication has come a long way. With new technologies developed by engineers who
makes the day to day life has become easier. There are two types of communication schemes:
Analog and Digital communication. The difference between these two schemes is that the
analog signal is continuous and digital signal is discrete. Today’s communication engineers try
to find the best way to resolve the scarce resource of frequency spectrum. There are many
advances engineers have made throughout the years. Various types of modulations have been
implemented in current systems. Each of these modulations has different bandwidth
efficiency.
Quadriphase-Shift Keying (QPSK) has a more efficient use of bandwidth since it
transmits data in both phase and quadruture channel. QPSK can be modeled as the sum of two
Binary Phase Shift Keying Modulation (BPSK). Furthermore, both of these systems have the
same bit error rate. The difference is the amount of bandwidth utilized by both systems; BPSK
utilizes twice the bandwidth used by QPSK.
The purpose of this project is to identify the main characteristics of a QPSK system and
implementing them with software simulation. This will give a clear understanding of how the
system functions and the theory behind each component.
QPSK System Simulation
Page 4
2.0 Introduction
The QPSK system can be divided in three different subsystems: Transmitter, Channel
and Receiver. Each of these subsystems completes a different function for the system to be
reliable. First, the transmitter inputs a set of Binary numbers. Then these binary bits enter an
encoder to then convert the series to enter both the in-phase and quadruture channel
multiplying it with the oscillator. The receiver than receives this QPSK signal and multiplies
them with the oscillator with a -90° phase shift. This signal is send to a low pass filter to
attenuate any high frequencies within the system. Moreover, this signal is sampled and goes
through a decision making device. Finally, it converts the signal from parallel to serial to receive
the same signal as intended by the user.
Quadrature Phase-Shift Keying Applications
QPSK modulation is widely used in communications industry. It may be applied
whenever low bit error rate is required and high energy per symbol level is not possible. Three
typical areas of QPSK application are satellite, fiber optics, and Bluetooth technologies.
QPSK in Satellite Communications
Because of its robustness QPSK is well suited for the digital satellite communications.
Digital television standard called Digital Video Broadcasting (DVB) is an internationally adopted
open standard. DVB standards are set by the organization called DVB Project. It contains more
than 270 members worldwide. Though it is not used in the United States, it is widely adopted in
Europe, Asia, and Australia. DVB distribution systems include satellite (DVB-S), terrestrial (DVB-
T2), cable (DVB-C). One of the most common modulation schemes used by these distribution
systems is QPSK.
QPSK System Simulation
Page 5
Figure 1 JXDH-6002-6 QPSK Demodulator
Figure 1 illustrates the component used for receiving and transferring DVB-S
satellitechannels to Transport Stream (TS) signal. Chengdu Jiexun Electronics Co., Ltd.
QPSK in Fiber Optics Communications
Fiber optics technology is crucial for today’s communication systems. Because of its
significant advantages over copper network lines, fiber optics have become the main
technology for the long distance, high capacity core communication lines. Traditionally, fiber
optics until very recently has been using simple On-Off keying to transmit digital information
(zeros and ones), without the need of more advanced modulation schemes often used in other
communication systems. The reason for it was the inherent efficiency and broadband capability
of fiber optic technology. Today, with rapidly increasing demand for more bandwidth, network
engineers are beginning to look at more complex modulation schemes that would allow faster
transmission rates over existing fiber optic lines. This is where QPSK and other modulations are
applied. Specifically, QPSK variant called Dual Polarization QPSK (DP-QPSK) seems to be a
modulation standard applied to the newly developing 100GHz fiber networks. Dual polarization
enables the transmission of more channels on a given fiber by supporting a signal in two
QPSK System Simulation
Page 6
polarizations. It is essentially a combination of two QPSK signals that are transmitted on the
same frequency but they are polarized 90 degrees from each other to minimize their
interaction.
Figure 2 DP-QPSK modulation scheme. NORDUnet A/S
DP–QPSK system requires a coherent receiver. In the past, optical devices recognized
signals by detecting the intensity of the light, which was switched on and off by way of using a
more basic modulation format known as On–Off keying. The typical receiver operates much like
a simple envelope detector AM radio, whereas coherent receiver requires local oscillator. The
oscillator is tuned to the frequency of the incoming signal and only extracts that information.
