Abstract
We propose and analyze a classifier based on logistic regression (LR) to mitigate the impact of nonlinear phase noise (NPN) caused by Kerr-induced self-phase-modulation in digital coherent systems with single-channel unrepeated links. Simulation results reveal that the proposed approach reduces the bit error ratio (BER) in a 100-km-long 16 quadrature amplitude modulation (16-QAM) system operating at 56-Gbps. Thus, the BER is reduced from 6.88 × 10−4 when using maximum likelihood to 4.27 × 10−4 after applying the LR-based classification, representing an increase of 0.36 dB in the effective Q-factor. This performance enhancement is achieved with only 624 operations per symbol, which can be easily parallelized into 16 lines of 39 operations.
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Funding
The authors thank the National Council for Scientific and Technological Development (CNPq, Grant Numbers 432303/2018-9 and 311035/2018-3) and the São Paulo Research Foundation (FAPESP, Grant Numbers 2015/24517-8 and 2018/25339-4).
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de Paula, R.A., Marim, L., Penchel, R.A. et al. Mitigation of nonlinear phase noise in single-channel coherent 16-QAM systems employing logistic regression. Opt Quant Electron 53, 508 (2021). https://doi.org/10.1007/s11082-021-03149-7
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DOI: https://doi.org/10.1007/s11082-021-03149-7