Advanced nonlinear equalizer for Filter Bank Multicarrier-based Long Reach-Passive Optical Network system,International Journal of Communication Systems

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Advanced nonlinear equalizer for Filter Bank Multicarrier-based Long Reach-Passive Optical Network system
International Journal of Communication Systems ( IF 1.7 ) Pub Date : 2021-07-20 , DOI: 10.1002/dac.4921
Jerart Julus L ₁ , Manimegalai D ₁ , Asha Beaula C ₂ , Joshan Athanesious J ₃ , Andrew Roobert A ₄

Affiliation

The performance of the intensity-modulated Filter Bank Multicarrier (FBMC) system using direct detection with advanced nonlinear equalizer in Long Reach-Passive Optical Network (LR-PON) is presented in this paper. First, the performance of the FBMC system and its nonlinearity in the channel are analyzed. We introduce two nonlinear equalizers, namely, Artificial Neural Networks–Nonlinear Feed-Forward Equalizer (ANN-NFFE) and Deep Neural Network–Nonlinear Equalizer (DNN-NLE). Both the equalizers can mitigate the nonlinearities in the signal. Also, the impact of the system in downlink is analyzed using simulation by varying the data rates for various fiber lengths. The FBMC using SMT provides better spectral efficiency. The performance of both equalizers is compared. The addition of the DNN-NLE equalizer provides a better OSNR, good accuracy, and better BER compared with ANN-NFFE.

中文翻译：

滤波器组基于多载波的长距离无源光网络系统的高级非线性均衡器

本文介绍了在长距离无源光网络 (LR-PON) 中使用具有高级非线性均衡器的直接检测的强度调制滤波器组多载波 (FBMC) 系统的性能。首先，分析了FBMC系统的性能及其在信道中的非线性。我们介绍了两种非线性均衡器，即人工神经网络-非线性前馈均衡器（ANN-NFFE）和深度神经网络-非线性均衡器（DNN-NLE）。两个均衡器都可以减轻信号中的非线性。此外，通过改变各种光纤长度的数据速率，使用仿真分析了系统在下行链路中的影响。使用 SMT 的 FBMC 提供更好的频谱效率。比较两个均衡器的性能。DNN-NLE 均衡器的加入提供了更好的 OSNR、良好的精度、

更新日期：2021-08-16

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