Image Processing Reference
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the NLCP optimization reveals less importance and it is already sufficient to calculate the
non-linearity at the end of each step if logarithmic step sizes are used. On the other hand, at
higher launch powers, EVM increases and the saturation of EVM reduction happens toward
larger number of steps. Note that with 9dBm launch power, the EVM cannot reach values
below 0.15 (BER=10 3 ) even if a large number of steps per span is applied.
Fig. 10. EVM of all SSFM algorithms with varying number of steps per span for (a) 3dBm, (b)
6dBm and (c) 9dBm.
Fig. 11(a) shows the required number of steps per span to reach BER=10 3 at various launch
powers for different SSFM algorithms. It is obvious that more steps are required for higher
launch powers. Using logarithmic distribution of step sizes requires less steps to reach a
certain BER than using uniform distribution of step sizes. At a launch power of 3dBm, the
use of logarithmic step sizes reduces 50% in number of steps per span with respect to using
the A-SSFM scheme with constant step sizes, and 33% in number of steps per span with
respect to using the S-SSFM and M-SSFM schemes with constant step sizes. The advantage
can be achieved because the calculated non-linear phase remains constant in every step along
the complete. Fig. 11(b) shows an example of logarithmic step-size distribution using 8
steps per span. The non-linear step size determined by effective length of each step, L eff ,
is represented as solid-square symbols and the average power in corresponding steps is
represented as circle symbols. Uniformly-distributed non-linear phase for all successive steps
can be verified by multiplication of L eff and average power in each step resulting in a constant
value.
γ DBP was optimized
to obtain the best performance. Fig. 12 shows constellation diagrams of received 16-QAM
signals at 3dBm compensated by DBP with 2 steps per span. The upper diagrams show the
results of using constant step sizes with non-optimized
Throughout all simulations the non-linear coefficient for DBP
γ DBP (Fig. 12(a)), and with optimized
γ DBP (Fig. 12(b)). The lower diagrams show the results of using logarithmic step sizes with
 
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