173 research outputs found

    Enabling Technologies for Cognitive Optical Networks

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    Simultaneous chromatic dispersion, polarization-mode-dispersion and OSNR monitoring at 40Gbit/s

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    A novel method for independent and simultaneous monitoring of chromatic dispersion ( CD), first-order PMD and OSNR in 40Gbit/s systems is proposed and demonstrated. This is performed using in-band tone monitoring of 5GHz, optically down-converted to a low intermediate-frequency (IF) of 10kHz. The measurement provides a large monitoring range with good accuracies for CD (4742 +/- 100ps/nm), differential group delay (DGD) (200 +/- 4ps) and OSNR (23 +/- 1dB), independently of the bit-rate. In addition, the use of electro-absorption modulators (EAM) for the simultaneous down-conversion of all channels and the use of low-speed detectors makes it cost effective for multi-channel operation. (C) 2008 Optical Society of Americ

    An Overview on Application of Machine Learning Techniques in Optical Networks

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    Today's telecommunication networks have become sources of enormous amounts of widely heterogeneous data. This information can be retrieved from network traffic traces, network alarms, signal quality indicators, users' behavioral data, etc. Advanced mathematical tools are required to extract meaningful information from these data and take decisions pertaining to the proper functioning of the networks from the network-generated data. Among these mathematical tools, Machine Learning (ML) is regarded as one of the most promising methodological approaches to perform network-data analysis and enable automated network self-configuration and fault management. The adoption of ML techniques in the field of optical communication networks is motivated by the unprecedented growth of network complexity faced by optical networks in the last few years. Such complexity increase is due to the introduction of a huge number of adjustable and interdependent system parameters (e.g., routing configurations, modulation format, symbol rate, coding schemes, etc.) that are enabled by the usage of coherent transmission/reception technologies, advanced digital signal processing and compensation of nonlinear effects in optical fiber propagation. In this paper we provide an overview of the application of ML to optical communications and networking. We classify and survey relevant literature dealing with the topic, and we also provide an introductory tutorial on ML for researchers and practitioners interested in this field. Although a good number of research papers have recently appeared, the application of ML to optical networks is still in its infancy: to stimulate further work in this area, we conclude the paper proposing new possible research directions

    Simultaneous multi-impairment monitoring of 640 Gb/s signals using photonic chip based RF spectrum analyzer

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    We report the first demonstration of simultaneous multiimpairment monitoring at ultrahigh bitrates using a THz bandwidth photonic-chip-based radio-frequency (RF) spectrum analyzer. Our approach employs a 7 cm long, highly nonlinear (γ ≈9900 /W/km), dispersion engineered chalcogenide planar waveguide to capture the RF spectrum of an ultrafast 640 Gb/s signal, based on cross-phase modulation, from which we numerically retrieve the autocorrelation waveform. The relationship between the retrieved autocorrelation trace and signal impairments is exploited to simultaneously monitor dispersion, in-band optical signal to noise ratio (OSNR) and timing jitter from a single measurement. This novel approach also offers very high OSNR measurement dynamic range (> 30 dB) and is scalable to terabit data rates

    Multi-impairment and multi-channel optical performance monitoring

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    Next generation optical networks will evolve from static to dynamically reconfigurable architectures to meet the increasing bandwidth and service requirements. The benefits of dynamically reconfigurable networks (improved operations, reduced footprint and cost) have introduced new challenges, in particular the need for complex management which has put pressure on the engineering rules and transmission margins. This has provided the main drive to develop new techniques for optical performance monitoring (OPM) without using optical-to-electrical-to-optical conversions. When considering impairments due to chromatic dispersion in dynamic networks, each channel will traverse a unique path through the network thus the channels arriving at the monitoring point will, in general, exhibit different amounts of residual dispersion. Therefore, in a dynamic network it is necessary to monitor all channels individually to quantify the degradation, without the requirement of knowing the data path history. The monitoring feature can be used in conjunction with a dispersion compensation device which can either be optical or electrical or used to trigger real-time alarms for traffic re-routing. The proposed OPM technique is based on RF spectrum analysis and used for simultaneous and independent monitoring of power, chromatic dispersion (CD), polarisation mode dispersion (PMD) and optical signal-to-noise ratio (OSNR) in 40Gbit/s multi0channel systems. An analytical model is developed to describe the monitoring technique which allows the prediction of the measurement range. The experimental results are given for group velocity dispersion (GVD), differential group delay (DGD) and OSNR measurements. This technique is based on electro-optic down-conversion that simultaneously down-converts multiple channels, sharing the cost of the key components over multiple channels and making it cost effective for multi-channel operation. The measurement range achieved with this method is equal to 4742±100ps/nm for GVD, 200±4ps for DGD and 25±1dB for OSNR. To the knowledge of the author, these dispersion monitoring ranges are the largest reported to date for the bit-rate of 40Gbit/s with amplitude modulation formats

