Nonlinear distortion has always been a challenge for optical communication due to the nonlinear transfer characteristics of the fiber itself. The next frontier for optical communication is a second type of nonlinearities, which results from optical and electrical components. They become the dominant nonlinearity for shorter reaches. The highest data rates cannot be achieved without effective compensation. A classical countermeasure is receiver-side equalization of nonlinear impairments and memory effects using Volterra series. However, such Volterra equalizers are architecturally complex and their parametrization can be numerical unstable. This contribution proposes an alternative nonlinear equalizer architecture based on machine learning. Its performance is evaluated experimentally on coherent 88 Gbaud dual polarization 16QAM 600 Gb/s back-to-back measurements. The proposed equalizers outperform Volterra and memory polynomial Volterra equalizers up to 6th orders at a target bit-error rate (BER) of ${10}^{-2}$ by 0.5 dB and 0.8 dB in optical signal-to-noise ratio (OSNR), respectively.

We report an industry leading optical dense wavelength division multiplexing (DWDM) field trial with line rates per channel.1.66 Tb/s using 130 GBaud dualpolarization probabilistic constellation shaping 256-ary quadrature amplitude modulation (DP-PCS256QAM) in a high capacity data center interconnect (DCI) scenario. This research trial was performed on 96.5 km of field-deployed standard single mode G.652 fiber infrastructure of Deutsche Telekom in Germany employing Erbium-doped fiber amplifier (EDFA)-only amplification. A total of 34 channels were transmitted with 150 GHz spacing for a total fiber capacity of 56.51 Tb/s and a spectral efficiency higher than 11bit/s/Hz. In the single-channel transmission scenario 1.71 Tb/s was achieved over the same link. In addition, we successfully demonstrate record net bitrates of 1.88 Tb/s in back-to-back (B2B) using 130 GBaud DP-PCS400QAM.

High speed optical transmission systems suffer from intersymbol interference (ISI) and colored noise induced by nonlinear bandwidth limited optical and electrical components. As a countermeasure, this article investigates deep neural network soft-demappers. In particular, we propose a bidirectional recurrent neural network soft-demapper (BRNN-SD) and benchmarked its performance against a time delay neural network soft-demapper (TDNN-SD) and a reference digital signal processing (DSP) scheme consisting of a Volterra nonlinear equalizer accompanied by a symbol-spaced whitening filter and a BCJR detector. On coherent 92GBd dual polarization (DP)-32QAM back-to-back measurements, the proposed soft-demapper matches the performance of the reference DSP. In 800 Gb/s 96GBd DP-32QAM 32-channel dense wavelength division multiplexing (DWDM) transmission over a 600 km fiber link the proposed approach outperforms the reference DSP.

High degree of heterogeneity of future optical networks, stemming from provisioning of services with different quality-of-transmission requirements, and transmission links employing mixed modulation formats or switching techniques, will pose a challenge for the control and management of the network. The incorporation of cognitive techniques can help to optimize a network by employing mechanisms that can observe, act, learn and improve network performance, taking into account end-to-end goals. The EU project CHRON: Cognitive Heterogeneous Reconfigurable Optical Network proposes a strategy to efficiently control the network by implementing cognition. In this paper we present a survey of different techniques developed throughout the course of the project to apply cognition in future optical networks.

We successfully demonstrate 400Gbit/s transmission at 1577nm over an unamplified 40km standard single-mode fiber (SSMF) link with 11dB loss target. Commercially available high-bandwidth coherent driver modulator (HB-CDM) and high-bandwidth micro integrated coherent receiver (HB-μICR) designed for Cband are used in combination with two TO-can packaged and thermally tuned low-cost L-band laser sources. With the aid of a memory-less 1 sample/symbol nonlinear offline digital-signal processing (DSP) correcting for the nonlinear transfer curve of the driver and modulator we can maximize the transmitter optical power, which is critical for unamplified fiber applications. In addition, multistage carrier recovery enables stable performance also with the large phase noise of the used coherent laser source, originally part of an electro-absorption modulated laser module (EML) and designed for extremely price-sensitive passive optical network (PON) applications.

We report a record of 72.64 Tb/s WDM transmission at 12.29 bits/s/Hz over 100 km G.654D fiber. Super C-band EDFAs with 6 THz gain spectrum are used to transmit 43 130 GBaud DP-PCS256QAM channels.