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CHAPTER 3

PERFORMANCE OF MODULATION FORMATS ON

DWDM OPTICAL SYSTEMS

3.1 INTRODUCTION

The need for higher transmission rate in Dense Wavelength

Division optical systems necessitates the selection of a suitable modulation

format for the efficiency of the optical system and has been a key issue in

recent research (Vassilieva et al 2001). Generally modulation formats are

classified into On Off Keying (OOK) and Phase Shift Keying (PSK)

techniques (Idler et al 2003). Over the last few years, novel modulation

formats with improved performance than the NRZ scheme have been

suggested and investigated, (Matsuda et al 1998). From the literature it is

found that by adapting a Return-to-Zero (RZ) format we can improve the

receiver sensitivity and non-linear tolerance (Winzer and Kalmar 1999,

Caspar et al 1999), but at the extra cost of one additional modulator and drive

circuitry in the transmitter.

Phase modulation combined with a balanced receiver offers a very

attractive 3 dB improved receiver sensitivity compared to OOK, (Ferber et al

2003). Recently, many OOK formats with additional phase modulation have

been shown to perform very well under certain circumstances, for example

Chirped-RZ scheme (Bergano et al 1998) which however, adds further

complexity to the transmitter. Four-level phase modulation - Differential

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Quadrature Phase Shift Keying (DQPSK) has also been studied recently

(Griffin et al 2003, Wree et al 2002, Cho et al 2003).

In this chapter the impact of the fiber non-linear effect is studied for

a 32 channel DWDM system for RZ and NRZ modulation formats using the

OPT package and the spectrum of Duobinary and CSRZ modulation formats

are also observed. The spectrum is also observed for a single channel system

as by, (Binh and Csematony 2003) and a sixteen channel system for RZ and

NRZ modulation formats with phase shift keying by carrying out a

simulation using MATLAB simulink for our fiber and data rate specifications.

The multi channel CSRZ – DQPSK modulation format for 16

Unequal spacing channels is also simulated and the Q factor is observed. In

addition, the impact of filtering techniques and dispersion compensating

techniques are also analyzed in terms of Q factor and Eye Opening Penalty to

identify methods for improving the spectral efficiency.

3.2 IMPACT OF NON-LINEAR EFFECTS ON MODULATION

FORMATS

3.2.1 RZ, NRZ and CSRZ

All modulation formats can be divided into NRZ-based and RZ-

based modulation formats, (Mohs et al 2000). In this thesis, we have made an

effort to study these modulation formats on a 32 channel DWDM system at

40 Gb/s bit rate per channel accounting for the impact of non-linear effects

like XPM and FWM.

A simulation scenario is set up initially as shown in Figure 3.1,

(Hodzic 2004) and applied in this work for our specifications. The system and

fiber parameters used for the simulation are listed in Tables 3.1 and 3.2

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respectively. The channels allotted are chosen between 191.9 and 195 THz

with 100 GHz spacing in the C band, with EDFA based amplification and

dispersion compensating fibers. The transmission data are coded into NRZ

sequences and RZ sequences and the corresponding Q factors are measured

and plotted with and without the inclusion of non-linear effects. The Q factors

obtained with and without the non-linear effects are plotted with respect to the

channel numbers as shown in Figure 3.2.

The Quality Factor in this case is defined as the center frequency

divided by the signal bandwidth in Hertz. The non-linearity comes into

picture when the signal power per channel is higher, in this case 6 mWs.

When the power is reduced to 2 mWs the non-linear effects observed are

negligible.

Figure 3.1 Simulation setup for 32 channel DWDM system

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Table 3.1 Simulation parameters for the system at 40 Gb/s

Parameter Values

Rise time of electrical signal MZM extinction ratio Duo binary low pass filter Duo binary low pass filter cut off frequency Laser frequencies Laser Line width Simulation bits PRBS length NLSE step size Sample rate EDFA noise figure Splice loss Optical filter Optical filter 3 dB bandwidth

5 ps Infinite Fourth order Bessel type 11.7 GHz 193.1 THz - 195 THz 10 Hz 1024 210 – 1 1000 m (or) 0.06 rad 32 samples / bit 5 dB 0 dB Second Order Super Gaussian 100.0 GHz

Table 3.2 Fiber parameters used in the simulation

for 32 channels , Keiser(2000)

Parameters SMF DCF

Length 80 km Variable ( 14.5 kms)

Attenuation 0.2 dB/km 0.25 dB/km

GVD 16 ps/nm/km -72 ps/nm/km

Slope 0.08 ps/nm2 0.08 ps/nm2

Effective Area 80 µm2 30 µm2

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Figure 3.2 Q-factor performance of NRZ modulation format

It is observed from Figure 3.2 that the Q factor is degraded with the

inclusion of non-linearities. It is also noted that the maximum Q factor

degradation is seen for the center channel. When the impact of non-linearity is

not included the center channel has a Q factor of 18 which gets reduced to 13

in the presence of non-linear effects. Hence we come to the conclusion that

non-linear effects will affect the spectral efficiency and the performance

degradation is maximum for the channels placed in the center.

