International Journal of Engineering Trends and Technology (IJETT) – Volume 18 Number3 - Dec 2014
DS-CDMA System with Multiuser Detection and
MMSE Equalizer to Mitigate MAI
Sunita Waykole
PhD. Research Scholar, Mewar University, Rajasthan
Abstract- Wireless communication has drastically shown
evaluation mobile communication and its counterparts. Code
Division Multiple Access is one of the reliable multiple
access methods appropriate for sustaining lots of new
services
for ex ample
speech,
video,
multimedia
applications, which are becoming progressively more
important for mobile communications. The multiple data
rates, future systems would also require boosting the
performance and capacity requirement. Direct Sequence
Code Division Multiple Access is very common proposed
CDMA system for the 3rd generation (3G) of wireless mobile
system. A DS-CDMA system using usual receiver methods
is limited in capacity due to the multiple
access
interference
and
the
near-far
consequence
will
significantly humiliate its performance. These troubles can
be solved by employing multiuser detection methods,
together with the optimum detectors and suboptimum ones.
Though optimum detectors provide high performance and
high capacity, it is very complicated to implement them due to
excessive computational complication, which grows
exponentially raised with the number of user. The MMSE
detector has very low complexity and provides satisfactory
performance.
Keywords- Multiple Access Interference (MAI), Direct
Sequence Code Division Multiple Access (DS-CDMA), and
MMSE.
I.
INTRODUCTION
Recently, there has been an increasing interest in
telecommunications towards new services and more
flexible communication systems. As an introduction to
the area of cellular communication systems t he
concept of a cellular system is introduced with
different approaches of multiple access techniques that
are widely used in communication systems. The main
idea of a cellular system is to divide the system service
areas into smaller areas, called cells, which are served
by separate base stations. The transmitted power of
the base stations will limit the coverage service area.
For increasing the capacity of a system, frequency
reuse technique must then be employed to reuse the
allocated frequency at the closet possible distance
without the interference level exceeding tolerable limits.
Several cells in a system are grouped into clusters in
which different frequencies are allocated to different
base station. The same frequencies are consequently
shared in other clusters. The number of cluster sizes, N,
ISSN: 2231-5381
could be obtained by
(1.1)
where i and j are arbitrary integer numbers such that 0 i <
j. It is obvious that the allowable number of cluster sizes
are N = 1, 3, 4, 7, 9, etc. The capacity of a system is
increased if the size of the cells is reduced, as the
allocated frequency band may be reused at shorter
distances. Nevertheless, this demands an increase in the
number of base stations and a decrease in the base
stations’ transmitted power. The cellular mobile network
with a cluster size of 4 is given in Figure 1.1. It shows
how a service region with many cells is connected via a
mobile.
II.
SYSTEM MODEL
CDMA is known as a spread spectrum technique, since
each user is assigned a unique spreading code to spread
the narrow band information signal over the whole
bandwidth. The most common CDMA methods are
frequency-hopping (FH) and direct-sequence (DS). In a
FH- CDMA system, the carrier hops from one frequency
to another in a pseudo-random hopping- pattern
controlled by the spreading code. For a DS-CDMA, the
spreading code is a pseudo-ransom, typically binary
sequence, with a much larger bandwidth than the
transmitted information signal. The information is
multiply by the spreading code to introduce rapid phase
transitions and accordingly increase the signal bandwidth.
The DS-CDMA technique is proposed for the third
generation of mobile systems.
DS-CDMA has many advantages for employing in the
next generation of mobile systems. First, it provides a
soft capacity meaning that there is no limited number of
users in the system. Second, a frequency reuse factor of
one can be deployed, thus allowing the whole spectrum
bandwidth to be theoretically reused in every cell. The
soft handoff, referred to the possibility of a mobile
station moving close to the cell boundary to establish the
new base station, can be implemented. This procedure
ensures that the quality of the radio link to the new base
station is not disconnected. In addition, in a soft
handoff, the mobile station can transmit using less power
and thus reducing the interference to intra-cell users as
well as to users in neighboring cells. Other advantages
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International Journal of Engineering Trends and Technology (IJETT) – Volume 18 Number3 - Dec 2014
of DS-CDMA include the rejection of narrow band
interference and the possibility to exploit multipath
diversity combining at the receiver. DS-CDMA,
however, experiences two main difficulties, i.e., the
near-far problem and the multiple access interference
(MAI).In synchronous CDMA systems with no
multipath propagation, orthogonal codes can be used and
therefore the users do not interfere with each other.
Original Bit Sequence
1.5
1
0.5
0
However, if the system is not completely synchronized
due to multipath propagation, the users will experience
MAI. This trouble is more accentuated by the near-far
problem. The near-far problem occurs especially in the
uplink (mobile station to base station) when a weak
signal from a distant mobile station is swamped out by
the strong signal from a mobile station closer to the base
station. Even the mobile station at the same distance
from the base station, the channel can be introduced
fading leading to the same effect.
Stringent power control, where the base station adjusts
the power level of the mobile stations so that the power
they receive is equal, is one way to combat the near-far
problem.
-0.5
0
20
40
60
80
100
120
Figure 1: Original Bit Pattern
Similarly we may find that the pseudorandom bit pattern
will look like as shown in figure 2:
Pseudorandom Bit Sequence
1.5
1
0.5
If the MAI is kept within reasonable limits by a good
code design and a moderate number of users, it is
possible to detect the signals using conventional matched
filter techniques with an acceptable loss in performance.
If there are many users in the system and the power
control is not ideal, the performance loss may be
substantial. This is the main reason for considering the
multiuser detection.
III.
PROBLEM FORMULATION
In a multiuser system problem of getting the probability
of error is very high because of the congestion in network
or in channel and also due to the multi path propagation.