The coherent receiver has to be able to lock onto both the frequency and phase of the DP–
QPSK signal in order to accurately recover the incoming bits. The great benefit of this system is
its capability to transmit four times the amount of data over existing fiber. In fact, the
equipment would be dealing with a signal that is four times slower than typical, and incoming
information can be processed by commonly available digital signal processing (DSP) technology.
QPSK System Simulation
Page 7
Figure 3 High Performance parallel driver designed for 100 GHz DP-QPSK long haul optical transmitters. Gigoptics, Inc.
QPSK in Bluetooth Communications
Bluetooth technology is a radio signal technology which uses spread spectrum and
frequency hopping. It splits the bandwidth into 79 smaller bands and transmits portions of data
through each channel, thus allowing 2 to 3 Mbps transmission rates. Older Bluetooth versions
were modulated using Gaussian Frequency-Shift Keying, which was later replaced by a QPSK
variant called Differential QPSK (DQPSK). DQPSK is designed to alleviate any phase ambiguity
that might be caused by a phase shift in the transmission channel and it also improved data
throughput from 1Mbps to 2Mbps.
Figure 4 Bluetooth Headset. Nokia Corporation
QPSK System Simulation
Page 8
3.0 Theory
Communication, with respect to the telecommunications field, is process that facilitates
the transmission of a message signal across some medium to a designated receiver. The type of
communication studied in this project is of the digital variety. In this scheme (shown below), a
discrete sequence of 1’s and 0’s representing the original signal is converted (modulated) to a
form that allows it to travel across the medium.
Figure 5
When comparing this method of transmission to its counterpart, analog communications,
digital communication have several key advantages: performance, reliability, integration with
other DSP techniques, security, and efficiency.
Band-pass Assumption
Digital communication schemes generally comprise of a device that transmits a
collection of pulses that represent the digitized information. Ideally, the pulse can be best
modeled with the sinc function (shown below). It is important to note that the main lobe of the
sinc function’s peak is equal to the square of the transmitted signal energy per bit.
QPSK System Simulation
Page 9
Figure 6
Alternatively, we can take the Fourier transform of the sinc pulse to obtain its frequency
response shown below. This ideal pulse shape mirrors that of a band pass filter in principle. This
implies that the overall transmission system has some minimum bit rate, Tb.
Figure 7
Nyquist Channel
QPSK System Simulation
Page 10
As stated above, digital communication schemes take in a bit stream, modulates it, and
sends the modulated wave across the channel. At the receiver, however, a number of things
can occur. Due to imperfections in the frequency response of the filter, deviations between the
sent and received messages can occur. One way of dealing with this involves requiring the
system to have a minimum transmission bandwidth contingent upon the rate at which the bits
are being sent and received. Using the fact that this transmission scheme is of the band pass
variety, we can infer that if we set the bandwidth equal must be chosen in such a way to
prevent the sinc pulses from overlapping. Specifically, the bandwidth must be 1/2Tb where Tb
is the reciprocal of bandwidth.
Phase Shift-Keying
Phase shift-keying (PSK) is a digital band-pass communication method that represents
bits through the phase of a cosine wave. The modulated wave s(t) is sqrt(2E/ Tb)*cos(2*pi*f*t
+phase) where E is the transmitted energy per bit. In general, the PSK is generated by
converting the stream to a constant amplitude using the non-return-to-zero encoder. This
device only allows transitions of the input bits to be between a positive or negative constant.
The converting stream is then modulated with the cosine wave sqrt(2E/ Tb)*cos(2*pi*f*t
+phase) to produce the PSK signal. A General illustration of a PSK modulator is shown below.
This modulator is the simplest variety of the PSK’s—Binary Phase Shift-Keying(BPSK). The
system uses the phases 0 and 180 degrees to represent 0 and 1. The bandwidth minimum
required for this type of transmission is 2/Tb.
QPSK System Simulation
Page 11
Figure 8
Quadrature Phase Shift-Keying (QPSK) is a modulation scheme where 4 phases are used
in the transmission of a 2 bit word (00,01,10,11). This signal is represented by the function
sqrt(2E/ Tb)*cos(2*pi*f*t +phase) where the phase is equal to 45, 135, 225, or 270. In terms of
generation, QPSK is essentially 2 BPSK’s put together. Shown below, the 2 BPSK’s differ by its
amplitude and by the phase 90 degree phase shifted oscillator.