    Machine Learning for Multi-Layer Open and Disaggregated Optical Networks

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    L'abstract è presente nell'allegato / the abstract is in the attachmen

    Developing coherent optical wavelength conversion systems for reconfigurable photonic networks

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    In future optical networks that employ wavelength division multiplexing (WDM), the use of optical switching technologies on a burst or packet level, combined with advanced modulation formats would achieve greater spectral efficiency and utilize the existing bandwidth more efficiently. All-optical wavelength converters are expected to be one of the key components in these broadband networks. They can be used at the network nodes to avoid contention and to dynamically allocate wavelengths to ensure optimum use of fiber bandwidth. In this work, a reconfigurable wavelength converter comprising of a Semiconductor Optical Amplifier (SOA) as the nonlinear element and a fast-switching sampled grating distributed Bragg reflector (SG-DBR) tunable laser as one of the pumps is developed. The wavelength conversion of 12.5-Gbaud quadrature phase shift keying (QPSK) and Pol-Mul QPSK signals with switching time of tens of nanoseconds is experimentally achieved. Although the tunable DBR lasers can achieve ns tuning time, they present relatively large phase noise. The phase noise transfer from the pump to the converted signal can have a deleterious effect on signal quality and cause a performance penalty with phase modulated signals. To overcome the phase noise transfer issue, a wavelength converter using tunable dual-correlated pumps provided by the combination of a single-section quantum dash passively mode-locked laser (QD-PMLL) and a programmable tunable optical filter is designed and the wavelength conversion of QPSK and 16-quadrature amplitude modulation (16-QAM) signals at 12.5 GBaud is experimentally investigated. Nonlinear distortion of the wavelength converted signal caused by gain saturation effects in the SOA can significantly degrade the signal quality and cause difficulties for the practical wavelength conversion of sig nal data with advanced modulation formats. In this work, the machine learning clustering based nonlinearity compensation method is proposed to improve the tolerance to nonlinear distortion in an SOA based wavelength conversion system with 16 QAM and 64 QAM signals

    Optical performance monitoring in optical packet-switched networks

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    Para poder satisfacer la demanda de mayores anchos de banda y los requisitos de los nuevos servicios, se espera que se produzca una evolución de las redes ópticas hacia arquitecturas reconfigurables dinámicamente. Esta evolución subraya la importancia de ofrecer soluciones en la que la escalabilidad y la flexibilidad sean las principales directrices. De acuerdo a estas características, las redes ópticas de conmutación de paquetes (OPS) proporcionan altas capacidades de transmisión, eficiencia en ancho de banda y excelente flexibilidad, además de permitir el procesado de los paquetes directamente en la capa óptica. En este escenario, la solución all-optical label switching (AOLS) resuelve el cuello de botella impuesto por los nodos que realizan el procesado en el dominio eléctrico. A pesar de los progresos en el campo del networking óptico, las redes totalmente ópticas todavía se consideran una solución lejana . Por tanto, es importante desarrollar un escenario de migración factible y gradual desde las actuales redes ópticas basadas en la conmutación de circuitos (OCS). Uno de los objetivos de esta tesis se centra en la propuesta de escenarios de migración basados en redes híbridas que combinan diferentes tecnologías de conmutación. Además, se analiza la arquitectura de una red OPS compuesta de nodos que incorporan nuevas funcionalidades relacionadas con labores de monitorización y esquemas de recuperación. Las redes ópticas permiten mejorar la transparencia de la red, pero a costa de aumentar la complejidad de las tareas de gesión. En este escenario, la monitorización óptica de prestaciones (OPM) surge como una tecnología capaz de facilitar la administración de las redes OPS, en las que cada paquete sigue su propia ruta en la red y sufre un diferente nivel de degradación al llegar a su destino. Aquí reside la importancia de OPM para garantizar los requisitos de calidad de cada paquete.Vilar Mateo, R. (2010). Optical performance monitoring in optical packet-switched networks [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/8926Palanci
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