Experimental comparison of artificial neural network and volterra based nonlinear equalization for CO-OFDM

2016 Optical Fiber Communications Conference and Exhibition (OFC) Pub Date : 2016-03-20 DOI:10.1364/OFC.2016.W3A.4

E. Giacoumidis, S. Le, I. Aldaya, Jinlong Wei, M. McCarthy, N. Doran, B. Eggleton

引用次数: 14

Abstract

A novel artificial neural network (ANN)-based nonlinear equalizer (NLE) of low complexity is demonstrated for 40-Gb/s CO-OFDM at 2000 km, revealing ~1.5 dB enhancement in Q-factor compared to inverse Volterra-series transfer function based NLE.

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CO-OFDM中人工神经网络与volterra非线性均衡的实验比较

提出了一种新型的基于人工神经网络(ANN)的低复杂度非线性均衡器(NLE)，该均衡器适用于2000 km的40gb /s CO-OFDM，与基于逆volterra系列传递函数的非线性均衡器相比，q因子提高了约1.5 dB。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

2016 Optical Fiber Communications Conference and Exhibition (OFC)

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