Toward Universal Optical Performance Monitoring for Intelligent Optical Fiber Communication Networks

2020 ◽  
Vol 58 (9) ◽  
pp. 54-59
Author(s):  
Dawei Wang ◽  
Qi Sui ◽  
Zhaohui Li
Keyword(s):  
Optical Fiber ◽  
Communication Networks ◽  
Performance Monitoring ◽  
Optical Fiber Communication ◽  
Optical Performance ◽  
Optical Performance Monitoring ◽  
Fiber Communication

A Comprehensive Review on Fiber Bragg Grating and Photodetector in Optical Communication Networks

2019 ◽  
Vol 0 (0) ◽  
Author(s):  
Suresh Kumar ◽  
Shiwani Rathee ◽  
Payal Arora ◽  
Deepak Sharma
Keyword(s):  
Optical Fiber ◽  
Fiber Bragg Grating ◽  
Communication Networks ◽  
Optical Communication ◽  
Communication System ◽  
Optical Fiber Communication ◽  
Bragg Grating ◽  
Fiber Communication ◽  
Efficient System ◽  
Data Links

AbstractThe optical fiber communication offers a huge bandwidth for data transmission at higher data rates but to increase the throughput for long-haul networks, metro data links, and data centers, additional fiber is required which is not economical. For effective reception of signals at the receiver, the photo detector in optical communication requires higher efficiency, lower noise, ultrafast response and optimum received signal strength. The inherent dispersion and nonlinear impairments in optical fiber communication system can be overcome by using the Fiber Bragg Grating (FBG) which is a Dispersion Compensating Module. FBG helps to improve the long-haul transmission by providing an efficient system performance. This paper presents a detailed review of FBG and photo detectors and their use in an Optical communication system. This paper will help the researchers to find useful material at a single platform.

Artificial intelligence based optical performance monitoring

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Palash Rai ◽  
Rahul Kaushik
Keyword(s):  
Communication Networks ◽  
Performance Monitoring ◽  
Signal To Noise Ratio ◽  
Chromatic Dispersion ◽  
Optical Signal ◽  
Optical Performance ◽  
Optical Performance Monitoring ◽  
Eye Diagram ◽  
Artificial Neural Network Ann ◽  
Data Signal

Abstract In this paper, a technique for optical performance monitoring (OPM) using deep learning-based artificial neural network (ANN) is implemented. ANN is trained with parameters derived from eye-diagram for the identification of optical signal to noise ratio (OSNR), chromatic dispersion (CD) and polarisation mode dispersion (PMD) simultaneously and independently in a 10 Gb/s system with non-return-to-zero (NRZ) on-off keying (OOK) data signal. ANN-based OPM confirms that the proposed approach can provide reliable estimated results. The mean squared errors for OSNR, CD and differential group delay (DGD) are found to be 4.6071 dB, 0.0417 ps/nm/km and 0.0016 ps/km, respectively. The proposed technique may be utilized in analyzing the signals of future heterogeneous optical communication networks intelligently.

Optical Fiber Communication Performance Monitoring Based on Asynchronous Delay Tap Sampling

2012 ◽  
Vol 32 (11) ◽  
pp. 1106004
Author(s):  
赖俊森 Lai Junsen ◽  
杨爱英 Yang Aiying ◽  
孙雨南 Sun Yu′nan
Keyword(s):  
Optical Fiber ◽  
Performance Monitoring ◽  
Optical Fiber Communication ◽  
Communication Performance ◽  
Fiber Communication
Sign in / Sign up

Export Citation Format

Share Document