The Q factor obtained with and without the non-linear effects in

this case of RZ shaping, is shown in Figure 3.3. In the case of RZ format, the

width of the optical signal is smaller than its bit period. It is observed from the

figure that there is degradation in Q factor due to non-linearity, however the Q

factor obtained is much higher than the case of NRZ formatting. The reason

for its superior performance is probably due to its ‘return-to-zero’

characteristic.

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Figure 3.3 Q-factor performance of RZ modulation format

Duo binary format whose spectral width is half of the standard

NRZ format is a possible way to increase spectral efficiency but it’s resistance

to nonlinear effects is not so large because the phase information is vulnerable

to interaction with Amplified spontaneous emission noise and SPM

(Yonennaga et al 1995, Keiser et al 2000). Thus this type is suitable only for

short distance DWDM systems. The spectrum of the Duo binary signaling

scheme obtained with our simulation for the design parameters from Table 3.1

is shown in Figure 3.4.

The narrow pulse nature of RZ format has a wider spectrum

leading to less spectrum efficiency in a DWDM system. To overcome this

difficulty and to improve the spectrum efficiency Carrier-suppressed RZ

(CSRZ) modulation has been recently proposed for high bit rate transmission

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Figure 3.4 Spectrum of the duo binary signal

systems, and has been intensively investigated in numerical and experimental

works (Miyamoto et al 2000). The transmitter and the fiber section for the

CSRZ format is shown in Figures 3.5 and 3.6, respectively as in Bosco et al

(2002). The spectrum obtained is shown in Figure 3.7. The carrier component

of the CSRZ signal spectrum is suppressed due to the external modulation at

“zero” point in the second MZM.

The CSRZ pulses possess a RZ signal shape with an optical phase

difference of π between adjacent bits. We have carried out investigation with

the CSRZ modulation format along with the phase modulations in this thesis.

The spectrum of the CSRZ modulation has been studied in this work for our

specification in the Table 3.1.

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Figure 3.5 Transmitter section of CSRZ format

Figure 3.6 Fiber section of CSRZ format

40 Gbs

CW laser

20 G clock

MZM2

20 G clock

MZM1

Loop control Number = 6

EDFA 1 EDFA 2 EDFA 3

SMF SMF SMF

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Figure 3.7 Spectrum of CSRZ format

3.2.2 Optimal Pre-Transmission Filter for DWDM Systems

A spectral efficiency of 0.1 b/s/Hz is realized with 100 channels of

100 GHz spacing and 10 Gb/s rate per channel. Spectral efficiency is

generally defined as the ratio of the per channel data rate to the channel

spacing in WDM systems. One way to improve the spectral efficiency is to

increase the data rate from 10 to 40 Gb/s and maintaining an optimum

channel spacing ( Ito et al 2000). The minimum channel spacing is limited by

the non-linear effects and the data rate efficiency depends on the modulation

format. Due to reduced spectral width, CSRZ modulation shows an increased

dispersion tolerance and is also more robust to non-linear impairments than

conventional RZ and NRZ systems, (Miyamoto et al 1999).

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The non-linear tolerance of CSRZ modulation can be enhanced by

the implementation of pre-chirp at the transmitter side (Sano and Miyamoto

2001) but the amount of pre-chirp has to be carefully optimized in order to

avoid the increase of linear cross talk and waveform distortions. The

robustness of CSRZ modulation to narrow band filtering can be improved and

hence can be beneficial for DWDM systems (Morita and Edagawa 2003). In

the reported literature, various transmission filters like Butterworth,

Chebychev, Dielectric, Fiber Bragg Grating, Arrayed Waveguide Grating and

Mech-Zender Interferometer Filter have been analyzed (Hodzic et al 2003).

