CHAPTER 3 PERFORMANCE OF MODULATION FORMATS ON DWDM...

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67 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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    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 m2 30 m2

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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 its 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 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

    f3db 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 its 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 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

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    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)

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    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, /2, , 3/2}.

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

    phase, , 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

    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

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    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

    Table 3.7 Q factor measured for various input powers for ESC and

    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

    Table 3.8 Q factor measured for various input powers for ESC and

    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

    Table 3.9 Q factor measured for various input powers for ESC and

    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.

    Table 3.10 Q factor measured for various input powers for ESC and

    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

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    Table 3.11 Q factor measured for various input powers for ESC and

    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

    Table 3.12 Q factor measured for various input powers for ESC and

    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

    Table 3.13 Q factor measured for various input powers for ESC and

    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

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    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.

    Table 3.14 Q factor measured for various input powers for ESC and

    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

    Table 3.15 Q factor measured for various input powers for ESC and

    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

    Table 3.16 Q factor measured for various input powers for ESC and

    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.

  • 104

    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 m2 30 m2

    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-

    compensation using DCF

    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

    compensation using DCF

    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.