Chapter  4

Chapter  4  

4 Impairment   monitoring   technique   applied   to   a   real  

transmission  system.    

In this chapter we apply the monitoring technique to a more realistic scenario involving signal transmission over an optical link with single mode fiber (SMF), dispersion compensation fiber (DCF), and optical amplification. We will use the OOK, QPSK and 16-QAM modulation formats for the LS and the optimum design parameters chosen in previous chapters; we will show the simulation results with three channels implementing a WDM system. First, we will test our technique with fiber transmission system linear impairments (i.e. optical noise and in-band crosstalk). Second, we will test the proposed monitoring technique in the presence of non-linear effects.

4.1 Simulation  Setup  

The simulation setup is shown in Figure 4.1:

• Single Mode Fiber: this module solves the nonlinear Schroedinger (NLS) equation describing the propagation of linearly-polarized optical waves in fibers using the split-step Fourier method. The model takes into account Stimulated Raman Scattering (SRS), Four-Wave Mixing (FWM), Self-Phase Modulation (SPM), Cross-Phase Modulation (XPM), first order Group-Velocity Dispersion (GVD), second order GVD and attenuation of the fiber. This is one of the simplest VPI fiber models in the range. It is the basis of many fiber simulations. However, more complex fiber models are provided to offer more flexibility in terms of input data format, interactions between signal representations, bidirectional Raman amplification, dispersion decreasing fiber, polarization mode dispersion, fast simulation of jitter in RZ systems, and simulation with aperiodic waveforms. The second fiber model (DCF) is using for the Dispersion Fiber Compensation; setting the fiber parameters based on the fiber data sheet shown in Appendix D, we can compensate the dispersion introduced by the first fiber module (SMF).

• Loop: this module can be used to construct loop structures, which can be initialized with optical input signals. The loop structure to be built starts at the loop output port and terminates at he loop input port of the module. A signal released into the loop via the input port will circulate a certain number of times through the ring, as specified via the Loops Parameter, and be released afterwards at the output port. This module serves to initialize the loop with external data to be supplied at the input port of the module.

• Amplifier Model: This is an Amplifier model with fixed gain shape for system simulations. The model can act as a gain-controlled, power-controlled, or saturable amplifier. Limiting effects related to high output power or high gain are taken into account. The model is

also valid for low gain and even attenuating amplifiers. This system-level amplifier module consists of an ideal amplifying unit characterized by a frequency- and wavelength-dependent gain G according to

(4.1) It runs in four different modes referring to the amplification behavior. These modes can be selected via the AmplifierType parameter; in our simulation we set

. In GainControlled mode (Figure 4.2) the pump power is variable and the parameter GainShapeDescription allows you to specify the input signal amplification via parameters or gain profile.

Figure 4.2 System-level amplifier

The port to port gain of the amplifier, G, is defined differently for low and high input powers:

Ø At low input powers, the amplifier provides a power-independent gain, equal to a specified Small-Signal Gain, . The Small-Signal Gain is either specified as a frequency-independent constant (Gain) or as frequency-dependent parameters (Gain, GainTilt and GainTiltRefFreq) or as a file (GainShapeFilename). The parameter GainTilt is used for gain calculation via the following equation:

(4.2) E_out = Ein,x E_in,y ⎛ ⎝ ⎜ ⎞ ⎠ ⎟ G f

( )

(

)

Where is the rate of the gain change with frequency, defined by the GainTilt parameter, ftiltref is the reference frequency of the tilt,

GainTilt=0 defined by the GainTiltRefFreq parameter. The gain profile is

flat if.

Ø At high input powers, the amplifier’s output power (averaged over one Block) will be limited, as in a real device, by setting a maximum output

power, , set by the parameter . This limiting is

achieved by scaling the port to port gain, , below the small signal gain,

so that in linear units , where is the ratio of the

unscaled output power to the desired output power . This

power limiting is useful in providing realistic simulations. If the gain is set to an unrealistically high value, the output will always equal the power

limit. The maximum output power ( ) relates to the sum of

powers of all signals in all channels, and is controlled by enhanced parameters SampledSignals, ParametrizedSignals, NoiseBins, Distortions (Figure 4.3).