In this section, the performances of a Gaussian Filter, a Second

order Super Gaussian Filter and a Flat top Bragg Grating Filter are compared

by simulating the setup shown in Figure 3.8. Narrow band filters with sharp

filter edges and flat pass band represent the optimal solution for DWDM

systems Teraxion (2002). For the numerical investigation presented here, the

characteristics of flat top filters are emulated using Gaussian filters of higher

order degree n 2.In this work, we have measured the performance of the

filter by finding the Q factor .The frequency response of such a Super

Gaussian filter is defined by the transfer function, Hodzic (2004),

2n

3dB

( ln 2 2(f fc)T(f ) expf

(3.1)

where fc is the filter central frequency, n defines the order of the filter and

Δf3db represents the 3-dB optical bandwidth of the filter. The increase in filter

order results in increased steepness of the filter edges. In this section, we have

used a second order Super Gaussian filter. A binary sequence of 29 bits is

considered to assess the performance of a single channel case. As these filters

have a real transfer function, delay distortion does not occur. Using low

dispersion fibers reduces the problem of dispersion, but increases the effect of

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FWM and using high dispersion fibers results in decreasing the effects of

XPM, (Kai Song 2000). The simulation parameters used are listed Table 3.3.

Figure 3.9 shows the eye diagram with measured Q factor in our simulation

using OPT simulation package.

Figure 3.8 Simulation set up for filter performance study

Table 3.3 Simulation parameters used in the setup to

study filter performance

S.No. Parameter Values

1 Number of loops 09

2. Input power per channel 0.25 mW

3. SMF and DCF lengths 80 kms and 14.5 kms per span

4. EDFA parameters Noise Figure 4 dB, Gain 30 dB, two per span

5. WDM channels, data rate 192.5 -193.7 THz, 40 Gb/s

6. Transmitter filter bandwidth 80 GHz bandwidth

Figure 3.9 Q factor measured at the receiver output

Tx Filter Fiber EDFA Detector

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Figure 3.10 shows the Q factor measured for our specification and

simulation parameters at the receiver output for varying fiber lengths for

various filters like Bragg Grating, Gaussian, Super Gaussian and Fabry Perot

Filters. The reduction in Q factor for increasing distances indicates the

necessity for a dispersion management technique. Super Gaussian filter of

higher order, in this case four, is observed to give the highest Q factor. Bragg

grating Filter shows a performance close to that of the Super Gaussian filter.

Super Gaussian filter show better tolerance to dispersion and nonlinearity due

to it’s reduced spectral width as the order increases. Hence more number of

channels could be incorporated in the available spectral width of the optical

channel resulting in an improvement in the spectral efficiency. This filter has

no negative side lobes hence this can be incorporated for the dispersion

managing schemes to limit the interactions of XPM and FWM effects.

Figure 3.10 Receiver output Q factor variation with distance

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3.3 MODELING THE PHASE SHIFT KEYING METHODS

Phase Shift Keying (PSK) uses the phase of the optical carrier to

encode information. The Differential PSK has larger resistance to non linear

effects at higher data rates, (Rhode et al 2000).Wree et al (2002) investigated

the improvement in the spectral efficiency for RZ DQPSK using balanced

detection. The Differential Quadrature Phase Shift Keying (DQPSK)

modulation characterized by a symbol rate that is only half of the nominal bit

rate, results in better narrow-band filtering characteristics and an improved

dispersion and PMD tolerance (Hoshida et al 2003). The interaction between

the ASE noise and the non-linearities will modify the probability density

function used for BER calculation. It has been shown that (Ho 2004), non-

linear noise induced by ASE does not have the characteristics of a Gaussian

pdf.

The general architecture used for system modeling is shown in

Figure 3.11, (Binh and cheung 2005). The pseudo random data bit sequence is

simulated using the Bernoulli binary generator available in the

communication block set of the SIMULINK. CW LASER is modeled by the

sine wave generator available in the signal processing block set.

The main section for simulating NRZ/RZ-DPSK modulation

techniques is shown in Figure 3.12, consisting of DPSK block and the Phase

Modulation (PM) block, ( Liem et al 2005). The NRZ electrical signal is first

encoded by DPSK encoder and the encoded electrical signal is then used to

drive an electro-optic phase modulator to generate a DPSK optical signal. The

expanded simulation block for DPSK and PM are shown in Figures 3.13 and

3.14, respectively, ( Liem et al 2005). Inside the PM block, the input port 1 is

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fed with the optical carrier and input port 2 is fed with the DPSK electrical

data. To produce the NRZ-DPSK optical signal, the complex phase shift

block is then used to phase shift the optical phase by π when the data bit is ‘1’

and a phase shift of zero when the data bit is ‘0’. In the case of RZ DPSK an

additional Intensity modulator is added and in this additional MZIM, the

NRZ-DPSK optical signal from output of the PM block will be sampled by a

pulse generator to achieve the desired RZ-DPSK signal. The sampling pulse

train is synchronized with the input electrical sequence and is at the same rate

as the data rate. The results are observed and studied for the simulink models

taken from the Binh etal 2006 for our date rate and specifications towards the

spectral improvement.

