Dual-Stage Soft Failure Detection and Identification for Low-Margin Elastic Optical Network by Exploiting Digital Spectrum Information

Supported by advanced digital signal processing algorithms and application specific integrated circuits, coherent receivers in elastic optical networks will be capable of measuring link impairments in real time. Specifically, coherent receivers can work as soft optical performance monitors. Optical spectra usually contain rich information about optical links and have been exploited to assist soft failure detection and identification. However, acquiring optical spectra needs the deployment of numerous optical spectrum analyzers. Instead, the digital spectra of received signals in coherent receivers are easy to obtain without the penalty of additional hardware. In this paper, we explore the feasibility of the digital spectra in assisting soft-failure detection (SFD) and soft failure identification (SFI). A digital spectrum based SFD and SFI framework is proposed. A dual-stage SFD structure is employed to reduce the monitoring and processing overhead in optical nodes. At the first-stage SFD, only bit error rate and received optical power are collected. When an anomalous sample is detected, extra digital spectrum features are extracted and collected for the second-stage SFD. Extensive numerical results are presented to analyze the digital spectrum characteristics and feature distributions of four common soft failures. Finally, we experimentally evaluate the detection and identification performance of the proposed method. With reasonable complexity, a false positive rate of 0.42% and a false negative rate of 1.47% can be achieved for SFD, and an identification accuracy of 99.55% can be obtained for SFI.