View
9
Download
0
Category
Preview:
Citation preview
89
CHAPTER 3
SIMULATION RESULTS AND DISCUSSION
3.1 SUB CARRIER ALLOCATION FOR MC-CDMA
The simulation has been performed for the specifications listed
(Wasantha and Fernando, 2002) in table 3.1. From the results shown in Figure
3.1, it is observed that the MC-CDMA system with the BPSK modulation
performs better as the number of users decrease. Here the BER performance
of the MC-CDMA system with 2 users is better when compared to 4, 8, and
16 users. As the number of users is 2, the BER of 4 . 10-5 is achieved which is
a better result when compared for more the number of users.
Table 3.1 Simulation Specifications
Data rate 9600 bits/sec
Chip rate 4.92 Mcps
Processing gain 512
Sub-carrier spacing 1.25 MHz
Modulation BPSK
Band width 5 MHz
Guard band 0.625 MHz
90
Figure 3.1 MC-CDMA with BPSK modulation for different number of
users
Figure 3.2 below represents the water-filling algorithm with 16
users, which is further compared with the root-finding method (Zeng et al
2004). From the figure it is observed that for lesser number of users the water-
filling performs slightly poorer when compared to the root finding method.
But for the case of 16 users, the water- filling performs much better in
allocating power to the users with more number of sub carriers. So it is
inferred that the water-filling is effective for the MC-CDMA system with
higher number of users where the sub-carriers are allocated dynamically.
91
Figure 3.2 Comparison of Water-filling algorithm with Root-finding
method
Figure 3.3 Capacity comparisons of Water-filling and Root-finding
methods
Figure 3.3 illustrates the capacity comparison of the water-filling
algorithm with the root finding method. As the number of users is 4, the
capacity exhibited by water-filling is 4.45 bits/s/Hz, which is high when
compared to root finding that yields 4.25 bits/s/Hz as the throughput. As the
92
number of users is 16, the throughput is 4.9 bits/s/Hz and 4.8 bits/s/Hz for the
water-filling and root finding methods respectively. So the water-filling
dominates the root finding technique in case of adaptive sub-carrier based
MC-CDMA system.
3.2 BER PERFORMANCE FOR PROPOSED MC-CDMA
SYSTEM
From figures 3.4 and 3.5, it is clear that the adaptive sub-carrier
based MC-CDMA outperforms the conventional MC-CDMA as the number
of sub-carriers (M) is increased and for the higher narrowband interference
power to signal power (JSR). In figure 3.4, for an SNR of 30 dB the BER
performance of our conventional scheme is 1.8.10-3 as the number of sub-
carriers is 4 and JSR of value 30 dB, whereas in figure 3.5 for an SNR of 30
dB by using iterative water-filling, the BER performance improved to 10-3.
Figure 3.4 BER Performance of MC-CDMA with M = 4 and JSR = 30 dB
93
Figure 3.5 BER Performance of MC-CDMA with M = 4 and
JSR = 30 dB using Water-filling algorithm
Figure 3.6 BER Performance of MC-CDMA with M =8 and JSR = 30 dB
94
Figure 3.7 BER Performance of MC-CDMA with M = 8 and
JSR = 30 dB using Water-filling algorithm
Figure 3.8 BER Performance of MC-CDMA with M = 512 and
JSR = 30 dB
In figure 3.5, 3.6, 3.7, 3.8, it is observed that the proposed scheme
achieves a BER of 4.10-3 as the number of sub carriers is 8 and for a JSR of
95
30 dB. This is a better performance to the previous case. Finally the Figure
3.6 shows that for an SNR value of 26 dB, the BER performance of the
proposed scheme reaches a fine value of 10-5 as we go for the higher number
of sub carriers (M = 512) with the JSR of 30 dB. So it is clear that the
adaptive sub-carrier based MC-CDMA system with large number of sub-
carriers outperforms the existing schemes with the usage of the iterative
water-filling algorithm for the dynamic sub-carrier selection (Tang and
Stolpman, 2004). Also, with higher number of sub carriers and high narrow
band interference power to signal power value the goal of higher data rates fit
for the future generation systems can be achieved.
