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ISSN 2394-3777 (Print)
ISSN 2394-3785 (Online)
Available online at www.ijartet.com
International Journal of Advanced Research Trends in Engineering and Technology (IJARTET)
Vol. II, Special Issue XXIII, March 2015 in association with
FRANCIS XAVIER ENGINEERING COLLEGE, TIRUNELVELI
DEPARTMENT OF ELECTRONICS AND COMMUNICATION ENGINEERING
INTERNATIONAL CONFERENCE ON RECENT ADVANCES IN COMMUNICATION SYSTEMS AND
TECHNOLOGIES
(ICRACST’15)
TH
25 MARCH 2015
Timing and Frequency Synchronized MIMO-OFDM System using
Phase Locked Loop with Low Fault Rate
1
M.Anita
PG Scholar
Department of Applied Electronics
St.Joseph’s College of Engineering
Chennai-600119, India
Abstract---Great attention has been received by various
wireless communication techniques and is widely used in
wireless communication systems for its high spectrum
efficiency and robustness to narrowband interference and
multipath fading. The Wireless communication technique
used in this project is MIMO-OFDM. MIMO-OFDM can
provide enormous data rates which is tolerable to radio
channel impairments. But in OFDM system, there may
occur a mismatch between transmitted and received
signal. To overcome the mismatch and for timing and
frequency synchronization between transmitted and
received signal, we use a PLL with low fault rate. This
project mainly investigates the effect of phase noise in the
system and the system performance is evaluated by
calculating the signal to noise ratio due to phase noise, in
terms of BERsimulations with and without PLL for
different channel conditions.
Keywords—PLL, MIMO-OFDM, Synchronization, Phase noise
I.INTRODUCTION
2
P.Thenmozhi
AssistantProfessor
Department of ECE,
St.Joseph’s College of Engineering,
Chennai-600119, India
to each other. Thus, the cross-talk between the sub-channels
is eliminated and inter-carrier gaurd bands are not required.
The orthogonality also allows high spectral efficiency, with a
total symbol rate near the nyquist rate for the equivalent
baseband signal. Almost the whole available frequency band
can be utilized. A convolutional channel-coder encodes the
bit stream of each user. The encoded bits are interleaved by
the outer interleaver and passed to the symbol mapped.With
respect to different modulation alphabets (e.g., PSK or
QAM), the bits are mapped to complex-valued data
symbols.We use the Additive White Gaussian Noise
(AWGN) channel for the Wireless Network.For system level
simulations, the simulation of all interfering signal paths is
complex. Thus, a simplification of the interference model is
done by the Gaussian approximation (GA) which assumes the
entire interference as Gaussian noise. Here by, the noise
variance has to be scaled appropriately. Inorder to achieve
timing and frequency synchronization between transmitted
and received signal, PLL is used in this project. Signal is
transmitted with the help of MIMO-OFDM technique and its
synchronization error is calculated without using PLL and
with using PLL and the results are compared.
II. RELATED WORKS
Phase Locked Loops are used in almost every
communication system. Some of its uses are recovering clock
from digital data signals, performing frequency modulation,
phase modulation and demodulation, recovering carrier from
satellite transmission signals and as a frequency synthesizer.
There are many designs in communication that require
frequency synthesizer to generate a range of frequencies; such
as cordless telephones, mobile radios and other wireless
products. The accuracy of the required frequencies is very
important in these designs as the performance is based on this
parameter. OFDMis a frequency division multiplexing sheme
which converts high data rate signal into low data rate signal
and transmits it through parallel narrowband channels. In
OFDM transceiver, the sub-carrier frequencies are orthogonal
Inproject [1] fractional N PLL based synthesizer is
equipped with a VCO, which is realized with CMOS
transistors in a current reuse technique and a DLL. And also
shows a good performance in terms of phase noise and can
be easily realized in a standard CMOS technology.In work
[2] GNSS receiver is considered in which the PLL’s phase
performance is degraded due to both thermal and
oscillatorphase noise. To overcome this noise rejection and
tracking error present in GNSS Receiver, PLL is designed
using optimal and Weiner filter.
