Mitigation of Multi-user Access Impairments in 5G A-RoF-based Mobile Fronthaul utilizing Machine Learning for an Artificial Neural Network Nonlinear Equalizer

被引：0

作者：

Liu, Siming ^{[1
,2
]}

Alfadhli, Yahya M. ^{[2
]}

Shen, Shuyi ^{[2
]}

Tian, Huiping ^{[1
]}

Chang, Gee-Kung ^{[2
]}

机构：

[1] Beijing Univ Posts & Telecommun, Sch Informat & Commun Engn, Beijing, Peoples R China

[2] Georgia Inst Technol, Sch Elect & Comp Engn, Atlanta, GA 30332 USA

来源：

2018 OPTICAL FIBER COMMUNICATIONS CONFERENCE AND EXPOSITION (OFC) | 2018年

基金：

美国国家科学基金会;

关键词：

SYSTEMS;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

We propose a complex-valued multi-level artificial neural network nonlinear equalizer (ANN-NLE) in bandwidth-efficient radio-over-fiber mobile fronthaul systems. The proposed ANN-NLE is experimentally demonstrated to mitigate intra/inter-band interferences caused by nonlinear impairments in multi-user environments.

引用

页数：3

共 6 条

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[2]

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[5]

Wang J., 2016, ECOC, P914

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