3.3 SIMULATION SPECIFICATIONS OF ADAPTIVE
MODULATION BASED MC-CDMA
Simulations of the Adaptive modulation based MC-CDMA system
with the specifications given in table 3.2 under different channel conditions
and different number of CDMA users has been carried out.
Table 3.2 Simulation Specifications
Number of data bits 3.2.103
Number of subcarriers 1024
CDMA code Walsh-Hadamard
Code length 32 chips
Power delay profile Exponential
Cyclic prefix ¼ th
96
The modulation schemes considered are2-QAM, 4-QAM and 16
QAM. In this simulation, perfect channel information is assumed to be
available and be fed back to the transmitter without time delay.
The size of the group has significant impact on the BER
performance of the adaptive MC-CDMA system (Chatterjee et al 2003). For
the small size group, it is easy to select the appropriate modulation format and
improve the system performance effectively; on the other hand, as the number
of the subcarriers in one group should be as same as the spreading factor, the
small size of the group results in small spreading factor, which weakens the
frequency diversity effect. Hence, a tradeoff between the both factors should
be considered to design the size of the group. In our simulation, the number
of subcarriers in one group is 32, i.e spreading factor is 32.
Figure 3.9 BER performance of adaptive modulation (2-QAM) based
MC-CDMA
97
Figure 3.10 BER performance of adaptive modulation (2-QAM) based
MC-CDMA using Water-filling algorithm
Figure 3.11 BER performance of adaptive modulation (4-QAM) based
MC-CDMA
98
Figure 3.12 BER performance of adaptive modulation (4-QAM) based
MC-CDMA using Water-filling algorithm
Figure 3.13 BER performance of adaptive modulation (16-QAM) based
MC-CDMA
99
Figure 3.14 BER performance of adaptive modulation (16-QAM) based
MC-CDMA using Water-filling algorithm
The figures 3.9, 3.10, 3.11, 3.12, 3.13 and 3.14 show the variations
in BER performance of 2 QAM, 4 QAM, and 16 QAM modulation techniques
with respect to signal to noise ratio for different number of users. From the
results it is found that
1. 2-QAM, 4-QAM, and 16-QAM performance is varied for
different number of users; all three modulations perform better
at few numbers of users.
2. For same number of users for example for SNR of 20 dB, when
number of user is four, the 2-QAM shows BER of 5.10-5, 4-
QAM shows BER of 2.10-4 and 16 QAM shows BER of 9.10-3.
3. For fixed values of signal to noise ratio, for varying number of
users 2-QAM outperforms other schemes.
100
3.4 SIMULATION RESULTS OF ULTRA WIDE BAND
In order to demonstrate the simulation results, we assume the
following:
Channel Model : S-V Channel
Bandwidth : 528Mbps (OFDM), 1.58Ghz(MC- CDMA)
Data Rate : 160 Mbps(OFDM),96 Mbps(MC-CDMA)
Modulation : QPSK
Rake finger : 16(Ds-CDMA)
Spreading Code length : 24(DS-CDMA) 20(MC-CDMA)
FFT size : 128 (OFDM),256(MC-CDMA)*
Data tone : 100 (OFDM),200(MC-CDMA)*
Guard Interval : 70.075ns(OFDM),54.0936ns(MC-CDMA)
Symbol Interval : 312.5ns (OFDM),208.33ns(MC-CDMA)
The channel model parameters for four different UWB channel
models are listed in Table 3.3.