The paper [3]has used MIMO-OFDM technique which
can achieve reliable high data rate transmission over
56
All Rights Reserved © 2015 IJARTET
ISSN 2394-3777 (Print)
ISSN 2394-3785 (Online)
Available online at www.ijartet.com
International Journal of Advanced Research Trends in Engineering and Technology (IJARTET)
Vol. II, Special Issue XXIII, March 2015 in association with
FRANCIS XAVIER ENGINEERING COLLEGE, TIRUNELVELI
DEPARTMENT OF ELECTRONICS AND COMMUNICATION ENGINEERING
INTERNATIONAL CONFERENCE ON RECENT ADVANCES IN COMMUNICATION SYSTEMS AND
TECHNOLOGIES
(ICRACST’15)
TH
25 MARCH 2015
Fig. 3.1:Proposed
broadband wireless channels. Channel state information
for System Block Diagram
both SISO and MIMO systems based on pilot aided
A.Input Data
arrangement is also investigated in this paper.In [4] phase
The input Data to the OFDM is given in terms of
noise and frequency accuracy of the frequency synthesizer
high bit stream with 9.6 KHz baud rate. The high bit streams
are analysed. The channel efficiency, the frequency
are converted to low bit stream by applying data segmentation
switching performance and the output spectral purity are
technique.
investigated at 2.5GHZ.Project [5]deals with the phase noise
performance of the PLL CMOS technology which is used to
B.Serial to Parallel Conversion
analyze the system.
The input serial data stream is formatted into the
In project [6] avoids significant amplification of the
word size required for transmission, e.g. 2 bits/word for
reference clock jitter, and loop gain is minimized. Jitter
QAM, and shifted into a parallel format. The data is then
transfer attenuation techniques through loop filtering and
transmitted in parallel by assigning each word to one carrier
phase filtering have also been discussed.
in the transmission.
In the work [7]conventional RF Frequency synthesizer
architecture based on a VCO and phase/ frequency detector
and charge pump combination, has been replaced with a
digitally controlled oscillator.The ADPLL phase noise
performance is also significantly improved. In the paper
[8]PLLs are used for synchronization technique in grid
connection applications and Moving Average filter Based
PLL is used to precisely and fastly estimate the phase and
frequency when the grid voltage is unbalanced and/ or
distorted.
III. PROPOSED SYSTEM
Block diagram of MIMO-OFDM system using PLL is given
as below.
Input
QAM
Coding
Interleaving
Modulation
IFFT
P/S
FFT
P/S
O
OO
S/P
Pilot Insertion
Cyclic Extension
S/P
Channel
Remove cyclic extension
Removal of Pilot data
QAM
Demodulation
Output
PLL
Decoder
Deinterleaving
C.Modulation of Data
The data to be transmitted on each carrier is then
differentially encoded with previous symbols, then mapped
into a Phase Shift Keying (PSK) format. Since differential
encoding requires an initial phase reference, an extra symbol
is added at the start for this purpose. The data on each
symbol is then mapped to a phase angle based on the
modulation method. For example, for QAM the phase angles
used are 0, 90, 180, and 270 degrees. The use of phase shift
keying produces a constant amplitude signal and is chosen
for its simplicity and to reduce problems with amplitude
fluctuations due to fading.
D.Inverse Fourier Transform
After the required spectrum is worked out, an
inverse Fourier transform is used to find the corresponding
time waveform. The guard period is then added to the start of
each symbol. OFDM uses the available spectrum efficiently
by spacing the channels much closer together. This is
achieved by making all the carriers orthogonal to one
another, preventing interference between the carriers. To
generate OFDM successfully the relationship between all
carriers must be carefully to maintain the orthogonality of the
carriers. For that, after choosing the spectrum required, we
have to convert it back to its time domain signal using an
Inverse Fourier Transform.
In most applications, an Inverse Fast Fourier
Transform is used, it performs the transformation very
efficiently, and provides a simple way of ensuring the carrier
signals produced are orthogonal.
E.Guard Period
One way to avoid the inter symbol interference is to
set a small gap equal to the duration of delay spread between
57
All Rights Reserved © 2015 IJARTET
ISSN 2394-3777 (Print)
ISSN 2394-3785 (Online)
Available online at www.ijartet.com
International Journal of Advanced Research Trends in Engineering and Technology (IJARTET)
Vol. II, Special Issue XXIII, March 2015 in association with
FRANCIS XAVIER ENGINEERING COLLEGE, TIRUNELVELI
DEPARTMENT OF ELECTRONICS AND COMMUNICATION ENGINEERING
INTERNATIONAL CONFERENCE ON RECENT ADVANCES IN COMMUNICATION SYSTEMS AND
TECHNOLOGIES
(ICRACST’15)
TH
25 MARCH 2015
the symbols. So, each symbol does not affect the next one.
