chapter 3 simulation results and...

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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

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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.

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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

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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

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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

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JSR = 30 dB using Water-filling algorithm


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

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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

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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

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MC-CDMA using Water-filling algorithm


MC-CDMA

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MC-CDMA

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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.

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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

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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

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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

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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.

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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.




2.10-5 at 20 dB.




4.10-5 at 20 dB.




5.10-5 at 20 dB.

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