An Overview on Application of Machine Learning Techniques in Optical Networks

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

Machine Learning for Multi-Layer Open and Disaggregated Optical Networks

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Artificial intelligence (AI) methods in optical networks: A comprehensive survey

Producción CientíficaArtificial intelligence (AI) is an extensive scientific discipline which enables computer systems to solve problems by emulating complex biological processes such as learning, reasoning and self-correction. This paper presents a comprehensive review of the application of AI techniques for improving performance of optical communication systems and networks. The use of AI-based techniques is first studied in applications related to optical transmission, ranging from the characterization and operation of network components to performance monitoring, mitigation of nonlinearities, and quality of transmission estimation. Then, applications related to optical network control and management are also reviewed, including topics like optical network planning and operation in both transport and access networks. Finally, the paper also presents a summary of opportunities and challenges in optical networking where AI is expected to play a key role in the near future.Ministerio de Economía, Industria y Competitividad (Project EC2014-53071-C3-2-P, TEC2015-71932-REDT

Experimental Demonstration of Partially Disaggregated Optical Network Control Using the Physical Layer Digital Twin

Optical communications and networking are fast becoming the solution to support ever-increasing data traffic across all segments of the network, expanding from core/metro networks to 5G/6G front-hauling. Therefore, optical networks need to evolve towards an efficient exploitation of the infrastructure by overcoming the closed and aggregated paradigm, to enable apparatus sharing together with the slicing and separation of the optical data plane from the optical control. In addition to the advantages in terms of efficiency and cost reduction, this evolution will increase network reliability, also allowing for a fine trade-off between robustness and maximum capacity exploitation. In this work, an optical network architecture is presented based on the physical layer digital twin of the optical transport used within a multi-layer hierarchical control operated by an intent-based network operating system. An experimental proof of concept is performed on a three-node network including up to 1000 km optical transmission, open re-configurable optical add & drop multiplexers (ROADMs) and whitebox transponders hosting pluggable multirate transceivers. The proposed solution is based on GNPy as the optical physical layer digital twin and ONOS as intent-based network operating system. The reliability of the optical control decoupled by the data plane functioning is experimentally demonstrated exploiting GNPy as open lightpath computation engine and software optical amplifier models derived from the component characterization. Besides the lightpath deployment exploiting the modulation format evaluation given a generic traffic request, the architecture reliability is tested mimicking the use case of an automatic failure recovery from a fiber cut

GNPy model of the physical layer for open and disaggregated optical networking [Invited]

Networking technologies are fast evolving to support the request for ubiquitous Internet access that is becoming a fundamental need for the modern and inclusive society, with a dramatic speed-up caused by the COVID-19 emergency. Such evolution needs the development of networks into disaggregated and programmable systems according to the software-defined networking (SDN) paradigm. Wavelength-division multiplexed (WDM) optical transmission and networking is expanding as physical layer technology from core and metro networks to 5G x-hauling and inter- and intra-data-center connections requiring the application of the SDN paradigm at the optical layer based on the WDM optical data transport virtualization. We present the fundamental principles of the open-source project Gaussian Noise in Python (GNPy) for the optical transport virtualization in modeling the WDM optical transmission for open and disaggregated networking. GNPy approximates transparent lightpaths as additive white and Gaussian noise channels and can be used as a vendor-agnostic digital twin for open network planning and management. The quality-of-transmission degradation of each network element is independently modeled to allow disaggregated network management. We describe the GNPy models for fiber propagation, optical amplifiers, and reconfigurable add/drop multiplexers together with modeling of coherent transceivers from the back-to-back characterization. We address the use of GNPy as a vendor-agnostic design and planning tool and as physical layer virtualization in software-defined optical networking. (C) 2022 Optica Publishing Grou

Automatic DGD and GVD compensation at 640 Gb/s based on scalar radio-frequency spectrum measurement

We demonstrate what we believe to be the first real-time impairment-cancellation system for groupvelocity dispersion (GVD) and differential group delay (DGD) for a 640 Gb/s single-channel signal. Simultaneous compensation of two independent parameters is demonstrated by feedback control of separate GVD and DGD compensators using an impairment monitor based on an integrated all-optical radio-frequency (RF) spectrum analyzer.We show that low-bandwidth measurement of only a single tone in the RF spectrum is sufficient for automatic compensation for multiple degrees of freedom using a multivariate optimization scheme

Wavelength tunable transmitters for future reconfigurable agile optical networks

Wavelength tuneable transmission is a requirement for future reconfigurable agile optical networks as it enables cost efficient bandwidth distribution and a greater degree of transparency. This thesis focuses on the development and characterisation of wavelength tuneable transmitters for the core, metro and access based WDM networks. The wavelength tuneable RZ transmitter is a fundamental component for the core network as the RZ coding scheme is favoured over the conventional NRZ format as the line rate increases. The combination of a widely tuneable SG DBR laser and an EAM is a propitious technique employed to generate wavelength tuneable pulses at high repetition rates (40 GHz). As the EAM is inherently wavelength dependant an accurate characterisation of the generated pulses is carried out using the linear spectrogram measurement technique. Performance issues associated with the transmitter are investigated by employing the generated pulses in a 1500 km 42.7 Gb/s circulating loop system. It is demonstrated that non-optimisation of the EAM drive conditions at each operating wavelength can lead to a 33 % degradation in system performance. To achieve consistent operation over a wide waveband the drive conditions of the EAM must be altered at each operating wavelength. The metro network spans relatively small distances in comparison to the core and therefore must utilise more cost efficient solutions to transmit data, while also maintaining high reconfigurable functionality. Due to the shorter transmission distances, directly modulated sources can be utilised, as less precise wavelength and chirp control can be tolerated. Therefore a gain-switched FP laser provides an ideal source for wavelength tuneable pulse generation at high data rates (10 Gb/s). A self-seeding scheme that generates single mode pulses with high SMSR (> 30 dB) and small pulse duration is demonstrated. A FBG with a very large group delay disperses the generated pulses and subsequently uses this CW like signal to re-inject the laser diode negating the need to tune the repetition rate for optimum gain-switching operation. The access network provides the last communication link between the customer’s premises and the first switching node in the network. FTTH systems should take advantage of directly modulated sources; therefore the direct modulation of a SG DBR tuneable laser is investigated. Although a directly modulated TL is ideal for reconfigurable access based networks, the modulation itself leads to a drift in operating frequency which may result in cross channel interference in a WDM network. This effect is investigated and also a possible solution to compensate the frequency drift through simultaneous modulation of the lasers phase section is examined