Figure 9
QPSK System Simulation
Page 12
In theory, the QPSK is said to be more efficient than BSK in terms of utilization of the channel.
Specifically, 1 more bit is sampled at the output every sampling instant when u compare it to
BPSK. Hence, the bandwidth of this QPSK is one half of that of the BPSK transmitter.
QPSK Detection
Detection of the QPSK is done so by coherent detection. In this scheme a signal is
product modulated with a local oscillator and then low-pass filtered. From there (shown
below), the
Figure 10
Filtered signals In the In and Q channels are compared to some threshold at a rate equal to the
sampling rate.
Detection of QPSK in Noise
Similar to the above receiver, this receiver takes in the signal multiplies it with a local
oscillilator and filters out the high frequency terms (integrate and dump).
QPSK System Simulation
Page 13
Figure 11
The integrate and dump step takes the product of the I or Q and the local oscillator computer
the integral during the sample period. After it computes the integral, it sends the value to the
threshold comparison and dump(resets) the old value for the next sample period.
4.0 Project Objectives
The team has decided to work with QPSK system and implement a transmitter, channel
and receiver. The team is composed of 4 members of Florida International University Electrical
Engineering graduate program. Each team member will contribute their expertise and the
knowledge attained during their studies and work experience. As a team, we have been asked
to submit a report detailing objectives, theory, design methods, conclusion and references
utilized during the team’s research. This project will enhance each member’s ability to design
the elements of a true communications system. Software implementation will simulate how a
communications system must perform.
QPSK System Simulation
Page 14
5.0 Proposed Methods
In this section, we will implement a QPSK transmitter, channel, and receiver. The proposed
QPSK transmitter can be seen below in Figure 12. Using Matlab’s Simulink environment, we
have designed a digital algorithm which is discrete in time and amplitude. The prerequisites for
this transmitter are such that the user owns an analog to digital converter. For this simulation,
we assume the ADC is an 8-bit ADC.
Figure 12
Information signal such as voice or other communication information, one can use an
analog to digital converter and convert each instance of time into an integer representation
based on the ADC possessed by the user. Once we have this information, we use a cast type
transformer to transform the integer data type and conformity to an unsigned 8-bit integer. At
QPSK Transmitter
EEL5501 - QPSK Project
Hassan Chaudhary
Napalys Juodzevicius
Jovan Robinson
David Sanchez
TX RF Out
bit-2
u(2)
bit-1
u(1)
Unbuffer 8-Bits
Rate Transition1
RT
Rate Transition0
RT
DATA
Ts = 1kHz
@1 Byte (8-bits)Tb=8kHz
Quadrature
Phase
Shift
In -90'
Non-Return
to Zero
Line Encoder
u*2-1
In-Phase
Local Osscilator
Fc = 24kHz
DSP
In-Phase
Frame to Sample
To
Sample
DaTC
uint8
Byte to
Bit-stream
Integer to Bit
Converter
Buffer 2-bits
[2x1]
[2x1]
[2x1]
8
[2x1]
QPSK System Simulation
Page 15
that moment in time, the user now possesses all the information required for RT PSK
transmitter to work. We first start off by taking this integer and converting it into a bit stream.
In an 8-bit integer, we of course will have eight bits to the byte and must initilsile the process
for this to happen. We serialize the byte frame of into singular bits. Once we have serial bits, we
need to transform them into a physical quantity such as voltage. For this to happen, we use a
non-returned to the zero line encoder. At this moment in time we will have the zeros and ones
transformed into 1 V and -1 V respectively. In order to accomplish this in a Matlab simulator
environment we presumed a random data set. The first set of block shows the transformation
all the way through non-returned to zero line encoder. With this information we go ahead and
perform a diabetic transformation to the serial input. We take two serial samples and convert
them into one symbol composed of two bits. We take the first bit, and perform an in-phase
BASK. The in-phase component simply takes the bit signal of 1 V or -1 V and multiplies this by a
local oscillator. In our simulation we used 24 kHz cosine for the QPSK carrier. We derive the
quadrature local oscillator, by base shifting the cosine wave by 90°. Similarly we multiply the
quadrature local oscillator by the secondary input bit which may be -1 V or 1 V. At this point we
subtract the quadrature component from the in-phase component. The output of such a
subtraction provides us with the QPSK signal.
