Applications of Physics-Informed Neural Network for Optical Fiber Communications | PERPUSTAKAAN UNIVERSITAS KATOLIK PARAHYANGAN

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Applications of Physics-Informed Neural Network for Optical Fiber Communications

Wang, Danshi - Nama Orang; Zhang, Min - Nama Orang; Chen, Xue - Nama Orang; Zhang, Zhiguo - Nama Orang; Song, Yuchen - Nama Orang; Fu, Meixia - Nama Orang; Jiang, Xiaotian - Nama Orang;

Due to the capability of the physics-informed neural network (PINN) to solve complex partial differential equations automatically, it has revolutionized the field of scientific computing. This article studies the applicability of PINN in optical fiber communication and presents five potential solutions for time-domain, frequency-domain, and spatial-domain modeling. By solving the nonlinear Schrödinger equation (NLSE), both forward and backward optical waveform propagation are modeled by PINN; by solving the inverse problem of NLSE, the physical parameters of fiber are identified with limited data, including attenuation, dispersion, and nonlinear coefficient. By solving the stimulated Raman scattering evolution equation, the wideband spectrum evolution is simulated for C+L-band systems. By solving the paraxial Helmholtz equation, the electric field distribution in a fiber is modeled, and five lowest-order fiber modes are studied. In comparison to conventional numerical methods, PINNs achieve the approximated accuracy while having lower computation complexity and less computation time over the same fiber length for a given initial condition. Finally, the challenges faced by PINN are pointed out, and an outlook on future research of the physics-informed approach is concluded.

Ketersediaan

Barcode		Tipe Koleksi	Nomor Panggil	Lokasi	Status
art144921	null	Artikel		Gdg9-Lt3	Tersedia namun tidak untuk dipinjamkan - No Loan

Informasi Detail

Judul Seri: IEEE COMMUNICATIONS MAGAZINE; Vol.60 No.9 September 2022
No. Panggil: -
Penerbit: : .,
Deskripsi Fisik: p. 32-37
Bahasa: English
ISBN/ISSN: -
Klasifikasi: NONE
Tipe Isi: -
Tipe Media: -
Tipe Pembawa: -
Edisi: -
Subjek: MATHEMATICAL MODELS
OPTICAL FIBERS
NEURAL NETWORKS
OPTICAL FIBER COMMUNICATION
OPTICAL FIBER NETWORKS
OPTICAL FIBER DISPERSION
ARTIFICIAL NEURAL NETWORKS
COMPUTATIONAL MODELING
NUMERICAL MODELS
Info Detail Spesifik: DOI: 10.1109/MCOM.001.2100961
Pernyataan Tanggungjawab: Danshi Wang, Xiaotian Jiang, Yuchen Song, Meixia Fu, Zhiguo Zhang, Xue Chen, Min Zhang

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