* (Sabernia and Tewfik 2003)
Table 3.3 UWB Channel Model Parameters
Channel model parameters CM 1 CM 2 CM 3 CM 4
Cluster arrival rate 0.0233 0.4 0.067 0.067
Ray arrival rate 2.5 0.5 2.1 2.1
Cluster decay factor 7.1 5.5 14.0 24.0
Ray Decay factor 4.3 6.7 7.9 12.0
1 [in dB] 3.4 3.4 3.4 3.4
2 [in dB] 3.4 3.4 3.4 3.4
[in dB] 3.0 3.0 3.0 3.0
101
The time axis is divided into bins, with the bin width defined as the
resolution of the channel or the largest time interval over which the receiver is
not capable of distinguishing separate path. The bin width is chosen to be Tp
which models the fine resolution of multipath components by restricting the
fading of interfering reflections (Simon Haykin, 2002). The resulting taps of
the tapped delay line channel model are separated at approximately integer
multiples of the inverse pulse widthp
1T
. The IEEE channel model is quite
general, and it is described for 167 ps multipath resolution or 7.5 GHz
bandwidth. As mentioned in the previous sections, the entire UWB spectrum
is divided in 14 subbands, each with a 1bandwidth of 528 MHz. The
multipath resolution and center frequency for each band is different. So the
above multipath UWB channel model is no longer applicable. Hence the
channel parameters are generated as per UWB channel model, passed through
a low pass filter and a re-sampling circuit with respect to MB OFDM symbol
rate (Bhai and Saltzberg, 1999). The various parameters like Mean excess
delay, RMS delay spread, Number of paths with energy within 10 dB of the
strongest path ( 10dBNP ) and Number of largest energy path captures 85 % of
the channel energy for UWB channel model are simulated and it listed in
Table 3.4.
Table 3.4 UWB channel statistics
Statistics CM 1 CM 2 CM 3 CM 4
Mean excess delay (nsec) 5.4627 9.7628 15.4725 27.3022
RMS delay (nsec) 5.6879 8.3800 14.2170 25.4445
NP (85% energy) 14 16.53 25.9 63.71
NP (10 dB peak) 22.91 35.36 63.71 116.490
102
Figure 3.15 BER performance of DS-CDMA/OFDM/MC-CDMA at CH-1
Figure 3.16 BER performance of DS-CDMA/OFDM/MC-CDMA at
CH-1 using Water-filling
103
Figure 3.17 BER performance of DS-CDMA/OFDM/MC-CDMA at CH-2
Figure 3.18 BER performance of DS-CDMA/OFDM/MC-CDMA at
CH-2 using Water-filling
104
Figure 3.19 BER performance of DS-CDMA/OFDM/MC-CDMA at CH-3
Figure 3.20 BER performance of DS-CDMA/OFDM/MC-CDMA at
CH-3 using Water-filling
105
Figure 3.21 BER performance of DS-CDMA/OFDM/MC-CDMA at CH-4
Figure 3.22 BER performance of DS-CDMA/OFDM/MC-CDMA at
CH-4 using Water-filling
From the Figures 3.15, 3.16, 3.17, 3.18, 3.19, 3.20, 3.21 and 3.22 it is found
that
1. UWB channel model the MC-CDMA behaves differently for UWB
channel models.
106
2. In channel model 1 using water-filling algorithm, the MC-CDMA
converges to BER of 4.10-6 at 17 dB, whereas DS-CDMA
converges to BER of 4.10-6 at 19 dB and OFDM converges to BER of
1.10-6 at 20 dB.
3. In channel model 2 using water-filling algorithm, the MC-CDMA
converges to BER of 5.10-6 at 19 dB, whereas DS-CDMA
converges to BER of 1.10-5 at 20 dB and OFDM converges to BER of
2.10-5 at 20 dB.
4. In channel model 3 using water-filling algorithm, the MC-CDMA
converges to BER of 6.10-6 at 18 dB, whereas DS-CDMA
converges to BER of 7.10-5 at 20 dB and OFDM converges to BER of
4.10-5 at 20 dB.
5. In channel model 4 using water-filling algorithm, the MC-CDMA
converges to BER of 8.10-6 at 18 dB, whereas DS-CDMA
converges to BER of 3.10-5 at 20 dB and OFDM converges to BER of
5.10-5 at 20 dB.
Recommended