QPSK System Simulation
Page 16
Figure 13
Timing is key to the simulation. Not only is bit-time important, the sampling and rate
transition timing is crucial as well. Figure 14 shows the raw bitstream alongside the buffered
and unbuffered decomposed symbol: bit0 & bit1. Each of these bits has its own QPSK which can
be seen the third plot in Figure 14.
Spectral analysis of the serial bitstream (which is the bit stream before the serial to
parallel conversion) confirms the main frequency component of the bitstream is in 8 kHz pulse
per bit. Harmonics and aliases in the spectrum can be seen from DC all the way through to
infinity. Clear separation of 8 kHz per side lobe can be seen in Figure 14.
QPSK System Simulation
Page 17
Figure 14
Figure 15
0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08
-70
-60
-50
-40
-30
-20
-10
0
10
20
Input bitstream spectrum
Tb = 8kHz
Frequency (MHz)
Ma
gn
itu
de
-sq
ua
red
,dB
m
0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18 0.2
-70
-60
-50
-40
-30
-20
-10
0
10
20
QPSK Output (Spectrum)
Frequency (MHz)
Ma
gn
itu
de
-sq
ua
red
,dB
m
QPSK System Simulation
Page 18
Figure 16
Taking that serial bit stream, we performed the QPSK modulation as described in Figure
13. The output spectral power density can be seen in Figure 15. Clearly the 24 kHz carrier is
visible as well as the infinite side lobes. The side lobe bandwidths are approximately 4 kHz each,
and the primary carrier lobe has a bandwidth of 1/Tb. The following figure, Figure 16, closes in
on the DC through 50 kHz. The spectrum observed is a textbook definition of QPSK.
0 0.005 0.01 0.015 0.02 0.025 0.03 0.035 0.04 0.045
-70
-60
-50
-40
-30
-20
-10
0
10
20Fc = 24kHz
QPSK Ouput (Spectrum)
Main Lobe Bandwidth is 8kHz
Frequency (MHz)
Ma
gn
itu
de
-sq
ua
red
,dB
m
QPSK System Simulation
Page 19
Figure 17
Next we implement the QPSK receiver. During the design of this DSP algorithm, we
realized how important it is to have a coherent receiver. If the receiver local oscillator has a
phase shift, phi, the received signal will multiplied by the cos(phi). Similar to the transmitter
receiver takes the incoming modulated QPSK RF and multiplies it by an in phase local oscillator
as well as a quadrature local oscillator. Due to the mathematics of this multiplication, the
cosine at the carrier frequencies will diminish. In the quadrature component, the sine waves,
will also diminish leading a double frequency component. By implementing a one cycle buffer
of the double frequency and integrating or digitally summing those samples we reduces the
double frequency to exactly 0. Once this happens we take each bit which is coming in parallel,
and concatenate them to form a serial vector. This vector will then be unbuffered to conformed
to a serial bitstream. The receiver then goes on to take eight bits and converts them into
integers. In this receiver, we assume that the receiver is exactly coherent and uses some phase
EEL5501 - QPSK Project
Hassan Chaudhary
Napalys Juodzevicius
Jovan Robinson
David Sanchez
QPSK Reciever
orignal code
1
inPhase
lo
Fc = 24kHz
DSP
buffer 1 cycle.
buffer 1 cycle
Unbuffer
Sum of
Elements2
Sum of
Elements1
QuadraturePhase
Shift
In -90'
Matrix
Concatenate
2
Math
Function
uT
In-Phase
Integrate and dump
Gain
-1
Frame to Samples1
To
Sample
Frame to Samples
To
Sample
8-Bit to Integer
Bit to Integer
Converter
QPSK in
1
[168x1]
[168x1]
[1x2]
[1x2]
[2x1]
QPSK System Simulation
Page 20
locked loop technique or other technique to remain coherent. Figure 17 shows the top-level
implementation of this algorithm.