Different equalizers show varying degree of the error
correction capabilities and their performance is again
limited by the intersymbole interference and also due to
the multiple access interference.
0
-0.5
0
20
40
60
80
100
120
Similarly look at the Direct Sequence Spread Spectrum
CDMA signal, as the DSSS sequence is shown for the
12000 samples therefore we will find it modulated
throughout the sequence. Please see figure no. 3:
DSSS Signal
1.5
1
0.5
0
-0.5
IV. SIMULATION RESULTS
After the theory and the thorough discussion of DSSS
CDMA we are able to run our simulation codes. First of
all let us see the original bit sequence. Plot of the
considered bit pattern is shown below in figure 1:
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-1
-1.5
0
2000
4000
6000
8000
10000
12000
Let us now see the Fast Fourier Transform of the DSSS
signal. We find that as we are dealing with the BPSK
modulation therefore the high peaks can be seen on the
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International Journal of Engineering Trends and Technology (IJETT) – Volume 18 Number3 - Dec 2014
two positions only and the lower amplitudes for the
remaining because BPSK has only two symbols. Given in
figure no. 4:
0.6
0.5
MMSE_BER
(Delay=1)
0.4
Plotting the FFT of DSSS signal
1200
0.3
MMSE_BER
(Delay=2)
1000
0.2
800
MMSE_BER
(Delay=3)
0.1
0
600
-0.1 0
400
Tap=
0.01
20
Es/No------>
200
0
10
0
2000
4000
6000
8000
10000
12000
14000
0.2
0.15
MMSE_BER
(tap=0.0)
0.1
MMSE_BER
(tap=0.2)
0.05
MMSE_BER
(tap=0.01)
0
0
5
-0.05
10
15
20
0.25
0.2
Es/No-------->
Figure5: Effect of tap weight on the performance of
MMSE Equalizer
From the simulation model of our case we find that the
MMSE equalizer along with the CDMA
results in minimizing BER in many ways. First of all let
us consider the case of figure 5, where we consider the
case of variation in tap weight. This is an important
parameter in MMSE algorithm, because it affects the
performance of considered equalizer. From the
simulation results it is very much clear that tap weight
should be low otherwise probability of error (BER) will
go high and which in turn degrades the performance of
receiver.
There is one more parameter to affect the performance
of MMSE equalizer that is path delay. In static
conditions we always consider channel as constant but
in case of dynamic channel measurements, delays are
variable.
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Figure 6: Consequence of delay on the performance of
MMSE equalizer
From figure no. 5 we considered the case of tap weight
and found that the tap weight should be low. Let us
consider the case of tap weight =0.01 and vary the other
parameter delay in figure 6. We find that lower delays are
considerable because lower delays can result in low
processing casts and due to them BER is low. Otherwise
higher delays will result in degrading the performance of
our receiver.
0.15
MMSE_BER(
Delay=1)
0.1
MMSE_BER(
Delay=2)
0.05
MMSE_BER(
Delay=3)
0
0
-0.05
5
power----->
Figure 7: Effect of power on the performance of MMSE
with variable delays
Third most important parameter is the power. We always
pay higher casts of processing that is involved in whole
receiver from hardware to software power consumption.
From figure 7, we find that if the delays are high than the
BER will become very high with low power
consumption.
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International Journal of Engineering Trends and Technology (IJETT) – Volume 18 Number3 - Dec 2014
0
0.14
10
128Chiplengthusers10
DD ber
CD ber
128Chiplengthusers100
0.12
-1
10
0.1
BER----->
BER----->
0.08
-2
10
0.06
0.04
-3
10
0.02
X: 20
Y: 1.76e-008
0
0
2
4
6
8
10
Eb/No------>
12
14
16
18
20
-4
10
0
1
2
3
4
SNR----->
5
6
7
8
Figure 8: Comparison of direct detection and CDMA
detection
From figure 8, we find that direct detection algorithms
results in more BER whereas CDMA will result in less
BER. From above result we find that for the less value of
SNR performance of direct detection and CDMA
detection there is no difference. But for higher SNR
conditions CDMA shows better performance the range of
error in CDMA in this case is 10-4
0
10
MMSE ber
CD ber
Actual ber
-1
BER------>
10
-2
10
-3
10
-4
10
1
2
3
4
5
6
7
8
SNR---------->
Figure 9: Comparison of MMSE BER with CD ber and
Actual BER
From figure9, it is clearly seen that if we consider CDMA
without MMSE than BER performance is low and it can
be improved by using MMSE with CDMA.
From figure 10, we see that the direct sequence with
multiuser detection and with MMSE equalizer we are
able to fight with the multiple accessing that result in
multi access interference (MAI).
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Figure 10: DS-CDMA with Multiuser Detection and with
MMSE equalizer
From above figure it is clearly visible that DS-CDMA
with Multiuser detection and with MMSE equalizer our
BER range can be improved drastically. Now in this case
we find the improvement in BER that is in the range of
10-8 with the chip length of 128.
V.
CONCLUSIONS
DS-CDMA is the very commonly proposed CDMA
system for the 3rd ( 3 G ) generation of mobile systems.
It has many advantages as explained earlier. On the
other hand, its performance is mainly degraded by the
near-far problem and the multiple access interference.
One way to circumvent these difficulties is to utilize a
multiuser detector. To reduce the computational
complexity, linear detectors may be employed because
their complexity increases linearly with the number of
users. The MMSE equalizer if compared with the
existing CDMA techniques then very good BER
performance can be expected in it. The MMSE linear
detector is one of such linear detectors. DS-CDMA with
Multiuser detection and with MMSE equalizer result in
BER range improved. Now in this case we find the
improvement in BER that is in the range of 10-8.
Considered chip length is 128 and by increasing chip
length we can also improve BER performance.
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