Abstract
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.
Highlights
Modern communication networks build upon a backbone of optical systems, which have fiber as the transmission medium
Components with nonlinear transfer characteristics, often with memory effects. Their limitations on the achievable capacity are aggravated by measures towards higher data rates, such as symbol rate increase or the shift to higher order pulse amplitude modulations (PAM) and quadrature amplitude modulations (QAM)
For the ultimate goal of reaching 600 Gb/s net data rate with the lowest possible bit-error rate (BER) over a wide range of optical signal-to-noise ratio (OSNR) levels, an optimal combination of modulation scheme and baud rate needs to be chosen in a first step, before improving its performance further with nonlinear equalization
Summary
Modern communication networks build upon a backbone of optical systems, which have fiber as the transmission medium. Due to its physical properties, including the Kerr effect, fiber communication is always affected by nonlinearities. This is the obvious, but not the only major source of nonlinear distortion in optical communication systems. Components with nonlinear transfer characteristics, often with memory effects. Their limitations on the achievable capacity are aggravated by measures towards higher data rates, such as symbol rate increase or the shift to higher order pulse amplitude modulations (PAM) and quadrature amplitude modulations (QAM). Nonlinear compensation for O/E components is not yet a standard feature in today’s optical transceivers, but will inevitably become a key element of digital signal processing (DSP)
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
