Modulation format-independent optical performance monitoring technique insensitive to chromatic dispersion and polarization mode dispersion using a multi-task artificial neural network.

Abstract

We propose and experimentally demonstrate modulation format-independent optical performance monitoring (OPM) based on a multi-task artificial neural network (MT-ANN). Optical power measurements at a series of center wavelengths adjusted using a widely tunable optical bandpass filter (OBPF) are used as the input features for a MT-ANN to simultaneously realize high-precision optical signal-to-noise ratio (OSNR) and launch power monitoring and baud rate identification (BRI). This technique is insensitive to chromatic dispersion (CD) and polarization mode dispersion (PMD). The experimental verification in a 9-channel WDM system shows that for 10 Gbaud QPSK and 32 Gbaud PDM-16QAM signals with OSNR in the range of 1-30 dB, the OSNR mean absolute error (MAE) and root mean square error (RMSE) are 0.28 dB and 0.48 dB, respectively. For launch power in the range of 0-8 dBm, the MAE and RMSE of the launch power monitoring are 0.034 dB and 0.066 dB, respectively, and the identification accuracy for both baud rates is 100%. Furthermore, this technique utilizes a single MT-ANN instead of three ANNs to realize the simultaneous monitoring of three OPM parameters, which greatly reduces the cost and complexity.