In the receiver block, the NRZ-DPSK optical signal is demodulated

and passed through a low pass filter to remove the carrier. A one-bit-delay

Mach-Zehnder Interferometer (MZI) is usually used as a DPSK optical

receiver as shown in Figure 3.15, ( Binh et al 2006).

In a DPSK balanced receiver, a photodiode is used at each MZI

output and then the two photocurrents are combined (logical subtract) to

double the signal level (Binh et al 2005). The spectrum of the NRZ-DPSK

and RZ-DPSK modulated signals obtained from simulation are shown in

Figures 3.16 and 3.17, respectively for our specification. Based on the

investigation made by the models proposed by Binh et al monash university

we have simulated the RZ and NRZ DPSK spectrum for our data rate and

specifications as discussed.

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Figure 3.11 General architecture for system modeling (Binh et al 2006)

Encoder signal shaping circuit

Input

Modulator

Optical source

Optical fiber

Optical

fiber EDFA

Optical detector

Decoder Demodulator

Amplifier

Output

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Figure 3.12 Main section for simulation of NRZ/RZ-DPSK modulation techniques

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Figure 3.13 Expansion of DPSK block

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Figure 3.14 Phase modulation block

85

Figure 3.15 Receiver block

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Figure 3.16 NRZ -DPSK spectrum at fiber input

Figure 3.17 Spectrum of the RZ-DPSK

Frequency (GHz)

Frequency (GHz)

87

An optical transmission with very high spectral efficiency is one of

the objectives of this research work. Various modulation formats for very

high spectral efficiency have been investigated in the literature, such as

Duobinary (Yonenaga and Kuwano 1997), NRZ VSB (Idler et al 2002) and

Narrow Band RZ (Gnauck et al 2003) to name a few.

A common feature of all these techniques is that of narrow signal

bandwidth with a reduction in the symbol rate. DQPSK is another spectrally

efficient modulation format by which two bits per symbol is transmitted.

DQPSK is a four-symbol format equivalent to phases of {0, π/2, π, 3π/2}.

Depending on the desired di-bit combination to be encoded, the difference in

phase, Δφ, between the two adjacent symbols (optical carrier pulses) is varied

systematically, (Griffin and carter 2002). The signal spectra before and after a

fiber length of 450 Kms for RZ-DQPSK are as depicted in Figures 3.18 and

3.19, respectively. The general simulation block, received signal eye-diagram

and signal spectra for CSRZ-DQPSK are shown in Figures 3.20 ,3.21 and

3.22, respectively. In order to built the simulation block in simulink for CSRZ

DQPSK we have studied the models and lay out for NRZ / RZ DPSK and

RZ DQPSK from ( Binh and Laville 2005) series of Monash university and

the results which are discussed in this chapter for the above formats are

obtained for our model parameters .Hence in our work the model of CSRZ –

DQPSK has been developed based on the other modulation formats

simulation , the results are obtained for the CSRZ DQPSK spectrum and eye

pattern at the detector output (Ramprasad and Meenakshi 2005) .

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Figure 3.18 RZ-DQPSK spectrum before the fiber

Figure 3.19 RZ-DQPSK after propagating 450 kms in the fiber

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Figure 3.20 CSRZ-DQPSK simulation set up

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Figure 3.21 Receiver eye pattern CSRZ-DQPSK

Figure 3.22 Spectrum of CSRZ-DQPSK

Time (bit period)

Am

plitu

de

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3.4 EYE OPENING PENALTY

A broadened eye opening is seen at the receiver for ideal optical

transmission. The comparison of the different modulation formats is done

with reference to the Eye Opening Penalty (EOP) which is defined as the ratio

of the difference in the eye openings of the mark and space state to the

difference in their corresponding variance.

In order to compare the transmission characteristics of PSK-based

modulation formats, a 40 Gb/s DWDM transmission system with Unequally

Spaced Channels and 7 spans of SSMF fibers of span length 80 kms is

considered. The EOP values are measured from the simulation model shown

in Figure 3.23 using MATLAB SIMULINK by varying the transmission

distance for 16 channels with USC scheme. The transmitter, receiver and fiber

parameters used are as listed in Tables 3.4 and 3.5.

Figure 3.24 provides a comparison of the EOP at different fiber

spans for the NRZ-DPSK, RZ-DPSK and the CSRZ-DQPSK modulation

formats. The figure shows that CSRZ-DQPSK offers the best transmission

results up to 560 kms. This is certainly due to its low symbol rate, which

suppresses the effects of fiber dispersion and subsequent nonlinear effects on

the signal as well as good narrow-band filtering characteristics. However

when compared to RZ-DPSK, the signal quality steadily decreases at greater

transmission spans. This can be attributed to the effects of ASE induced phase

noise, which accumulate as the transmission distance increases, resulting in

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Figure 3.23 Simulation model for measuring EOP and Q factor

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Table 3.4 Simulation parameters used to determine Q factor for USC and ESC scheme.