The guard period used is made up of two sections. Half of
the guard period is a zero amplitude transmission. The other
half of the guard period is a cyclic extension of the symbol to
be transmitted. This is to allow for symbol timing to be easily
recovered by envelope detection.
STEP -1: A high speed data with baud rate of 9600 Hz is
given as input.
I n p u t Da t a
1
0.9
0.8
AWGN is often used as a channel model in which the only
impairment to communicate is a linear addition of wideband
or white noise with a constant spectral density (expressed as
watts per hertz of bandwidth) and a Gaussian distribution of
amplitude. The model does not account for fading, frequency
selectivity, interference, nonlinearity or dispersion. However,
it produces simple and tractable mathematical models which
are useful for gaining insight into the underlying behaviour
of a system before other phenomena are considered.
G.Receiver
The receiver basically does the reverse operation to
the transmitter. The guard period is removed. The FFT of
each symbol is then taken to find the original transmitted
spectrum. The phase angle of each transmission carrier is
then evaluated and converted back to the data word by
demodulating the received phase. The data words are then
combined back to the same word size as the original data.
0.6
0.5
0.4
0.3
0.2
0.1
0
0
2000
4000
6000
Time in ms
8000
10000
Fig 5.1 Input data
STEP – 2: 9600 bits are separated into hundred 96 low bit
data stream.
S e g me n t e d D a t a
1
0.9
0.8
0.7
Amplitude in Volt
F.Channel noise (AWGN)
Amplitude in Volt
0.7
0.6
0.5
0.4
0.3
0.2
IV.SOFTWARE AND ITS DESCRIPTION
MATLAB (matrix laboratory) is a multi-paradigm numerical
computing environment and fourth-generation programming
language developed by MathWorks, MATLAB allows matrix
manipulations, plotting of functions and data, implementation
of algorithms, creation of user interfaces, and interfacing
with programs written in other languages, including C, C++,
Java, Fortran and Python. Although MATLAB is intended
primarily for numerical computing, an optional toolbox uses
the MuPAD symbolic engine, allowing access to symbolic
computing capabilities. An additional package, Simulink,
adds graphical multi-domain simulation and Model-Based
Design for dynamic and embedded systems. MIMO-OFDM
system is simulated with the help of MATLAB software.
0.1
0
0
20
40
60
Time in ms
80
100
Fig 5.2 Segmented data
STEP – 3: The low bit data’s are encrypted with the help of
convolutional encoder for security purpose.
V.RESULTS AND DISCUSSIONS
This section will suggest the output and its description.
58
All Rights Reserved © 2015 IJARTET
ISSN 2394-3777 (Print)
ISSN 2394-3785 (Online)
Available online at www.ijartet.com
International Journal of Advanced Research Trends in Engineering and Technology (IJARTET)
Vol. II, Special Issue XXIII, March 2015 in association with
FRANCIS XAVIER ENGINEERING COLLEGE, TIRUNELVELI
DEPARTMENT OF ELECTRONICS AND COMMUNICATION ENGINEERING
INTERNATIONAL CONFERENCE ON RECENT ADVANCES IN COMMUNICATION SYSTEMS AND
TECHNOLOGIES
(ICRACST’15)
TH
25 MARCH 2015
En c o d e d Da t a
1
QA M Mo d u l a t e d D a t a
4.5
0.9
4
0.8
3.5
Amplitude in volt
Amplitude in volt
0.7
0.6
0.5
0.4
3
2.5
2
0.3
1.5
0.2
0.1
1
0
0
0
50
100
Time in ms
150
200
10
20
30
Time in ms
40
50
Fig 5.5
QAM modulated signal
Fig 5.3 Encoded data
STEP – 4: The data sequence is converted into matrix format
with the help of matrix interleaver.
