Abstract
In an elastic network paradigm, where the transceiver is able to control several characteristics of the transmitted signal according to the optical link quality and capacity demand, receivers able to automatically detect the modulation format are fundamental to recover the transmitted signal without the necessity of headers that reduce system capacity. This work presents a simulated performance comparison of six methods for blind identification of modulation format in high-capacity optical systems: k-nearest neighbors (KNN), k-means, fuzzy c-means, deep neural networks, support-vector machine (SVM) and peak-to-average power ratio (PAPR). The transmitted channels were 64-GBd modulated with the following modulation formats available at the transceiver: QPSK, 16QAM, 64QAM, and 256QAM. The optical link was emulated considering several impairments, as amplified spontaneous emission from optical amplifiers, frequency and phase noise from lasers, and polarization rotation and differential group delay from the propagation. The support-vector machine algorithm presented the most robust results.
Highlights
Optical networks are a key technology to support the global telecommunications backbone, especially with the rising and large acceptance of on-demand high-quality video distribution, cloud computing, and Internet of Things (IoT) applications
The accuracy for each modulation format identification (MFI) approach as a function of the received signal optical signal-to-noise ratio (OSNR) is presented in Fig. 3, on which the signals were degraded only by the insertion of amplified spontaneous emission (ASE) emulated by loading AWG noise
The training sequences were obtained from signals with 26.4-dB OSNR and with phase and frequency deviations ranging uniformly from 0 up to the maximum values considered on the analysis presented in Fig 4 (i.e., 1-MHz residual frequency deviation and 100-kHz lasers linewidth)
Summary
Optical networks are a key technology to support the global telecommunications backbone, especially with the rising and large acceptance of on-demand high-quality video distribution, cloud computing, and Internet of Things (IoT) applications. This new technological paradigm, besides increasing the capacity demand in optical networks, drastically changes its requirements in some cases. High-capacity optical systems usually rely on wavelength-multiplexing (WDM) techniques, on which the specific frequency (or wavelength) of each transmitted channel is set in a fixed grid. Optical components and devices can be designed to operate in specific and fixed frequency slots, diminishing costs and accelerating the development process
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