Wyniki wyszukiwania - BazTech

1

Using ADTS and CNN methods to effectively monitor CD, crosstalk, and OSNR in an optical network

Mrozek Tomasz, Perlicki Krzysztof

Opto-Electronics Review

|

2024

|

Vol. 32, No. 3

art. no. e151963

EN

The article presents the results of a method based on asynchronous delay-tap sampling (ADTS) and convolutional neural network (CNN) for determining simultaneously occurring disturbances described using the chromatic dispersion (CD), crosstalk and optical signal-to-noise ratio (OSNR) parameters. The ADTS method was used to generate training and test data for the convolutional network, which in turn was used to learn to recognize interference from said data. The tests were carried out for a transmission speed of 10 Gbit/s and for on-off keying (OOK) and differential phase shift keying (DPSK) modulation. Very good results were obtained in recognizing simultaneously occurring phenomena. Accuracy of over 99% was achieved for CD and crosstalk for DPSK modulation and over 98% for OOK modulation. In the case of amplified spontaneous emission (ASE) noise, slightly weaker results were obtained, above 95-96% for both modulations. Based on the conducted research, it was determined that the use of ADTS and CNN methods enables monitoring of simultaneously occurring CD, crosstalk, and ASE noise in the physical layer of the optical network, while maintaining the requirements for modern monitoring systems.

2

Simultaneous monitoring of chromatic dispersion and optical signal to noise ratio in optical links using convolutional neural network and asynchronous delay-tap sampling

Mrozek Tomasz, Perlicki Krzysztof, Jakubiak Andrzej

Optica Applicata

|

2020

|

Vol. 50, nr 3

331--341

EN

The article presents a method for image analysis using asynchronous delay-tap sampling (ADTS) technique and convolutional neural networks (CNNs), allowing simultaneous monitoring of many phenomena occurring in the physical layer of the optical network. The ADTS method makes it possible to visualize the course of the optical signal in the form of characteristics (so-called phase portraits), which change their shape under the influence of phenomena (including chromatic dispersion, amplified spontaneous emission noise and other). Using the VPI photonics software,a simulation model of the ADTS technique was built. After the simulation tests, 10000 images were obtained, which after proper preparation were subjected to further analysis using CNN algorithms. The main goal of the study was to train a CNN to recognize the selected impairment (distortion); then to test its accuracy and estimate the impairment for the selected set of test images. The input data consisted of processed binary images in the form of two-dimensional matrices, with the position of the pixel. This article focuses on the analysis of images containing simultaneously the phenomena of chromatic dispersion and optical signal to noise ratio.

3

The use of convolutional neural networks for simultaneous monitoring of chromatic dispersion and Optical to Signal Noise Ratio in the physical layer of the optical network

Mrozek Tomasz, Perlicki Krzysztof

Przegląd Telekomunikacyjny + Wiadomości Telekomunikacyjne

|

2019

|

nr 3

67--72

EN

The article presents a method for image analysis using Asynchronous Delay Tap Sampling (ADTS) technique and Convolutional Neural Networks (CNN), allowing simultaneous monitoring of many phenomena occurring in the physical layer of the optical network. The ADTS method makes it possible to visualize the course of the optical signal in the form of characteristics (so-called phase portraits), which change their shape under the influence of phenomena (including chromatic dispersion, amplified spontaneous emission noise and others). Using the VP Iphotonics software, a simulation model of the ADTS technique was built. After the simulation tests, 10000 images were obtained, which after proper preparation were subjected to further analysis using convolutional neural networks algorithms. The main goal of the study was to train a convolutional neural network to recognize the selected impairment (distortion); then to test its accuracy and estimate the impairment for the selected set of test images. The input data consisted of processed binary images in the form of two-dimensional matrices, with the position of the pixel. This article focuses on the analysis of images containing simultaneously the phenomena of chromatic dispersion and optical to noise signal ratio.

PL

Przedstawiono metodę analizy obrazu za pomocą technik: Asynchronous Delay Tap Sampling (ADTS) i Convolutional Neural Networks (CNN), umożliwiającą równoczesne monitorowanie wielu zjawisk zachodzących w warstwie fizycznej sieci optycznej. Metoda ADTS umożliwia wizualizację przebiegu sygnału optycznego w postaci charakterystyk (tzw. portrety fazowe), które zmieniają swój kształt pod wpływem zjawisk (w tym dyspersji chromatycznej, OSNR i innych). Za pomocą oprogramowania VP Iphotonics zbudowano model symulacyjny techniki ADTS. Po testach symulacyjnych uzyskano 10 000 obrazów, które po odpowiednim przygotowaniu poddano dalszej analizie za pomocą algorytmówk konwolucyjnych sieci neuronowych. Głównym celem badań było nauczenie konwolucyjnej sieci neuronowej rozpoznawania równocześnie występujących zaburzeń. Dane wejściowe składały się z przetworzonych obrazów binarnych w postaci macierzy dwuwymiarowych. Artykuł skupia się na analizie obrazów zawierających jednocześnie zjawisko dyspersji chromatycznej i OSNR.