6.0 Results
For a more detailed analysis, we look to Figure 18. Figure 18 displays three-time scopes:
scope one represents the parallel bits as well as the QPSK modulated RF output from the
transmitter and is received in the receiver. As soon as the RF QPSK is received into the receiver,
the receiver multiplies by the in phase and quadrature local oscillator respectively. The middle
scope shows the original bits with a double frequencies superimposed on them due to the in-
phase and quadrature multiplication. Surprisingly after an integrator (which acts as a low pass
filter at every double frequency time period), the third scope shows the original signals quite
intact. There is however a byproduct of the integration and dump component. There is an
apparent phase shift as seen in the third scope with respect to the first scope. This represents
the information coming into the receiver inducing a timeshift upon exit of the information.
QPSK System Simulation
Page 21
Figure 18
QPSK System Simulation
Page 22
Figure 19
Spectral analysis of the signal after the QPSK is multiplied by the local oscillator on the
receiver can be seen in Figure 19. On the left you can see bits zero and bit one. On the right you
can see the spectrum after the integrate and dump process. We can clearly see a double
frequency component's spike at the spectrum before the integrated dump filter. After only
applying integration in digital domain, we can see a spectrum no longer contains the 48 kHz
double frequency component. We are left with what seems to be an allianced pulse wave. Each
of the two bits clearly has a bit frequency of 4 kHz. Once combined, they will form a timing of
1/8kHz.
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2
-80
-60
-40
-20
0
20
Frame: 17
Bit-0 Power Spectral Density
Bit-1 Power Spectral Density
Frequency (MHz)
Ma
gn
itu
de
-sq
ua
red
,dB
m
0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08
-80
-60
-40
-20
0
20
Double Frequecy due to cos^2Carrier frequency no longer present
Double Frequecy due to cos^2Carrier frequency no longer present
Frequency (MHz)
0 2 4 6 8 10 12
-10
0
10
20
30
40
50
60
Bit-0: Post Integrate and Dump PSD
Bit-1: Post Integrate and Dump PSD
Frequency (kHz)
Ma
gn
itu
de
-sq
ua
red
,dB
m
0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 2
-80
-60
-40
-20
0
20
Frame: 17 Frequency (MHz)
Ma
gn
itu
de
-sq
ua
red
,dB
m
0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08
-80
-60
-40
-20
0
20
Frame: 17 Frequency (MHz)
Magnitude-s
quare
d,
dB
m
0 2 4 6 8 10 12
-10
0
10
20
30
40
50
60
Frame: 7 Frequency (kHz)
Ma
gn
itu
de
-sq
ua
red
,dB
mDouble Frequecy due to sin^2
Carrier frequency no longer present
QPSK System Simulation
Page 23
We next analyzed the QPSK from a system-level perspective. Until now we have
neglected the issues with noise and assume a perfect transmitter, receiver and channel. In the
following section, we will take into account the effects of an imperfect channel.
Figure 20
The top level diagram of the system can be seen in Figure 20. In a QPSK system, a
symbol is received to the transmitter is then forwarded to a transmit filter. On the receiver, side
a receive filter is also implemented to try and match the original signal and reduce noise and
temporal distortions.
Due to a noisy channel, these filters are necessary to maximize all gains and minimize
errors. The perfect channel would of course be the Nyquist channel, however in this scenario
we take into account a channel with white noise. Such a channel has a constant spectral
density. In our simulations we forced the energy per bit her noise spectral density to be 12 dB,
System Level QPSK
EEL5501 - QPSK Project
Hassan Chaudhary
Napalys Juodzevicius
Jovan Robinson
David Sanchez
Noisy ChannelForced Eb/N0 = 12dB
Random Symbol
M=4
Random
Integer
QPSK
Transmitter
QPSK
QPSK
Reciver
QPSK
Normalized Raised Cosine
TX Filter
Roll-Off Factor: 0.3
Normal
Normalized Raised Cosine
RX Filter
Roll-Off Factor: 0.3
NormalSymbol
Decoder
Constant (White) Spectral Density
w/ Gaussian Amplitude
AWGN
QPSK System Simulation
Page 24
this way we can scrutinize a poorly received signal with a lot of added white Gaussian noise and
see what the effects are.
The specific filter used for our simulations was a raised cosine transmit and receive
filter. Essentially this is a low pass filter with finite impulse response using a rolloff factor of 0.3.
As opposed to an infinite impulse response filter (IIR) such as Chevychev or Butterworth, a finite
impulse response (FIR Filter), is linear in phase. The said filter’s magnitude response and phase
response can be seen on the left in Figure 21. This is the normalize response of the filter. The
impulse response in the time domain can also be seen on the right.
