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978-1-4244-4826-5/09/$25.00 ©2009 IEEE 1

Gaussian Approximation Analysis of ZCC Code for Multimedia Optical CDMA Applications

Indu Bala, Vanita Rana Chandigarh Engineering College, Mohali, PB - 140307, India

* Jaypee University of Information Technology, Waknaghat (Solan), HP -173215, India E-mail: indu469@gmail.com,*vanita.rana@juit.ac.in

ABSTRACT In this paper, performance of ideal cross correlated ZCC code is investigated to support different multimedia applications with variable data rates and quality of service requirements in terms of signal to noise ratio and bit error rate. Simplicity in code construction and flexibility in Cross Correlation control has made this code a compelling candidate for future OCDMA applications. Further, various parameters related to the improvement of system performance have also been discussed. Keywords: zero cross correlation (ZCC), optical code division multiple access (OCDMA), optical orthogonal

code (OOC), phase induced intensity noise (PIIN), bit error rate (BER), signal to noise ratio (SNR), multiple user interference (MUI).

1. INTRODUCTION With substantial growth of data traffic, the major technical challenge to today’s communication network systems is for more information carrying capacity to process it rapidly. Among many multiple access techniques, Optical Code Division Multiplexing Access (OCDMA) is one most robust access technique that takes advantage of excess bandwidth in single mode optical fibre to obtain random, asynchronous access [1-5]. The optical CDMA has attracted much attention for various applications of optical communication due to its advantageous features like Simple, random and simultaneous access protocol, bursty traffic, ability to support variable data rates and therefore it’s suitability for multimedia applications, privacy and security in transmission, no need of strict timing and wavelength control, efficient utilization of bandwidth, immunity to various noises etc. [6-10].

The key to an effective optical CDMA system is the choice of efficient address code sequences with excellent autocorrelation and cross correlation properties. Recent studies have shown that an optical CDMA system cannot simply be evaluated by only considering the performance (i.e. correlation properties) of the selected optical pseudo-orthogonal codes. The coding architecture (i.e. the structure of the optical encoders and decoders) is another important factor to consider, since it affects the power budget, size, cost, and eventually the feasibility of the whole system [11]. Therefore, the selection of the optical code and coding architecture used in the system must be considered together to attain best quality services from the network.

In this paper performance evaluation has been done for ideal Zero Cross Correlation (ZCC) code to support data format independent and time transparent transmission to support variable bit rate multimedia applications like multirate data, images, graphics, audio and video for different traffic constraints and Quality of Services (QOS) in terms of Signal to Noise Ratio (SNR) and Bit Error Rate (BER).In addition to this various code and system parameters have also been discussed for further improvement in system’s performance.

2. ZERO CROSS CORRELATION CODE The optimum code set is one having good auto and cross correlation properties with high code cardinality to support maximum number of users with minimum code weight and code length. This ensures guaranteed quality of services with least error probabilities for given number of users at least for short haul optical networking. Studies have shown that major bottleneck in the successful implementation of all optical network is basically multiple user interference (MUI) when all the users try to transmit their data simultaneously. It can be conquered by designing coding sequences such that they may cause least overlapping between data chips.

Recently, Zero Cross correlation (ZCC) codes have been proposed for Spectral Amplitude Coding (SAC) based optical CDMA system [12, 13]. The idealistic cross correlation properties of the code provides excellent system performance in terms of Signal to Noise Ratio (SNR) and Bit Error Rate (BER).The code is represented by R×C matrix where R is number of rows and also represents number of simultaneous users. C is number of columns and represents code length. With the help of mapping and transformation techniques the code can be designed for any code weight to support different multimedia applications. For example implementation of OCDMA system with this code may support three different multimedia applications with 3 sequences of weight 2, 4 with weight 3 and 5 with weight 4 and so on.

3. PERFORMANCE ANALYSIS FOR ZCC CODE In this section, Signal to Noise Ratio (SNR) and Bit Error Rate (BER) performance for incoherent SAC optical CDMA has been investigated for Zero Cross Correlation (ZCC) optical orthogonal code using method suggested

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in [12-13]. It has been assumed that Multiple User Interference (MUI) is mainly due to thermal noise, shot noise and Phase Induced Intensity Noise (PIIN). Since the code has idealistic zero cross correlation properties, the effect of PIIN noise has been neglected here. With this assumption, SNR will be given by

22

2

41

sr

b n nsr

L

PR pSNRK T fFw kq fRP

v R

≅Δ+ +Δ +

, (1)

where

( )182e

SNRP erfc= . (2)

Fig. 2 and Fig. 3 are showing the system performance in terms of SNR for different code weights at 160 Mbps data rate from each user at -10 dBm, -5 dBm respectively. Because of the non existence of phase induced intensity noise (PIIN) increase in number of simultaneous users hardly affect the system performance. Further, the scope of improvement in system performance is large by increasing the effective power from each user at receiver end. Moreover, it is also clear from the diagrams that increase in code weight causes degradation in SNR.

Figure 2. SNR versus number of simultaneous users with Psr= -10dBm with different code weights at 160 Mbps.

Figure 3. SNR versus number of simultaneous users with Psr = -5dBm with different code weights at 160 Mbps.

Figure 4. SNR versus number of simultaneous users with

Psr = -10dBm, code weight 11 for variable data rate. Figure 5. SNR versus number of simultaneous users at

Psr = -5dBm, code weight 11 for variable data rate.

Fig. 4 and Fig. 5 are showing the effect of variable data rate on signal to noise ratio of the system. It is clear from these graphs that signal to noise ratio degrades with an increase in transmission rate of the system. Moreover, in the absence of phase induced intensity noise (PIIN) for given transmission rate more number of users can be accommodated without any degradation in system SNR. The effect of an effective optical power from each user can also be observed from these graphs. It is clear that for Psr > -10 dBm from each user the system performance increased significantly.

Fig 6 and Fig. 7 are showing variation in bit error rate with respect to the number of users at Psr = -10 dBm for variable data rates at code weight 23 and 11 respectively. It can be easily make out from these figures that the system performance degrades with an increase in transmission rate whereas, it is possible to accommodate more number of users with same effective optical power and data rate by designing a code with less weight and therefore with less system complexity for assured quality of services for different multimedia applications.

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Figure 6. BER versus number of simultaneous users with

Psr = -10 dBm, code weight 23 for variable data rate. Figure 7. BER versus number of simultaneous users with

Psr = -10dBm, code weight 11 for variable data rate.

Figure 9. BER versus effective optical power for different

code weights for 150 simultaneous users. Figure 10. BER versus effective optical power for different

code weights for 450 simultaneous users.

Fig. 9 and Fig. 10 are showing BER variations for different code weights with respect to an effective optical power from each user for 150 and 450 simultaneous users respectively. The BER improvement can be seen from these graphs for Psr > -10 dBm. The effect of an increase in code weight can also be observed. It is clear that with an increase in code weight Bit error probabilities increased as it is concerned with number of ones in the code and therefore power transmitted.

4. CONCLUSION In the absence of the phase induced intensity noise (PIIN) zero Cross correlation code shows excellent performance with spectral amplitude coded asynchronous optical CDMA system. It has been observed that for stated code number of simultaneous users hardly affect the system performance and the scope of improvement in system performance is large by increasing the effective power from each user at receiver end. Though number of users can be increased further by increasing code weight but it affects the system performance severely. Therefore, it is advisable to increase the user’s optical power instead of code weight to enhance the system performance.

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