arrow
Return

Modulation Format Identification in Mode Division Multiplexed Optical Networks

delete2019-01-01
delete11
delete
OA
AI
W
Waddah S. Saif *
A
Amr M. Ragheb
H
Hussein Seleem
T
Tariq Alshawi
S
Saleh A. Alshebeili
DOI:10.1109/ACCESS.2019.2949201delete
deleteOriginal
deleteShare
deleteSave
View PDF
Abstract

Abstract

En 中文
In this paper, we address the problem of modulation format identification (MFI) for few mode fiber (FMF) transmission in elastic optical networks (EONs). The MFI accuracy is studied under different FMF channel conditions including mode coupling (MC), optical signal-to-noise ratio (OSNR), and chromatic dispersion (CD). Artificial neural network, trained using features extracted from the asynchronous in-phase quadrature histogram (IQH), is proposed to investigate the identification accuracy. Extensive simulation results have been conducted to identify six modulation schemes widely used in polarization division multiplexing coherent optical networks. This includes PDM-BPSK, PDM-QPSK, PDM-8QAM, PDM-16QAM, PDM-32QAM, and PDM-64QAM transmitted at 10 Gbaud network transmission speed. The results show that the proposed MFI achieves a successful average identification accuracy exceeding 98 in the presence of low MC when the incoming signal OSNR is greater than 20 dB. However, the effect of high MC and CD 1100 ps/nm reduces the average accuracy to 90. Further, the MFI accuracy is investigated under different symbol rates such as 14 and 20 Gbaud.
Keywords:
Optical fiber networks
Optical modulation
Optical amplifiers
Multiplexing
Optical transmitters
Optical polarization
Coherent optical communication
few mode fiber
modulation format identification
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

IEEE Access cover
IEEE Access
IF:
3.6
Papers:
9.8W
Citations:
29.4W

Organization

K
King Saud University
Scholars:
3.4W
Papers: 3.8W
Citations: 815
E
egyptian knowledge bank (ekb)
Scholars:
11.6W
Papers: 9.3W
Citations: 84