Lightwave Technology

Chapter 9.6.2 - Dispersion Fluctuations

9.6.2 Dispersion Fluctuations

So far we have treated the dispersion of all fiber sections used to form a dispersion-managed fiber link as being uniform along the section length. We have also assumed that dispersion does not change with time. Both these assumptions are questionable for realistic fibers. The zero-dispersion wavelength λ0 of a fiber depends on its core diameter, which can vary along the fiber length by a small amount (a few percent) in a random fashion during the fiber-pulling stage. Any variations in λ0 manifest as changes in the value of the dispersion parameter D(λ) at the channel wavelength. Although such dispersion variations are static in nature, they can affect system performance whenever nonlinear effects are not negligible along the link. For this reason, dispersion fluctuations have attracted the most attention in the context of solitons [151]-[153].

A second source of dispersion fluctuations is related to environmental changes. If the temperature of the fiber changes at a given location, the local dispersion would also change with it because D also depends on temperature [154]-[156]. Such dynamic fluctuations are of considerable concern for 40-Gb/s channels for which dispersion tolerance is relatively tight. In a simple model, D is assumed to vary with λ as

09_06_02_Lightwave_Technology-1.jpg

where S0 is the dispersion slope at the zero-dispersion wavelength λ0. Both S0 and λ0 vary along the fiber length and with temperature. Such variations affect system performance because the BER or the Q factor is sensitive to the distribution of dispersion along the link length. In the case of a linear system, their impact can be completely eliminated by employing a dynamic dispersion-compensation scheme (see Section 7.7.1). However, such a scheme does not work perfectly when nonlinear effects play a significant role.

To study the impact of dispersion fluctuations on the performance of a WDM channel operating at 40 Gb/s, the NLS equation is solved numerically, while including both the amplitude and phase fluctuations induced by the noise added by amplifiers. Dispersion fluctuations are included by writing the local dispersion parameter as

09_06_02_Lightwave_Technology-2.jpg

where 2 is the average value of local dispersion and δβ2is a random variable assumed to have a Gaussian distribution with zero mean and standard deviation σD. Every realization of the Gaussian process represents a different fiber link. Since time-dependent dispersion fluctuations related to temperature variations occur on a relatively long time scale, the Q factor can be calculated for each realization, but it changes in a random fashion for different realizations of dispersion distribution along the fiber link. Such changes in Q reflect the situation that the BER of a WDM channel can change during a day because of temperature-induced changes in fiber dispersion.

Figure 9.31 shows how Q changes with distance for 15 different realizations of the random variable δβ characterized by a standard deviation of σD= 0.4 ps2/km [153]. In these simulations, the dispersion map consisted of two fiber sections of nearly equal lengths (5 km) with 2 = ± 8 ps2/km. The average dispersion of the link was set at -0.01 ps2/km. Link losses were compensated every 80 km through distributed Raman amplification. The RZ bit stream employed 6-ps Gaussian input pulses with a chirp parameter of 0.3 and a peak power of 2 mW, a value that was below the formation of dispersion-managed solitons. Figure 9.31 shows that Q can vary over a considerable range because of dispersion fluctuations. The worst case corresponds to the lowest value of Q.

09_06_02_Lightwave_Technology-3.jpg

Figure 9.31: Q factor as a function of distance for 15 realizations of dispersion fluctuations for a 40-Gb/s channel. The inset shows Q values expected in the absence of dispersion fluctuations. The input peak power of 6-ps pulses was 2 mW. (After Ref. [153]; ©2003 IEEE.)


Figure 9.32 shows for several different values of σD how the worst-case Q factor changes with input peak power after 2,400 km. In the absence of dispersion fluctuations, the peak value of Q ≈ 9.5 around 2 mW is large enough that the system can operate without FEC coding. However, the peak shifts toward lower values of peak powers, and its height is reduced considerably, in the presence of dispersion fluctuations. For σD = 0.8 ps2/km, a value that corresponds to a fluctuation level of 10%, Q is around 5 at an input peak power of 1 mW. Such a system cannot operate reliably without FEC. These results illustrate that dispersion fluctuations, if left uncontrolled, can be detrimental to a lightwave system.

09_06_02_Lightwave_Technology-4.jpg

Figure 9.32: Worst-case Q factor for a 40-Gb/s channel at a distance of 2,400 km as a function of input peak power for three values of σD. (After Ref. [153]; ©2003 IEEE.)

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