S.No. Parameter Values used in the model

1. PRBS 2.5 Gb/s,223-1,10Gb/s

2. Pulse generator NRZ /RZ Encoding

3. Laser Diode 3 mw power per channel line width 10 MHz

4. Modulator MUX

Mech zender modulator Gaussian MUX filter at the transmitter

5. EDFA Gain 12 db, Noise factor 4 dB.

6. Fiber Nonlinear dispersive fiber length 60 km , attenuation 0.22db/km

7. Optical filter Trapezoidal filter with Zero dB bandwidth 45 GHz, Cut off Bandwidth 50 GHz, Cut off Magnitude 30 dB.

8. Photo detector Responsivity 1 A/W ,Dark current 10 nA

9. Low pass Filter Bessel filter Bandwidth 1.875G Hz

10. Power per channel Variable power in milli watts per channel

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Table 3.5 Non-linear dispersive fiber parameters used in the simulation

Lucent (2001)

Parameters Values

α attenuation 0.25 dB/km

Input coupling efficiency -1 dB

Output coupling efficiency 0.022dB

GVD constant 4.5 ps/nm/km

Dispersion slope constant 0.11ps/nm2/km

Effective Area 72 m2

N2 constant 2.6 e-20 m2/w

Peak Raman gain coefficient 9.9 e-014 m/w

Pump wavelength 1000 nm

Raman self shift time 5 fsec

Figure 3.24 EOP measurements for the modulation formats

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larger phase fluctuations and possible errors in the detection process.

RZ-DPSK can cope better with these effects and is less severely affected over

the entire transmission span, because of better error tolerance at the receiver

compared to DQPSK. NRZ-DPSK has higher EOP values and larger

variations in the EOP due to its reduced non-linear tolerance, (Ramprasad and

Meenakshi 2005 ).

3.5 IMPACT OF FWM ON MODULATION FORMATS

3.5.1 Q Factor Measurement

Based on the simulation model, the Q factor is measured for

various modulation formats namely RZ, NRZ, CSRZ and VSB-RZ. The block

diagram with optimum filter design to generate VSB-RZ and CSRZ are

obtained from the previous section. The fiber is modeled as non-linear and

dispersive thereby giving rise to FWM components in the DWDM system

considered for simulation. Table 3.6 shows the measured Q factor for NRZ

modulation with four channels at 10 Gb/s and other parameters same as

shown in Tables 3.4 and 3.5. The channel allocations using ESC technique

and orthogonal coding based USC techniques, for four channels are {193.1,

193.2, 193.3, 193.4} THz and {193.1, 193.3, 193.4, 193.8} THz respectively.

The corresponding results obtained for RZ categories are tabulated in

Tables 3.7, 3.8 and 3.9.

It is found from the Tables 3.6, 3.7, 3.8 and 3.9 that the Q factor for

both ESC and USC schemes decreases in spite of an increase in the channel

power of the system for all the modulation formats. This is due to the

presence of Four wave mixing effect. In general RZ format shows better Q

factor values and hence is more non-linear tolerant. The non-linear tolerant

96

Table 3.6 Q factor measured for various input powers for ESC and

USC schemes under NRZ modulation - 4 channel DWDM

Power in mw 0.25 0.5 0.75 1.0 1.25 1.5

Q factor ( ESC ) 14.04 6.977 4.03 2.853 1.839 1.222

Q factor ( USC ) 16.97 9.553 6.904 4.982 3.079 2.998


USC schemes under RZ modulation - 4 channel DWDM

Power in mw 0.25 0.5 0.75 1.0 1.25 1.5

Q factor ( ESC ) 28.02 12.89 8.99 5.12 3.89 2.44

Q factor ( USC ) 32.24 18.78 13.98 9.88 6.98 6.99


USC schemes under CSRZ modulation - 4 channel DWDM

Power in mw 0.25 0.5 0.75 1.0 1.25 1.5

Q factor ( ESC ) 32.06 16.01 12.98 9.66 7.83 6.89

Q factor ( USC ) 38.27 24.53 16.24 15.45 12.37 12.23


USC schemes under VSB-RZ modulation - 4 channel

DWDM

Power in mw 0.25 0.5 0.75 1.0 1.25 1.5

Q factor ( ESC ) 33.85 17.55 14.56 11.66 9.39 8.222

Q factor ( USC ) 41.97 26.65 18.904 17.982 14.079 14.998

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characteristics is combined with the filtering effect at the transmitter side to

get vestigial side band RZ format which shows good overall performance in

the presence of FWM. Comparing Q factor for ESC and USC schemes under

constant input powers; it is observed that the Q factor values are higher for

USC than ESC irrespective of the modulation format implying that USC

schemes are more FWM tolerant, (Ram prasad and Meenakshi 2006).

