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.

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.

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.

This work details the design of a plastic fiber link in 28-nm CMOS, operating in two adjacent bands centered on 117.5 and 152.5 GHz. Each band supports multilevel (PAM-4) intensity-modulated signaling, which can be detected noncoherently, obviating the need for carrier recovery and phase alignment. A rectification-based detector is proposed to support linear noncoherent demodulation. A manifold diplexer is designed on-chip to increase the level of integration. The dual-band link achieves data rates up to 100 Gb/s over a fiber length of 3 m at a power consumption of 574 mW and a bit error rate (BER) better than 2.2e-4, corresponding to the standardized KP4 forward error correction (FEC) threshold. With only the low-band (LB) circuitry active, the link reaches up to 50 Gb/s over a distance of 7 m at a degraded BER of 2.2e-3 and up to 10 Gb/s over 11 m at a BER of 1e-6, representing the highest reported data rates for these link lengths. An energy efficiency reaching as low as 0.8 pJ/bit/m is reported for the 7-m case.

In this article, we discuss challenges and options for scaling IM/DD transceivers towards 800Gbps. Our focus is CWDM4 PAM4 transmission and our target distance is 10km in O-band, which is a most urgent use case for next generation optical short reach systems like data centre interconnects and networks. At this reach and rate, chromatic dispersion (CD) becomes the main challenge. Its mitigation is essential and primarily done with digital signal processing. State of the art techniques, however, make transceivers quickly too complex. We show upon measurement results how neural network equalization can meet Volterra equalization performance with 30% less hardware multiplier complexity. When also applying magnitude weight pruning, an additional 43% reduction is possible without performance loss across all CWDM4 lanes. If needed, an added MLSE stage can further push performance in both cases. In any of these configurations, a key enabler against strong CD penalties is duobinary training, which is applicable to all feed-forward equalization architectures.

Single lambda coherent 600Gb/s solutions based on single carrier modulation or OFDM with and without bit and power loading are experimentally assessed. Volterra nonlinear equalization architectures are optimized for the most performant schemes.