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B
E
Abstract —
multipath fadproblems in p
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due to differ
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of Additive W
are explored
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approaches h
performance.
Key Words
The radio
multipath fad
interference iinterference f
diversity algocan be para
characterizedamplitudes sh
of terminals
large number (OFDM) sym
estimating an
the wireless
attenuation, aof OFDM is
function of c
amplitude anfrom the av
removes the
subsequent sy
OFDM is a
can accommo based wirele
integral part
MIMO-OFDdivides the av
but orthogo
R Per
viron
The wireless c
ing characterioper reception
e type of fadihe channel esti
nt types of i
in equipmendigital comm
hite Gaussion
and their p
ast square Er
used to pror Inter-Symbol
variable in m
ined Equal Garsity techniqu
hniques is ad Inter-symbo
ave resulted
OFDM, Equ
I. INTR
hannels in m
ing channels,
the receivedrom the signa
rithm can beeterized as
by a delayow fast tempo
hile the del
of orthogonal bols. A possib
d tracking the
channel cause
d phase shiftto mitigate th
annel estimati
phase shiftailable pilot
effect of the
mbol demodul
special case o
date high datas systems. S
of OFDM s
systems proailable spectr
al narrowba
orma
ent Us
Deepmal
mmunication
stics and the. Therefore th
g is most impmation has bec
nterference pr
ts. In thisnications syste
oise and Mult
erformance is
ror equalizer
vide the optierror. As the
ultipath fadin
in combining as, and find t
ble to fightl interference
in big impr
lizer, Diversity
DUCTION
obile radio sy
which are ca
signal. To rel, much kind
sed. The wire
a combinatio
and compleal variations
ys are almos
frequency divle approach i
delay [1].it i
s an arbitrar
in the receiveffect of ti
on is to form
caused by thinformation.
wireless ch
ation.
multicarrier t
rate requiremince channel
ystems. As
mises higher m into a num
d sub chan
o ri ht © 2
ce Imp
ng Co
TSingh Pari
is impaired by
efore createsknowledge o
rtant in desigome very vast
esent in wire
thesis, estimams in the pres
ipath environ
investigated.
and Zero for
um solutionBER perform
channel there
nd Maximal Rat Maximal R
with Co-Charoblem. The a
vement in
, QAM.
stems are usu
sing intersy
ove intersyof equalizers
less radio chaof paths,
amplitude.ue to the mob
t constant ov
sion multiplethat of expli
well known
time dispers
d signal. Thee dispersion.
an estimate o
e wireless caThe equaliza
nnel and all
ransmission a
ent of multimestimation is
combinatio
ata rates. OFer of overlap
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Fig. 2.
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l Journal of Ele
ll ri ht reserv
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Equali
esProf. R
ts a frequency
e channel [2].
ORTHOGO
M is a mult
rm/ Fast Fo
iers. OFDM inications sys
ity with high
gard to multdth is divide
e 2000-8000
n2 and data ismethod is so
to multipath t
M is a combi
ation means a
arrier phase,lexing means
dependent da
In OFDM
dent channeexed to create
Block diagra
equence and
tronics Commu
V
ed
ultipa
zer an
vi Mohan
selective cha
II. OFD
AL FREQU
ULTIPLEX
icarrier syste
rier Transfo
s becomingems due to i
andwidth effi
ipath fadingd into very
hz for digi
transmitted i popular for ne
ransmission.
Fig. 1.
ation of mod
mapping of th
requency or aa method of s
ta channels. O
the signal it
s, modulatedthe OFDM ca
of an OFD
guard bit ins
ication and Co
olume 3, Issue 2,
h Fadi
Diver
nel into a no
ENCY DIVIS
NG)
uses Discr
m and
idely applieds high rate tr
ciency and its
nd delay [4].any narrow
al TV and
parallel on tw broadband
ulation and m
e information
mplitude or charing a band
FDM is a spe
self is first
by data anrrier.
system using
rtion FFT is
161
puter Engineeri
ISSN 2249 –071
g
ity
frequency
ION
te Fourier
spectra for
in wirelessansmission
robustness
Available bands for
48 hz for
ese bands.ystems are
ltiplexing.
on changes
mbination.width with
cial case of
split into
then re-
FFT, pilot
ritten as
g
X
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162
International Journal of Electronics Communication and Computer Engineering
Volume 3, Issue 2, ISSN 2249 –071X
Copyright © 2012 IJECCE, All right reserved
∑ / , 0 1
…. (1) W N be the complex-valued phase factor
/
Thus, X (k) becomes
∑
, 0 1
…. (2)
Similarly IFFT is written as,
∑
, 0 1
.… (3)
III. QUADRATURE AMPLITUDE MODULATION
(QAM)
QAM is more efficient in terms of bandwidth than either
FSK or QPSK, but it is also more susceptible to noise. Thedisadvantage of DSB signals which is occupy twice the
bandwidth required for the baseband can be overcome by
transmitting two DSB signals using carriers of the samefrequency but in phase quadrature [5].