STEP – 6: In the receiver side, error will occur in first few
bits, so cyclic extension is used to convert 64bits into 80 bits
Cy c l i c E xt e n d e d Da t a
0.8
I FF T Da t a S u b c a r r i e r S i gn al
1.4
0.6
1.2
0.4
Amplitude in volt
Amplitude in volt
1
0.8
0.6
0.4
0
-0.2
0.2
0
0
0.2
-0.4
10
20
30
40
Time in ms
50
60
70
Fig 5.4
Sub carrier signal
-0.6
0
10
20
30
40
50
Time in ms
60
70
80
Fig
5.6 Cyclic extended data
STEP – 5: The signal is modulated with the help of QAM
modulator.
STEP – 7: Output without PLL
59
All Rights Reserved © 2015 IJARTET
ISSN 2394-3777 (Print)
ISSN 2394-3785 (Online)
Available online at www.ijartet.com
International Journal of Advanced Research Trends in Engineering and Technology (IJARTET)
Vol. II, Special Issue XXIII, March 2015 in association with
FRANCIS XAVIER ENGINEERING COLLEGE, TIRUNELVELI
DEPARTMENT OF ELECTRONICS AND COMMUNICATION ENGINEERING
INTERNATIONAL CONFERENCE ON RECENT ADVANCES IN COMMUNICATION SYSTEMS AND
TECHNOLOGIES
(ICRACST’15)
TH
25 MARCH 2015
OF D M S i g n a l t h r o u g h t h e c h a n n e l
1.4
C h a n n e l E s t i ma t i o n
0
10
1.2
-1
10
0.8
Fault Rate
Amplitude in volt
1
0.6
-2
0.4
10
0.2
0
0
10
20
30
40
50
Time in ms
60
70
80
-3
10
0
5
10
Fig 5.7 OFDM signal
20
25
Fig
5.9 Output with PLL
STEP – 8: Channel estimation without PLL
STEP – 10: Comparison between OFDM without PLL and
OFDM with PLL
C h a n n e l E s t i ma t i o n
2
15
SNR in (dB)
10
C h a n n e l E s t i ma t i o n
2
10
OFDMwithout PLL
OFDMwith PLL
1
10
1
Fault Rate
10
Fault Rate
0
0
10
10
-1
10
-2
10
-1
10
1
2
3
4
5
SNR in (dB)
6
Fig 5.8 Output without PLL
7
8
-3
10
0
5
10
15
SNR in (dB)
20
25
Fig 5.10 Comparison between output without PLL and with PLL
STEP – 9: Channel estimation with PLL
6.CONCLUSION
In MIMO-OFDM systems the interference due to
phase noise can be separated into the common phase error
(CPE) and the random or ICI term similar to SISO OFDM
systems. The CPE can be estimated using pilots and
corrected. In a power constrained MIMO system the CPE
decreases as more antennas are added. An important system
level tradeoff is the issue of correlated v/s uncorrelated phase
noise. Presence of correlated phase noise can be corrected to
a larger extent than CPE when the phase noise is
uncorrelated at the various transmit/receive RF chains. We
also showed that in the case of uncorrelated phase noise with
pilots dedicated to each data stream performs better than a
joint estimate across all the data streams.
60
All Rights Reserved © 2015 IJARTET
ISSN 2394-3777 (Print)
ISSN 2394-3785 (Online)
Available online at www.ijartet.com
International Journal of Advanced Research Trends in Engineering and Technology (IJARTET)
Vol. II, Special Issue XXIII, March 2015 in association with
FRANCIS XAVIER ENGINEERING COLLEGE, TIRUNELVELI
DEPARTMENT OF ELECTRONICS AND COMMUNICATION ENGINEERING
INTERNATIONAL CONFERENCE ON RECENT ADVANCES IN COMMUNICATION SYSTEMS AND
TECHNOLOGIES
(ICRACST’15)
TH
25 MARCH 2015
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[1] Herman Jalli Ng and Alexander Fischer.(2013) ‘A DLL- Supported,
low phase noise fractional-N PLL with a wideband VCO and a highly
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[2] James T. Curran and Gerard Lachapelle. (2012) ‘Digital GNSS PLL
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Murphy, IEEE transactions on aerospace and electronic systems Vol.48,
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[3] Kala Praveen Bagadi (2010) ‘MIMO – OFDM channel estimation using
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[4] Kim Fung Tsang.(2006) ‘A Low Voltage Fast Switching Frequency
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[6] M-J Edward Lee and William J. Dally.(2003) ‘Jitter Transfer
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