MIMO detection using a deep learning neural network in a mode division multiplexing optical transmission system

被引：19

作者：

Poudel, Bishal ^{[1
]}

Oshima, Joji ^{[1
]}

Kobayashi, Hirokazu ^{[1
]}

Iwashita, Katsushi ^{[1
]}

机构：

[1] Kochi Univ Technol, Dept Photon Syst Engn, 185 Miyanokuchi, Kami City, Kochi 7828502, Japan

来源：

OPTICS COMMUNICATIONS | 2019年 / 440卷

关键词：

Multiple Input Multiple Output; Deep learning neural network; Mode division multiplexing; Optical transmission system; Optimum detector; SDM TRANSMISSION; EQUALIZATION; SIGNALS; CORE;

D O I：

10.1016/j.optcom.2019.02.016

中图分类号：

O43 [光学];

学科分类号：

070207 ; 0803 ;

摘要：

Optimum Multiple Input Multiple Output (MIMO) detector has always been a challenge in MIMO communication systems. In this paper, a novel MIMO detector has been designed using a supervised Deep Learning Neural Network (DLNN) and has been implemented successfully in a Mode Division Multiplexing (MDM) optical transmission system. A conventional Graded-Index Multi-Mode Fiber (GI-MMF) is used to design an MDM optical transmission system. We have used a DLNN for MIMO detection in MDM optical transmission system and have compared its performance with Zero Forcing (ZF) detector and Semi-Definite Relaxation Row-by-Row (SDR-RBR). The results confirm that our DLNN outruns the performance of traditional MIMO detectors.

引用

页码：41 / 48

页数：8

共 29 条

[11]

Hinton G.E., 2012, IMPROVING NEURAL NET

[12] Mode-dependent loss and gain: statistics and effect on mode-division multiplexing [J].

Ho, Keang-Po ;

Kahn, Joseph M. .

OPTICS EXPRESS, 2011, 19 (17) :16612-16635

[13] SDM transmission of real-time 10GbE traffic using commercial SFP plus transceivers over 0.5km elliptical-core few-mode fiber [J].

Ip, Ezra ;

Milione, Giovanni ;

Li, Ming-Jun ;

Cvijetic, Neda ;

Kanonakis, Konstantinos ;

Stone, Jeffery ;

Peng, Gaozhu ;

Prieto, Xesus ;

Montero, Carlos ;

Moreno, Vicente ;

Linares, Jesus .

OPTICS EXPRESS, 2015, 23 (13) :17120-17126

[14]

Jeon C, 2015, IEEE INT SYMP INFO, P1227, DOI 10.1109/ISIT.2015.7282651

[15] Caffe: Convolutional Architecture for Fast Feature Embedding [J].

Jia, Yangqing ;

Shelhamer, Evan ;

Donahue, Jeff ;

Karayev, Sergey ;

Long, Jonathan ;

Girshick, Ross ;

Guadarrama, Sergio ;

Darrell, Trevor .

PROCEEDINGS OF THE 2014 ACM CONFERENCE ON MULTIMEDIA (MM'14), 2014, :675-678

[16]

Kingma D.P., ADAM METHOD STOCHAST

[17] Semidefinite Relaxation of Quadratic Optimization Problems [J].

Luo, Zhi-Quan ;

Ma, Wing-Kin ;

So, Anthony Man-Cho ;

Ye, Yinyu ;

Zhang, Shuzhong .

IEEE SIGNAL PROCESSING MAGAZINE, 2010, 27 (03) :20-34

[18]

Ma WK, 2008, INT CONF ACOUST SPEE, P2673

[19]

Marcuse D., 2013, Theory of Dielectric Optical Waveguides

[20] Coupled Manakov equations in multimode fibers with strongly coupled groups of modes [J].

Mecozzi, Antonio ;

Antonelli, Cristian ;

Shtaif, Mark .

OPTICS EXPRESS, 2012, 20 (21) :23436-23441

← 1 2 3 →