Image of Modulation Scheme Identification Based on Artificial Neural Network Algorithms for Optical Communication System

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Modulation Scheme Identification Based on Artificial Neural Network Algorithms for Optical Communication System



Abstract
Higher-order modulation schemes in optical communication systems that suffer from several impairments can use artificial intelligence (AI) algorithms, among other possible techniques, to mitigate these issues. In this paper, several techniques for optical communication systems have been proposed to enhance the performance of dual-polarization (DP) M-ary Quadrature Amplitude Modulation (M-QAM) as DP-16-QAM, DP-64-QAM, DP-128-QAM, and DP-256-QAM with 240Gbps data rate. Artificial neural networks (ANNs) with seven different training algorithms have been applied to optimize the optical communication system. A high optimization of modulation format identification (MFI) with accuracy up to 100% was obtained at about 13 dB OSNR and at 22 dB OSNR for the DP-265-QAM format.


Ketersediaan

JICTRA1-005JICTRA V14N1 July 2020Perpustakaan FT UPI YAITersedia

Informasi Detil

Judul Seri
Journal of ICT Research and Application
No. Panggil
JICTRA V14N1 July 2020
Penerbit ITB Journal Publisher : Bandung.,
Deskripsi Fisik
hlm : 69-77
Bahasa
English
ISBN/ISSN
2337-5787
Klasifikasi
JICTRA
Tipe Isi
-
Tipe Media
-
Tipe Pembawa
-
Edisi
Volume 14 Nomor 1 July 2020
Subyek
Info Detil Spesifik
-
Pernyataan Tanggungjawab

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