Figures 3.25 and 3.26 show the spectrum of the 4 channel ESC and

USC schemes. The strength or the power of the inter modulation FWM cross

talk products falling on the desired channels for both ESC and USC scheme

are shown. It is seen that many cross talk inter modulation products are

present in the desired band of the four channels for ESC and lesser inter

modulation products are present in the desired channel band as cross talk

components for the USC scheme.

Figure 3.25 Output spectrum of four channels in ESC

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Figure 3.26 Output spectrum of four channels in USC

3.5.2 Simulation Results for 16 Channels

The simulation is carried out for 16 DWDM channels with the same

system parameters shown in Tables 3.4 and 3.5 but the data rate is chosen as

40 Gb/s per channel. The results obtained for NRZ, RZ, CS-RZ and VSB-RZ

are tabulated as shown in Tables 3.10, 3.11, 3.12 and 3.13 respectively.


USC Schemes under NRZ modulation - 16 channel DWDM

Power in mw 0.25 0.5 0.75 1.0 1.25 1.5

Q factor ( ESC ) 11.09 4.977 2.03 1.84 1.2 1.0

Q factor ( USC ) 14.34 7.78 4.98 4.45 4.34 3.45

99


USC Schemes under RZ modulation - 16 channel DWDM

Power in mw 0.25 0.5 0.75 1.0 1.25 1.5

Q factor ( ESC ) 26.23 11.45 06.56 3.67 3.78 2.87

Q factor ( USC ) 36.26 16.78 11.57 07.76 04.76 04.56


USC Schemes under CSRZ modulation - 16 channel DWDM

Power in mw 0.25 0.5 0.75 1.0 1.25 1.5

Q factor ( ESC ) 31.67 15.78 11.64 7.546 5.76 4.676

Q factor ( USC ) 36.454 22.656 14.75 13.565 10.75 10.87


USC Schemes under VSB-RZ modulation - 16 channel

DWDM

Power in mw 0.25 0.5 0.75 1.0 1.25 1.5

Q factor ( ESC ) 31.66 15.45 12.77 9.46 7.77 6.74

Q factor ( USC ) 37.45 24.36 16.26 15.47 12.57 12.11

On observing the tabulated values for 16 channel system, it is

observed that the Q factor values for USC are reasonable even at higher

channel powers and is almost double that of ESC schemes. Hence we

conclude that, better suppression of Four wave mixing effect at higher data

rate is achieved by the Unequal Spacing Channel allocation using orthogonal

optical codes. Further, the comparison of Q factor values suggests that a

100

combination of orthogonal code based USC and VSB-RZ formatting can

effectively combat FWM even at higher channel powers. Figures 3.27 and

3.28 show the received Eye diagram for NRZ and RZ coded 16 channel

DWDM system under ESC and USC schemes, respectively. The eye is seen

to be more distinct for RZ under USC compared to that of NRZ under ESC.

Figure 3.27 Measured Q factor and Eye diagram for NRZ under ESC

Figure 3.28 Measured Q factor and Eye diagram for RZ under USC

101

The Q factor performance of PSK formats namely, DPSK, DQPSK

and CSRZ- DQPSK modulations are also investigated at high data rates of 40

Gb/s, in a 16 channel DWDM system for a propagation distance of

600 kms in a NZDSF. Tables 3.14, 3.15 and 3.16 show the output Q factor

measured for DPSK , DQPSK and CSRZ-DPSK modulation formats with

balanced detection using the simulation parameters given in Tables 3.4 and

3.5.


USC Schemes under DPSK - 16 channel DWDM

Power mw 0.25 0.5 0.75 1. 0 1.25

Q (ESC) 27 18 12 10 08

Q( USC) 32 20 14 13 11


USC Schemes under DQPSK - 16 channel DWDM

Power mw 0.25 0.5 0.75 1. 0 1.25

Q (ESC) 29 21 18 15 11

Q( USC) 36 22 17 16 13


USC Schemes under CSRZ DQPSK - 16 channel DWDM

Power mw 0.25 0.5 0.75 1.0 1.25

Q ( ESC) 29 22 18 15 11

Q ( USC) 37 24 18 17 13

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It is found from Table 3.16 that the Q factor for the CSRZ-DQPSK

modulation format shows better values at all power levels. Hence a

combination of OOC based USC with the CSRZ-DQPSK shows better

resistance towards the four wave mixing effect and gives better Q factor

values. It is also inferred that at high powers the performance of DQPSK and

CSRZ-DQPSK are similar and yield the same value of Q factors. Thus these

two modulation formats perform equally well in the presence of non-linear

effects.

