Blind Density-Peak-Based Modulation Format Identification for Elastic Optical Networks

Abstract

Optical modulation format identification is critical in the next generation of heterogeneous and reconfigurable optical networks. Here, we present a blind modulation format identification method by applying fast density-peak-based pattern recognition in the autonomous receiver of elastic optical networks. In this paper, we find that the different modulation format types show different energy level features which can be used as a metric to identify these modulation formats in two-dimensional Stokes plane. The proposed method does not require training symbols, and is insensitive to carrier phase noise, frequency offset as well as polarization mixing. The effectiveness is verified via numerical simulations and experiments with PDM-BPSK, PDM-QPSK, PDM-8PSK, PDM-16PSK, PDM-8QAM, and PDM-16QAM. The results show that high identification accuracy can be realized using our proposed method over wide optical signal-to-noise ratio ranges. Meanwhile, we also discuss the influence of the residual chromatic dispersion, polarization mode dispersion, and polarization dependent loss impairments to our proposed method. We believe that the simple and flexible identification method would certainly bring a great convenience to the future optical networks.