Nonlinear inverse synthesis technique for optical links with lumped amplification

ST Le, JE Prilepsky, SK Turitsyn - Optics express, 2015 - opg.optica.org
Optics express, 2015opg.optica.org
The nonlinear inverse synthesis (NIS) method, in which information is encoded directly onto
the continuous part of the nonlinear signal spectrum, has been proposed recently as a
promising digital signal processing technique for combating fiber nonlinearity impairments.
However, because the NIS method is based on the integrability property of the lossless
nonlinear Schrödinger equation, the original approach can only be applied directly to optical
links with ideal distributed Raman amplification. In this paper, we propose and assess a …
The nonlinear inverse synthesis (NIS) method, in which information is encoded directly onto the continuous part of the nonlinear signal spectrum, has been proposed recently as a promising digital signal processing technique for combating fiber nonlinearity impairments. However, because the NIS method is based on the integrability property of the lossless nonlinear Schrödinger equation, the original approach can only be applied directly to optical links with ideal distributed Raman amplification. In this paper, we propose and assess a modified scheme of the NIS method, which can be used effectively in standard optical links with lumped amplifiers, such as, erbium-doped fiber amplifiers (EDFAs). The proposed scheme takes into account the average effect of the fiber loss to obtain an integrable model (lossless path-averaged model) to which the NIS technique is applicable. We found that the error between lossless path-averaged and lossy models increases linearly with transmission distance and input power (measured in dB). We numerically demonstrate the feasibility of the proposed NIS scheme in a burst mode with orthogonal frequency division multiplexing (OFDM) transmission scheme with advanced modulation formats (e.g., QPSK, 16QAM, and 64QAM), showing a performance improvement up to 3.5 dB; these results are comparable to those achievable with multi-step per span digital back-propagation.
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