3.6 IMPACT OF DISPERSION COMPENSATION ON

MODULATION FORMATS

Dispersion compensation is basically classified as: (a) pre-chirp

techniques at the transmitter side, (b) dispersion compensation in the

transmission line (in-line compensation) and (c) dispersion compensation at

the receiver side, ( Keiser 2000 ).

In pre-chirp, a chirp with the opposite sign of that of the fiber is

introduced at the transmitter for reducing the GVD effects in the fiber.. The

pre-chirp can be realized by several methods, namely by exploiting the

internal chirp of the laser source (Wedding et al 1994) or of an external

modulator (Gnauck et al 1991, Henmi et al 1994), by the implementation of

complex transmitter structures using additional components such as phase

modulators (Khosravani and Willner 2001). The impact of Dispersion slope

for NRZ and DPSK modulation formats at higher bit rate has to be taken into

consideration ( Castanon and Hoshida (2002) . Hayee and Willner (1997)

showed the concept of pre and post compensation of the fiber in the presence

of non linearities and dispersion at the data rate of 10 Gb/s.

103

The main application area of these technique are the cost effective,

optical short-reach systems (e.g. MANs) with smaller channel bit rates, but in

combination with dispersion compensation techniques they can enable a

performance improvement even in high-bit rate transmission systems over

long distances (Sano etal 2000). In-line dispersion compensation is realized in

the optical domain. This is achieved by chirped fiber gratings, using DCF

fibers or phase conjugators. The post-chirp techniques at the receiver side are

characterized by the compensation of the chromatic dispersion in electrical

domain by Maximum Likelihood Detection (Otte and Rosenkranz 2000).

In this section we have estimated the optimal length of dispersion

compensating fibers to be used to realize a high Q factor for various input

power levels. The simulation is done for 16 channels with the data rate of

40 Gb/s per channel propagating over a non-linear dispersive fiber, and the Q

factor is determined for various modulation formats. The performance of the

non-linear fiber is also studied at higher data rate for various modulation

formats towards the improvement of Q factor.

The impact of chromatic dispersion becomes larger with a system

upgrade to higher channel bit rates greater than 10 Gb/s. The performance of

NRZ, RZ and DQPSK modulation formats are analyzed with pre, post and

symmetrical dispersion compensation techniques for a constant SMF length

of 80 kms and a varying length of DCF. One loop in our simulation includes

SMF of fixed length 80 km and EDFA 1 of gain 20 dB, noise figure 4 dB and

the variable length DCF followed by EDFA 2 of 12.6 dB gain. The other fiber

parameters used are listed in Table 3.17. The receiver side of our simulation

has a photo detector with low pass Bessel filter of cut off frequency 0.75

times the bit rate. Table 3.18 lists the Q factors measured for various lengths

of DCF based post compensation for the NRZ, RZ and DQPSK modulation

formats.

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It is observed that the Q factor is maximized for a certain length of

DCF and degrades if the length is increased or decreased from the optimum

value. It is found from Table 3.18 that, the optimum DCF length for best Q-

factor is different for different modulation formats. For example, in the NRZ

format, a maximum Q factor of 13.66 is achieved for a DCF length of 15 kms.

For RZ format the optimum DCF length is 13 kms giving a maximum Q

factor of 15.79 and for DQPSK the optimum DCF length is 12 kms giving a

maximum Q factor of 17.34.

Table 3.17 Fiber parameters used in the simulation for studying the

dispersion compensation schemes

Parameters SMF DCF

Length 80 km Variable

Attenuation 0.2 dB/km 0.25 db/km

GVD 16 ps/nm/km -72 ps/nm/km

Slope 0.08 ps/nm2 0.08 ps/nm2

Effective Area 80 µm2 30 µm2

Table 3.18 Q factor measured at Input power of 2 dBm - Post

compensation using DCF

SMF in km DCF length in km

Q factor (NRZ)

Q factor (RZ)

Q factor (DQPSK)

80 10 12.29 14.59 15.11 80 11 12.98 14.88 15.23 80 12 13.08 15.67 17.34 80 13 12.45 15.79 15.45 80 14 13.27 15.26 16.12 80 15 13.66 14.79 16.33 80 18 12.33 14.23 15.67 80 20 12.00 13.37 15.76 80 22 11.10 13.19 14.35

105

Tables 3.19 and 3.20 list out the Q factors measured under Pre-

compensation and Symmetric compensation by DCF. In the case of

symmetrical compensation, the loop consists of a DCF of variable length,

EDFA 1 of 12.8 db gain with 4 db noise figure , SMF of length 80 kms ,

EDFA 2 of 20 dB gain , SMF of 80 kms, EDFA 3 of 20 dB gain, a DCF of

length 10 kms, and finally EDFA 4 of 12.8 dB.

