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Threshold-Based Pruned Retraining Volterra Equalization for 100 Gbps/Lane and 100-m Optical Interconnects Based on VCSEL and MMF
35
Citations
15
References
2019
Year
PhotonicsElectrical EngineeringEngineeringRetraining Volterra EqualizationNonlinear EqualizerOptical Transmission SystemMixed-signal Integrated CircuitVolterra EqualizerChannel EqualizationComputer EngineeringOptical Wireless CommunicationPhotonic Integrated Circuit100-M Optical InterconnectsOptical CommunicationOptical NetworkingOptoelectronicsVolterra Equalization
The high-speed multimode optical interconnects based on vertical-cavity surface-emitting laser and multimode fiber (MMF) are severely constrained by band-limited devices, modulation nonlinearity, and laser induced noises such as relative intensity noise, mode partition noise, and fiber-induced noises such as chromatic dispersion and mode dispersion. The advanced digital signal processing technologies have been viewed as the inevitable tool to mitigate the physical limitations of electrical and optical components and the noise interactions during the transmission. In order to achieve multimode 100 Gbps/lane over 100-m transmission with the existing devices, a Volterra equalizer has been proven as a very effective equalization solution to deal with nonlinear impairments. However, the practical implementation of this nonlinear equalizer has been constrained by its tremendously high computation complexity. In this paper, we propose the threshold-based pruned retraining Volterra equalization (TRVE) to reduce the computation complexity, while maintaining the transmission performance. Multimode 100-Gbps/lane transmission over 100-m OM3 MMF has been experimentally demonstrated with up to 70.7% computation complexity reduction, while keeping the bit error rate under the 7% hard-decision forward error correction limit. In addition, the TRVE with l <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> -regularization is also proposed and experimentally verified to optimize the threshold selection.
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