Figure 4.3 Transfer characteristic of the amplifier

GainTilt Pout(max) OutputPowerMax G f

( )

( )

( )

Additionally, the amplifier corrupts the output signal by Amplified Spontaneous Emission (ASE) noise. The resulting (NF) is defined (as in all electronic systems usual, too) by the quotient of the Signal-to-Noise-Ratio (SNR) at the input divided by the output SNR measured by an ideal, shot-noise limited photodiode:

(4.3) The SNRs are measured in the electrical domain and refer to an ideal photodetector, which converts each incoming photon into one electron. According to the quantum mechanical treatment in the Noise Figure is (in a quantum-beat-noise-limited formula) given by

(4.4) Equation (4.4) is only valid for:

i. A coherent light source;

ii. Single-mode propagation including two polarization modes, and

iii. An input high enough such that ASE-ASE-beat and ASE-shot noise can be neglected.

In a semi classical description, the sum in Equation (4.4) is the beat of the signal and the ASE noise. The second term originates from the normalized signal shot noise. The symbol N is usually interpreted as the mean photon number of the amplified spontaneous emission in each polarization mode. The physically minimum Noise Figure, , can be derived for a positive amplification, given

that : (4.5) Eout NoiseFigure NF = 10log SNRin SNR_out NF = 10log 2n_sp⋅G−1 G + 1 G ⎡ ⎣⎢ ⎤ ⎦⎥= 10log 1+ 2N G NFmin nsp ≥ 1 NF > NFmin = −10log 2 −1 G

(

)

The minimum value can be below , such as in low-gain amplifiers. For high gain amplifiers ( ) the noise figure is above , commonly referred to as the quantum limit. Consequently, SNR degradation below the quantum limit is possible, but at the expense of amplifier gain. For amplifiers with net attenuation the minimum Noise Figure is

(4.6) Which again arises from the shot noise process in the photodiode. From Equation (4.4) it results for the (one-sided) ASE noise spectral density

(4.7) Where is Planck’s constant and denotes the optical frequency, Gain and Noise Figure are specified in . The amplified spontaneous emission is modeled by a Gaussian distributed noise added independently to both polarization components, the amplified optical field components and . Its degree of polarization is zero. The ASE noise is added to the output signal inside the spectral range Noise Bandwidth.

NFmin 3dB G ≫ 1 3dB NF > NFmin = −10logG dP_ASE,x df = dP_ASE,y df = N ⋅ hf = 10NF 10_G−1

(

)

4.2 Simulation  Results  

In this section we show the simulation results, first for the Linear Impairments Scenario and then in the presence of nonlinearities. From the previous sections we obtained the followings outcomes: LS Code LS Symbol Rate Monitor Signal Bit Rate Extinction Ratio Value LS Modulation Formats OOK 8B/10B&9B/10B 10Gb/s 20Mb/s 0.4 dB QPSK Not Necessary 10GBd 20Mb/s 0.4 dB 16-QAM 8B/10B 10GBd 2Mb/s 0.15 dB

Table 4.1 Simulation Parameters

The simulations are made only for the above optimum combinations of the design parameters because now the simulation time is much longer than the previous due to the introduction of the fiber. Note that we used an SMF fiber 100 km-long and we simulated 10 loops to be sure that the linear and non-linear impairments occur.

4.2.1 Linear  Impairments  Simulation  Results  

This section shows the simulations results for the scenarios shown in Errore. L'origine

riferimento non è stata trovata., for Linear Inband Crosstalk and OSNR impairments.

4.2.1.1 OSNR  Impairments  Monitoring    

Errore. L'origine riferimento non è stata trovata. and Errore. L'origine riferimento non è stata trovata. show the LS and MS (MS) Bit-Error-Rate curves, when we

consider a LS with OOK modulation and a bit rate equal to 10Gb/s, a MS bit rate equal to 20Mb/s and a Extinction Ratio of the Mach-Zehnder Modulator equal to 0.4dB. From those figures we can conclude that the Impairments Monitoring Technique works well in this scenario. Therefore we can tap some optical power at the node of a network and through detection and BER estimation we can verify if the link is still in good condition

or not: if the BER of MS is in a range of acceptable values we can assume that the OSNR of the link is high enough for the correct detection of the LS; otherwise we have to take some countermeasures for contrast the degradation of the link (i.e. change modulation format or increase the Transmitter Launch Power).

