Mitigation of nonlinear phase noise in single-channel coherent 16-QAM systems employing logistic regression

• Published in: Optical and quantum electronics Vol. 53; no. 9
• Main Authors: de Paula, Rômulo A., Marim, Lucas, Penchel, Rafael A., Bustamante, Yésica R. R., Abbade, Marcelo L. F., Perez-Sanchez, Grethell, Aldaya, Ivan
• Format: Journal Article
• Language: English
• Published: New York Springer US 01-09-2021; Springer Nature B.V
• Subjects: Characterization and Evaluation of Materials; Computer Communication Networks; Electrical Engineering; Lasers; Optical Devices; Optics; Phase noise; Photonics; Physics; Physics and Astronomy; Quadrature amplitude modulation; Coherent systems; Nonlinearity compensation; Machine learning
• ISSN: 0306-8919; 1572-817X
• DOI: 10.1007/s11082-021-03149-7

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.