Table 3.19 Q factor measured at Input power of 2 dBm - Pre-


SMF in km

DC F length in km

Q factor (NRZ)

Q factor (RZ)

Qfactor (DQPSK)

80 10 19.80 21.08 23.08

80 11 21.30 22.29 24.29

80 12 21.09 22.98 27.66

80 13 18.42 24.45 26.66

80 14 17.13 19.27 21.23

80 15 16.04 18.66 21.88

80 18 14.42 15.43 17.34

80 20 14.00 14. 60 16.35

80 22 12.10 14.10 16.11

106

Table 3.20 Q factor measured at Input power of 2 dBm - Symmetrical


SMF in km

DCF length in km

Q factor (NRZ)

Q factor (RZ)

Q factor (DQPSK)

80 10 15.75 18.08 20.08

80 11 18.98 19.29 22.29

80 12 16.34 21.98 24.98

80 13 14.72 16.45 17.45

80 14 13.98 16.27 18.27

80 15 15.69 13.66 15.66

80 18 13.89 12.33 14.33

80 20 12.99 11.00 12.00

80 22 11.08 10.10 13.10

It can be concluded from these investigations that, an optimum

DCF length can give us the best Q factor performance and this optimum

length is also dependent on the modulation format as well as the location of

compensation. Comparing Pre, Post and Symmetrical dispersion

compensation techniques in terms of Q factor realized, it is observed that Pre-

compensation is the best option. It is also noted that the DQPSK modulation

format shows the best Q factor performance. DQPSK with pre-compensation

using DCF of length 12 km gives the highest Q-factor of 27.66.

Figures 3.29, 3.30 and 3.31 show the eye diagram and Q factor for

the NRZ, RZ and DQPSK modulation formats, under different dispersion

compensation techniques.

107

Figure 3.29 Q factor of NRZ under post compensation using DCF

Figure 3.30 Q factor of RZ under pre-compensation using DCF

108

Figure 3.31 Q factor of NRZ under symmetrical compensation using

DCF

3.7 SUMMARY

In this chapter a modulation format has been identified by

investigating its performance under Equally Spaced Channel and Unequally

Spaced Channel schemes for DWDM systems. Unequally Spaced Channel

assignment is studied using optical orthogonal coding technique. In addition,

the impact of filtering techniques, modulation formats and dispersion

compensating techniques in combating the linear and non-linear fiber

impairments are also analyzed in terms of Q factor and Eye Opening Penalty

to identify methods for improving the spectral efficiency.

The right choice of the optical filter used for transmitter and

receiver side is crucial especially in a system requiring more spectral

109

efficiency. The Q factor measured at the receiver output for various pre-

transmission filters like Bragg Grating, Gaussian, Super Gaussian and Fabry

Perot Filters shows a reduction in Q factor for increasing distances indicating

the necessity for a dispersion management technique. Super Gaussian filter of

higher order, is observed to give the highest Q factor with Bragg grating Filter

showing a closer performance.

In terms of Q factor and EOP measurements, it is concluded that

RZ based formats are more non-linear tolerant. In addition it is also concluded

that under constant input powers the Q factor values are higher for USC

scheme than the ESC scheme, irrespective of the modulation format. This is a

significant inference implying that USC schemes are more FWM tolerant.

Further, the comparison of Q factor values suggests that a combination of

orthogonal code based USC and CSRZ-DQPSK formatting can effectively

combat FWM even at higher channel powers. The Q-factor comparison of

PSK based formats namely DPSK, DQPSK and CSRZ-DQPSK suggests that

DQPSK and CSRZ-DQPSK have similar performance and are better FWM

tolerant.

The performances of the dispersion compensation schemes like

post, pre and symmetrical compensation techniques are observed to be

dependent on the modulation format as well as the DCF length. It can be

concluded from our investigations that, an optimum DCF length can give us

the best Q factor performance and this optimum length is also dependent on

the modulation format as well as the location of compensation. Comparing

Pre, Post and Symmetrical dispersion compensation techniques in terms of Q

factor realized, for different modulation formats it is concluded that DQPSK

modulation format with pre-compensation using optimum DCF length is the

best option.