In this figure, the boxes labeled – π/2 are phase shifters,which delay the phase of an input sinusoid by – π/2 rad. If
the two baseband signals to be transmitted are m1 (t) and m2
(t), the corresponding QAM signal φQAM (t), the sum of the
two DSB-modulated signals is
….. (4)
Both modulated signals occupy the same band. Yet two baseband signals can be separated at the receiver by
synchronous detection using two local carriers in phase
quadrature.
2
2 ……... (5)
2 2 ……... (6)
The last two terms are suppressed by the low-pass filter,
yielding the desired output . Similarly, the output of the
lower receiver branch can be shown to be . This scheme isknown as quadrature amplitude modulation (QAM). Thus, two
baseband signals, each of bandwidth B Hz, can be transmitted
simultaneously over a bandwidth 2B by using DSB transmission
and Quadrature multiplexing.
IV. EQUALIZER
Theoretically, an equalizer [6] should have a frequency
characteristic that is the inverse of that of the transmissionmedium. This will restore higher frequency components and
eliminate pulse dispersion. Unfortunately, this also increases the
received channel noise by boosting its high-frequencycomponents. For digital signals, however, complete equalization
is really not necessary, because a detector has to make relativelysimple decisions- such as whether the pulse is positive or
negative.
4.1 Zero Forcing equalizer (ZF)It is really not necessary to eliminate or minimize ISI with
neighboring pulses for all t. all that is needed is to eliminate or minimize interference with neighboring pulses at their respectivesampling instants only, because the decision is based only on
sample values. This can be accomplished by the transversal-
filter equalizer encountered earlier, which forces the equalizer output pulse to have zero values at the sampling instants. In
other words, the equalizer output pulses should satisfy the
Nyquists criterion or the controlled ISI criterion.
1
……… (7)
4.2 Least Mean Squared Error Equalizer (LMSE)Another approach to equalization, the least mean squared
error method, does not try to force the pulse samples to zero
at 2N points. Instead the mean of the squared errors over a
set of output samples is minimized [7].
The prediction error is given by
^
^
…………. (8)
…………. (9) W k is a weight vector
To compute the mean square error || at time instant k.
||
2
……….… (10)
Taking the expected value of || over k yields
||
2
…. (11)
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International Journal of Electronics Communication and Computer Engineering
Volume 3, Issue 2, ISSN 2249 –071X
Copyright © 2012 IJECCE, All right reserved
W k, filter weights are not included in the time average since,
for convenience, it is assumed that they have converged to
the optimum value and are not varying with time.
V. DIVERSITY
Diversity techniques [8] are based on the notion thaterrors occur in reception when the channel attenuation is
large, i.e. when the channel is in a deep fade. If we can
supply to the receiver several replicas of the sameinformation signal transmitted over independently fading
channels, the probability that all the signal components will
fade simultaneously is reduced considerably.
5.1 Maximal Ratio Combining (MRC)In telecommunications, maximal-ratio combining [9] is a
method of diversity combining in which: (a) the signals
from each channel are added together,(b) the gain of each
channel is made proportional to the rms signal level and
inversely proportional to the mean square noise level in that
channel.(c) different proportionality constants are used for
each channel. It is also known as ratio-squared
combining and predetection combining. Maximal-ratio-
combining is the optimum combiner for
independent AWGN channels. In this method, the diversity
branches are weighted for maximum SNR as can be seen in
Figure 5 [9].
The Combiner output is given by
∑ ………..... (12)
The SNR of the combined signal is
∑
….……… (13)
5.2 Equal-Gain Combining Diversity (EGC )
Various techniques are known to combine the signals
from multiple diversity branches. In Equal Gain
Combining,[10] each signal branch weighted with the samefactor, irrespective of the signal amplitude. However, co-
phasing of all signals is needed to avoid signal cancellation.
In figure 5 each branch signal is rotated by , all branchsignals are then added.
The Combiner output is given by
∑ ……….… (14)
The SNR of the combined signal is
Γ = ∑
.....……… (15)
VI. RESULTS
If we set the simulation environment for the OFDM basedwireless modulation, then we get the variable performance
for equalizers as well as for diversity techniques.
The following results have been obtained with the
considered combinations.
Fig. 1.
Fig. 2.
Fig. 3.
0 3 6 9 12 15 18 21 24 27 30
10-0.15
10-0.13
10-0.11
10-0.09
10-0.07
10-0.05
10-0.03
SNR in dB
B i t E r
r o r R a t e
o f E G
C
BER with 'LS', 'MRC', 'ZF', 'EGC' with 512 Subchannels, 32 QAM and 1000 iterations
LS
MRC
ZF
EGC
0 3 6 9 12 15 18 21 24 27 30
10-0.13
10-0.11
10
-0.09
10-0.07
10-0.05
10-0.03
SNR in dB
B i t E r r o
r R
a t e
o f E G
C
BER with 'LS', 'MRC', 'ZF', 'EGC' with 256 Subchannels, 32 QAM and 1000 Iterations
LS
MRC
ZF
EGC
0 3 6 9 12 15 18 21 24 27 30
10-0.16
10-0.14
10-0.12
10-0.1
10-0.08
10-0.06
10-0.04
10-0.02
SNR in dB
B i t E r r o
r R a t e
o f E G
C
BER with 'LS', 'MRC', 'ZF', 'EGC' with 1024 subchannels, 32 QAM and 3000 iterations
LS
MRC
ZF
EGC
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164
International Journal of Electronics Communication and Computer Engineering
Volume 3, Issue 2, ISSN 2249 –071X
Copyright © 2012 IJECCE, All right reserved
Fig. 4.