Figure 21
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9
-60
-50
-40
-30
-20
-10
0
10
20
Normalized Frequency ( rad/sample)
Magnitude (
dB
)
Magnitude (dB) and Phase Responses
Raised-Cosine Transmit and Recive Filters
Roll-Off Factor: 0.3
-15.8005
-13.7924
-11.7842
-9.7761
-7.768
-5.7599
-3.7517
-1.7436
0.2645
Phase (
radia
ns)
0 10 20 30 40 50 60
-0.2
0
0.2
0.4
0.6
0.8
1
Samples
Am
plitu
de
Impulse Response
QPSK System Simulation
Page 25
Figure 22
Most QPSK systems either use binary coding or grey coding, we used binary coding in
our system due to its simplicity. Figure 22 shows the eye diagrams as well as the constellation
diagrams. After the transmitter receives a specific symbol, it proceeds to output QPSK through
the raised cosine transmit filter. On the left-hand side, both the in-phase/quadrature and polar
representations at the device output of the transmitter are analyzed. Due to a 12dB Eb/No, we
see very noisy eye diagram after the transmitter has passed the modulated signal. Here is
where the receiver raised cosine filter shines the greatest. As a constellation diagrams show,
the trivial scenario with a voltage of -1 V and 1 V portrays an extremely noisy cloud at each of
QPSK System Simulation
Page 26
the four symbols. After the receive filter we see a very tight noise cloud with an extreme
separation per symbol.
Finally, the received symbol is seen after the QPSK demodulator has processed the
received signal. Figure 23 clearly portrays the accuracy and timing of the original signal. There
seems to be a huge transient at the output of the QPSK demodulator possibly due to digital and
filter errors. However overall, the system seems to be performing well with a slight phase shift.
Figure 23
QPSK System Simulation
Page 27
7.0 Conclusion
By doing this project at the digital and sampled level, two important factors clearly rose above
all others.
Firstly, we have now learned firsthand how important it is to have matching filters; especially in
phase modulation techniques like QPSK. One cannot use conventional IIR filters, and must use linear
phase FIR filters such as the ones used in our simulation. The IIR filters may not allow sharp
discontinuities in the carriers phase in QPSK signal. They will induce harmonics and output non-linear
phase shifts making them very difficult to correct via the integrate and dump process. With FIR, the
QPSK demodulator can easily recover the original signal.
The second important factor learned was the importance of coherency. This concept was for us
as a team in class to us, however, we underrated it during class lectures. Without a coherent and stable
local oscillator at the receiver side, there really cannot be any communications. The development of
such a method to lock onto the incoming carrier was underappreciated prior to doing this project. We
now hold this concept with much more esteem. This point cannot be overstated enough.
In conclusion, the team was able to successfully simulate a complete QPSK system with visible
results. This project experience was helpful to all the team members; it provided huge insight of how
communication systems mechanism works. The team clearly understood how each component is
integrated and how each team member provided their specific knowledge for the benefit of the project.
In addition, no major setbacks occurred within the team during the design process. Since the assigned
date everybody had a clear idea of their specific responsibilities.
QPSK System Simulation
Page 28
8.0 References
An introduction to digital and analog communications . 2nd ed. S.l.: Wiley, 2006. Print.
Breach, Tony. "40 G and 100G Overview." NORDUnet. N.p., 20 Mar. 2009. Web. 10 Apr. 2011.
<https://wiki.ndgf.org/download/attachments/10355162/40G+and+100G+Overview+-
+Report.pdf>.
"DVB - Digital Video Broadcasting - Home." DVB - Digital Video Broadcasting - Home. N.p.,
n.d. Web. 10 Apr. 2011. <http://www.dvb.org>.
"Jiexun Electronics." Chengdu Jie Xun Electronics. N.p., n.d. Web. 11 Apr. 2011. <www.jie-
xun.com/en>.
" Nokia USA - world leader in cell phone industry ." Nokia USA - world leader in cell phone
industry . N.p., n.d. Web. 11 Apr. 2011. <http://www.nokiausa.com>.
"Semiconductor Technologies for Optical Interconnection." GigOptix. N.p., n.d. Web. 11 Apr.
2011. <www.gigoptix.com/component/k2/item/download/8.html>.