Figure 4.6 shows the relation between the BER of LS and the BER of MS: from this curve we can go obtain the value of the BER of LS, once calculated the BER of the MS. As this figure shows, if the degradation of MS is about two decades, the LS suffers a degradation of about the same value.

Figure 4.4 BER of OOK LS when varying a) the OSNR and b) number of loops. The OOK LS is simulated with a 8B/10B coded sequence at 10GBd, the MS bit rate is equal to 20Mb/s and the ER=0.4 dB.

Figure 4.5 BER of MS when varying a) the OSNR and b) number of loops. The OOK LS is simulated with a 8B/10B coded sequence at 10GBd, the MS bit rate is equal to 20Mb/s and the ER=0.4 dB.

Figure 4.6 Relation between the BER of the MS and BER of the LS.

In the following we show the results when we consider a LS with QPSK modulation and a symbol rate equal to 10GBd, a MS bit rate equal to 20Mb/s and a Mach-Zehnder Modulator Extinction Ratio equal to 0.4 dB. Figure 4.7 and Figure 4.8 show the LS and MS Bit-Error-Rate curves.

Figure 4.7 BER of QPSK LS when varying a) the OSNR and b) number of loops. The QPSK LS is simulated with a uncoded PRBS (N=17) at 10GBd, the MS bit rate is equal to 20Mb/s and the ER=0.4 dB.

Figure 4.8 BER of MS when varying a)the OSNR and b) number of loops. The QPSK LS is simulated with an uncoded PRBS (N=17) at 10GBd, the MS bit rate is equal to 20Mb/s and the ER=0.4 dB.

The relation between the BER of LS and the BER of SS is shown in Figure 4.9.

b) a)

b) a)

Figure 4.9 Relation between the BER of the MS and BER of the LS.

Finally we show the simulation results (Figure 4.10, Figure 4.11, Figure 4.12) when we consider the LS with 16-QAM modulation, a MS bit-rate equal to 2 Mb/s and an ER=0.15 dB.

Figure 4.10 BER of QAM LS (@10GBd) when varying a) the OSNR and b) number of loops. Both components of 16-QAM LS are simulated with a 8B/10B code sequence; the MS bit rate is equal to 2Mb/s and the ER=0.15 dB.

b) a)

Figure 4.11 BER of MS when varying a)the OSNR and b) number of loops. Both components of 16-QAM LS (@10GBd) are simulated with a 8B/10B code sequence; the MS bit rate is equal to 2Mb/s and the ER=0.15 dB.

Figure 4.12 Relation between the BER of the MS and BER of the LS.

4.2.1.2 Inband  Crosstalk  Monitoring  

In this section we study whether it is possible use the Impairments Monitoring Technique to understand whether the LS is affected from the Linear Inband Crosstalk. In order to simulate this kind of impairment, we set the Laser Emission Frequency of the LS on Channel 1 (Figure 4.1) equal to the Laser Emission Frequency of the LS on Channel

2. Then by means of an attenuator placed at the output of the Mach-Zehnder Modulator on Channel 1, we decrease the optical power of this channel representing the Crosstalk Signal.

When we consider an 8B/10B coded Line Signal, with OOK modulation, we obtain the results shown in Figure 4.13 and Figure 4.14

Figure 4.13 BER of LS and MS on Channel 2, when we consider the Overmodulated Signals on Channel 1 and Channel 3 the Inband Crosstalk Signals. The LS on Channel 1 is OOK modulated with a 8B/10B coded sequence at 10Gbit/s; the MS on Channel 2 is as usual at 20Mb/s (OOK); the ER=0.4 dB.

