activity
20182024
most citedLow Complexity Component Nonlinear Distortions Mitigation Scheme for Probabilistically Shaped 64-QAM Signals

2 citations · 3 across the 4 of their papers we have counts for

collaborators

5 papers

eess.SP2021

An Interpretable Mapping from a Communication System to a Neural Network for Optimal Transceiver-Joint Equalization

Zhiqun Zhai, Hexun Jiang, Mengfan Fu +4

In this paper, we propose a scheme that utilizes the optimization ability of artificial intelligence (AI) for optimal transceiver-joint equalization in compensating for the optical…

eess.SP20202 cited

Low Complexity Component Nonlinear Distortions Mitigation Scheme for Probabilistically Shaped 64-QAM Signals

Yiwen Wu, Mengfan Fu, Huazhi Lun +3

We propose a degenerated hierarchical look-up table (DH-LUT) scheme to compensate component nonlinearities. For probabilistically shaped 64-QAM signals, it achieves up to 2-dB SNR…

eess.SP2020

A Data-Fusion-Assisted Telemetry Layer for Autonomous Optical Networks

Xiaomin Liu, Huazhi Lun, Ruoxuan Gao +4

For further improving the capacity and reliability of optical networks, a closed-loop autonomous architecture is preferred. Considering a large number of optical components in an o…

eess.SP2020

Neural Network Training for OSNR Estimation -- From Prototype to Product

Andrew D. Shiner, Mohammad E. Mousa-Pasandi, Meng Qiu +6

A method for in-service OSNR measurement with a coherent transceiver is presented and experimentally verified. A neural network is employed to identify and remove the nonlinear noi…

eess.SP2018

Application of Machine Learning in Fiber Nonlinearity Modeling and Monitoring for Elastic Optical Networks

Qunbi Zhuge, Xiaobo Zeng, Huazhi Lun +3

Fiber nonlinear interference (NLI) modeling and monitoring are the key building blocks to support elastic optical networks (EONs). In the past, they were normally developed and inv…