ORT image and IMT-MIMO-ResNet-based multi-mode multi-parameter joint optical performance monitoring in MDM-EON systems

This paper presents a novel joint optical performance monitoring (OPM) scheme for multiple spatial modes in mode division multiplexing elastic optical network (MDM-EON) systems, which integrates the optimal Radon transform (ORT) image with the improved multi-task multi-input multi-output residual neural network (IMT-MIMO-ResNet) model. The ORT images effectively enhance the differentiation among various parameters across different spatial modes. Additionally, based on the output characteristics and intrinsic correlations among spatial modes of the MDM-EON system, we design the IMT-MIMO-ResNet model. The proposed scheme overcomes the limitations of existing approaches, where a single OPM device can monitor only one spatial mode. It enables simultaneous monitoring of bit rates (BRs), modulation formats (MFs), mode coupling (MC) intensities, and optical signal-to-noise ratio (OSNR) values for each MF across five spatial modes. Moreover, the scheme demonstrates favorable robustness under conditions with large chromatic dispersion, large differential group delay, and strong fiber nonlinear effects. Both simulation and experimental results show that the accuracy of baud rate identification (BRI) and modulation format identification (MFI) for each spatial mode reaches 100%, and the average mean absolute errors (MAEs) for OSNR values and MC intensities corresponding to each MF are below 0.4 dB and 0.010, respectively. The computational complexity of the proposed scheme, evaluated using floating-point operations (FLOPs) and parameters (Params), is approximately 1/7 of that required by a typical OPM scheme.