Fig. 5.
Fig. 6.
Fig. 7.
Fig. 8.
VII. CONCLUSION
In this paper we have considered the maximum number
equals 3000. We have also considered varying number of subchannels. The wireless communication without the
channel estimation results in high errors. Therefore
channel estimation is important to know the parameters of
the channel and also to get the knowledge of affecting parameters. Without the channel estimation we can not
find the proper knowledge of the channel andimpairments.
If we look at the simulation result with 1024
subchannels and 1000 iterations, we find that the BER curve is becoming linear and therefore with high number
of subcarriers and with 1000 iterations we get more better
results compared to 256 and 512 subchannel conditions.Figure no.7, shows the effect of the
different equalizers and diversity techniques with the
2000 iterations and 1024 subchannels. Here we find the
results in the range of 0.1 to 0.001. But not a good
difference is seen here.
One thing is clear here that with lower order QAMmodulation techniques results are not much comparative,
but results in bunching like the optimum performers.Only the change between performances can be seen with
lower number of subcarriers and with 1000 iterations.
Therefore we conclude with this assumption that with
more number of iterations and with the higher number of subchannels results can be improved but at the cast of high
simulation time. Finally with 1000 iterations we have
better performance of used algorithms and MRC is verymuch able to show expected results and with less
complexity in achieving the better BER performance.
ACKNOWLEDGMENT
Foremost, I would like to express my sincere gratitude
to my advisor Prof. Ravi Mohan for the continuous
support of my M.Tech study and research, for his patience,motivation, enthusiasm, and immense knowledge. His
guidance helped me in all the time of research and writing
of this thesis. I could not have imagined having a better advisor and mentor for my M.Tech study.
Besides my advisor, I would like to thank Prof. L. D.
Malviya for their encouragement, insightful comments,
0 3 6 9 12 15 18 21 24 27 30
10-0.04
10-0.03
10-0.02
SNR in dB
B i t E
r r o r R a t e
o f E G
C
BER with 'LS', 'MRC', 'ZF', 'EGC' with 64 subchannels, 32QAM and 1000 iterations
LS
MRC
ZF
EGC
0 3 6 9 12 15 18 21 24 27 3030
10-0.38
10-0.36
10-0.34
10-0.32
10-0.3
10-0.28
10-0.26
10-0.24
SNR in dB
B i t E r
r o r R a t e
o f E G
C
BER with 'LS', 'MRC', 'ZF', 'EGC' with 64 Subchannels, 4 QAM, and 3000 iterations
LS
MRC
ZF
EGC
0 3 6 9 12 15 18 21 24 27 30
10-0.38
10-0.36
10-0.34
10-0.32
10-0.3
10-0.28
10-0.26
10-0.24
SNR in dB
B i t E r r o
r R a t e
o f E G
C
BER with 'LS', 'MRC', 'ZF', 'EGC' with 64 subchannels, 4 QAM and 1000 iterations
LS
MRC
ZF
EGC
0 3 6 9 12 15 18 21 24 27 3010
-3
10-2
10-1
100
SNR in dB
B i t E r r o
r R a t e
o f E G
C
BER with 'LS', 'MRC', 'ZF', 'EGC' with 1024 Subchannels, 4 QAM and 2000 iterations
LS
MRC
ZF
EGC
0 3 6 9 12 15 18 21 24 27 3010
-3
10-2
10-1
100
SNR in dB
B i t E
r r o r R a t e
o f E G
C
BER with 'LS', 'MRC', 'ZF', 'EGC' with 256 Subchannels, 4 QAM and 3000 iterations
LS
MRC
ZF
EGC
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and hardthank my
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AUTHO
uestions. Lastfamily &
throughout m
RE
ang.K.B. Letaief,
FDM transmissietric channel
49, no. 3, pp 467-
, J.H. Wintess, a
ess communicat
nel estimation,”IE
2002, pp. 1471–1
i Shen and Ed
ms’” January 200
.google.co.in
. Lathi, “Mode
ms“.
dore S. Rappapo
ractice,” 2nd Edit
G. Proakis and
dition
th Hourani, “A
ess communicat
ology.
hah and A.M.
mal ratio comb
ining for mobil
erence”, IEEE
, Jul 2000.
ng, S. D. Blostei
qual Gain Combi
eigh Fading,” IEE
65-870, Sept. 200
’S PROFILE
DeepmDOB - 3rd I have co
communic
of technol
Master of
Technolog
but not the ly friends
life.
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