When the LS is coded with an 9B/10B code, the simulation results are:

Figure 4.15 BER of LS and MS on Channel 2, when we consider the Overmodulated Signals on Channel 1 and Channel 3 the Inband Crosstalk Signals. The LS on Channel 1 is OOK modulated with a 9B/10B coded sequence at 10Gbit/s; the MS on Channel 2 is as usual at 20Mb/s (OOK); the ER=0.4 dB.

4.2.2 Nonlinear  Impairments  Simulation  Results  

The goal of the simulations shown in this section is to figure out if it is possible to use the Impairments Monitoring Technique for detecting the presence of Nonlinear impairments on the LS. In particular, in this section we will show only the results related to Four Wave Mixing (FWM). In fact, we tried to apply our technique in the case of two other common nonlinear transmission impairments as Self-Phase Modulation and Cross-Phase Modulation, (discussed in Chapter 1), but the conclusion is that those kind of impairments cannot be sensed using our monitoring technique. Therefore, this section we study and simulate only the FWM caused from Channel 1 and Channel 3 on the desired channel (Ch 2).

As usual, at the beginning we consider the LS with OOK modulation and then the other modulation formats (QPSK and 16-QAM) for the scenario shown in Errore. L'origine

riferimento non è stata trovata..

In order to detect the presence of this kind of phenomena on the Line Signal by using the Monitor Signal, we gradually increase the Launch Power of the three channels. Setting the receiver on the Channel 2 and increasing the launch power of Channel 1 and Channel 3, Channel 2 is affected by FWM: new unwanted frequencies components arise in the spectrum of the desired LS bringing theBER of the LS above unacceptable levels. As the launch power increases, the Monitor Signal shows the same trend, making it possible to use the MS to understand if the LS is in good condition or not.

4.2.2.1 OOK  Case  

Figure 4.17 and Figure 4.18 show the simulation results when we consider the Line Signal (@10 Gb/s) with OOK modulation format, using a 8B/10B; the Monitor Signal bit-rate is equal to 20 Mb/s and the Extinction Ratio of the Mach Zehnder modulator is equal to 0.4 dB.

Figure 4.17 Four Wave Mixing on the Desired Channel (CH 2), when the Line Signal (@10Gb/s) is modulated with an OOK, varying the Launch Power.

Figure 4.18 Relation between the BER of the MS and BER of the LS.for Channel 2.

Similar results are obtained when 9B/10B code is used.

4.2.2.2 QPSK  Case  

Figure 4.19 and Figure 4.20 show the simulation results when we consider a LS with a QPSK modulation with a baud-rate equal to 10 GBd; for the MS, the settings are the same used for the previous OOK case.

Figure 4.19 Four Wave Mixing on the Desired Channel (CH 2), when the Line Signal (@10Gb/s) is modulated with an QPSK, varying the Launch Power.

Figure 4.20 Relation between the BER of the MS and BER of the LS.for Channel 2.

4.2.2.3 16-­‐QAM  Case  

Finally in the case of 16-QAM modulation format we obtain the results shown in Figure 4.21 and Figure 4.22.

Figure 4.21 Four Wave Mixing on the Desired Channel (CH 2), when the Line Signal (@10Gb/s) is modulated with an 16-QAM, varying the Launch Power.

4.3 Conclusions  

Based on the preliminary study presented in Chapter 2 and Chapter 3, we applied the proposed monitoring technique to a real fiber optic transmission system with linear and non-linear impairments. From the results obtained in this chapter, we can affirm that the use of the Impairments Monitoring Technique based on Overmodulation allows to detect Linear Impairments like OSNR degradation and Inband Crosstalk and non-linear impairments such as FWM, when the design parameters of the system are set like shown in Table 4.1

The next chapter, which will conclude this thesis work, will present experimental verification for some of the results obtained in the previous chapters. Note that, the parameters in Table 4.1 and the results obtained so far have been generated through simulations. In a real scenario, those parameters and results might differ due to non-ideal conditions dictated by the hardware available or just differences between the experimental and simulative conditions. So, it is reasonable to expect some differences between the experimental and simulation results, but what matters is to verify the effectiveness of the proposed scheme in a real experimental scenario.