Nonlinear equalization method based on Gaussian mixture model clustering algorithm for a coherent optical OFDM communication system

In this paper, an unsupervised clustering algorithm based on the Gaussian Mixture Model (UCGMM algorithm) for the coherent optical OFDM communication system is proposed to determine the constellation diagram. The purpose of nonlinear equalization of communication systems is achieved. In a back to back transmission system, compared to the Kmeans algorithm and the without any clustering algorithm, the UCGMM algorithm can obtain gains of approximately 0.6dB and 2dB respectively. For the cases of simulation in optical fiber transmission, the transmission distance of UCGMM algorithm is extended by 45km relative to the K-means algorithm, and 75km relative to without any clustering algorithm. In both cases, the effectiveness of the proposed UCGMM algorithm in nonlinear equilibrium is proved.

[1]  Mingyi Gao,et al.  K-means-clustering-based fiber nonlinearity equalization techniques for 64-QAM coherent optical communication system. , 2017, Optics express.

[2]  Yi Lin,et al.  Harnessing machine learning for fiber-induced nonlinearity mitigation in long-haul coherent optical OFDM , 2019, Future Internet.

[3]  Marc Wuilpart,et al.  Fiber Nonlinearity Equalizer Based on Support Vector Classification for Coherent Optical OFDM , 2016, IEEE Photonics Journal.

[4]  白光富 Bai Guangfu,et al.  Nonlinearity analysis and signal distortion cancelation in IMDD OFDM PON , 2018 .

[5]  J. Kahn,et al.  Compensation of Dispersion and Nonlinear Impairments Using Digital Backpropagation , 2008, Journal of Lightwave Technology.

[6]  Elias Giacoumidis,et al.  Blind Nonlinearity Equalization by Machine-Learning-Based Clustering for Single- and Multichannel Coherent Optical OFDM , 2018, Journal of Lightwave Technology.

[7]  Elias Giacoumidis,et al.  A Blind Nonlinearity Compensator Using DBSCAN Clustering for Coherent Optical Transmission Systems , 2019 .

[8]  Qi Zhang,et al.  Robust weighted K-means clustering algorithm for a probabilistic-shaped 64QAM coherent optical communication system. , 2019, Optics express.

[9]  Darko Zibar,et al.  Machine Learning Techniques in Optical Communication , 2015, Journal of Lightwave Technology.

[10]  Xiangjun Xin,et al.  Mixture-of-Gaussian clustering-based decision technique for a coherent optical communication system. , 2019, Applied optics.