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

Quantum Key Distribution

This chapter describes the application of lasers, specifically diode lasers, in the area of quantum key distribution (QKD). First, we motivate the distribution of cryptographic keys based on quantum physical properties of light, give a brief introduction to QKD assuming the reader has no or very little knowledge about cryptography, and briefly present the state-of-the-art of QKD. In the second half of the chapter we describe, as an example of a real-world QKD system, the system deployed between the University of Calgary and SAIT Polytechnic. We conclude the chapter with a brief discussion of quantum networks and future steps.Comment: 20 pages, 12 figure

Advanced DSP Techniques for High-Capacity and Energy-Efficient Optical Fiber Communications

The rapid proliferation of the Internet has been driving communication networks closer and closer to their limits, while available bandwidth is disappearing due to an ever-increasing network load. Over the past decade, optical fiber communication technology has increased per fiber data rate from 10 Tb/s to exceeding 10 Pb/s. The major explosion came after the maturity of coherent detection and advanced digital signal processing (DSP). DSP has played a critical role in accommodating channel impairments mitigation, enabling advanced modulation formats for spectral efficiency transmission and realizing flexible bandwidth. This book aims to explore novel, advanced DSP techniques to enable multi-Tb/s/channel optical transmission to address pressing bandwidth and power-efficiency demands. It provides state-of-the-art advances and future perspectives of DSP as well

Transmissores-recetores de baixa complexidade para redes óticas

Traditional coherent (COH) transceivers allow encoding of information in both quadratures and the two orthogonal polarizations of the electric field. Nevertheless, such transceivers used today are based on the intradyne scheme, which requires two 90o optical hybrids and four pairs of balanced photodetectors for dual-polarization transmission systems, making its overall cost unattractive for short-reach applications. Therefore, SSB methods with DD reception, commonly referred to as self-coherent (SCOH) transceivers, can be employed as a cost-effective alternative to the traditional COH transceivers. Nevertheless, the performance of SSB systems is severely degraded. This work provides a novel SCOH transceiver architecture with improved performance for short-reach applications. In particular, the development of phase reconstruction digital signal processing (DSP) techniques, the development of other DSP subsystems that relax the hardware requirement, and their performance optimization are the main highlights of this research. The fundamental principle of the proposed transceiver is based on the reception of the signal that satisfies the minimum phase condition upon DD. To reconstruct the missing phase information imposed by DD, a novel DCValue method exploring the SSB and the DC-Value properties of the minimum phase signal is developed in this Ph.D. study. The DC-Value method facilitates the phase reconstruction process at the Nyquist sampling rate and requires a low intensity pilot signal. Also, the experimental validation of the DC-Value method was successfully carried out for short-reach optical networks. Additionally, an extensive study was performed on the DC-Value method to optimize the system performance. In the optimization process, it was found that the estimation of the CCF is an important parameter to exploit all advantages of the DC-Value method. A novel CCF estimation technique was proposed. Further, the performance of the DC-Value method is optimized employing the rate-adaptive probabilistic constellation shaping.Os sistemas de transcetores coerentes tradicionais permitem a codificação de informação em ambas quadraturas e em duas polarizações ortogonais do campo elétrico. Contudo, estes transcetores utilizados atualmente são baseados num esquema intradino, que requer dois híbridos óticos de 90o e quatro pares de foto detetores para sistemas de transmissão com polarização dupla, fazendo com que o custo destes sistemas seja pouco atrativo para aplicações de curto alcance. Por isso, métodos de banda lateral única com deteção direta, também referidos como transcetores coerentes simplificados, podem ser implementados como uma alternativa de baixo custo aos sistemas coerentes tradicionais. Contudo, o desempenho de sistemas de banda lateral única tradicionais é gravemente degradado pelo batimento sinal-sinal. Nesta tese foi desenvolvida uma nova arquitetura de transcetor coerente simplificada com um melhor desempenho para aplicações de curto alcance. Em particular, o desenvolvimento de técnicas de processamento digital de sinal para a reconstrução de fase, bem como de outros subsistemas de processamento digital de sinal que minimizem os requerimentos de hardware e a sua otimização de desempenho são o foco principal desta tese. O princípio fundamental do transcetor proposto é baseado na receção de um sinal que satisfaz a condição mínima de fase na deteção direta. Para reconstruir a informação de fase em falta causada pela deteção direta, um novo método de valor DC que explora sinais de banda lateral única e as propriedades DC da condição de fase mínima é desenvolvido nesta tese. O método de valor DC facilita a reconstrução da fase à frequência de amostragem de Nyquist e requer um sinal piloto de baixa intensidade. Além disso, a validação experimental do método de valor DC foi executada com sucesso em ligações óticas de curto alcance. Adicionalmente, foi realizado um estudo intensivo do método de valor DC para otimizar o desempenho do sistema. Neste processo de otimização, verificou-se que o fator de contribuição da portadora é um parâmetro importante para explorar todas as vantagens do método de valor DC. Neste contexto, é proposto um novo método para a sua estimativa. Por último, o desempenho do método de valor DC é otimizado recorrendo a mapeamento probabilístico de constelação com taxa adaptativa.Programa Doutoral em Engenharia Eletrotécnic

Cognitive and Autonomous Software-Defined Open Optical Networks

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

Advanced DSP for coherent optical fiber communication

In this paper, we provide an overview of recent progress on advanced digital signal processing (DSP) techniques for high-capacity long-haul coherent optical fiber transmission systems. Not only the linear impairments existing in optical transmission links need to be compensated, but also, the nonlinear impairments require proper algorithms for mitigation because they become major limiting factors for long-haul large-capacity optical transmission systems. Besides the time domain equalization (TDE), the frequency domain equalization (FDE) DSP also provides a similar performance, with a much-reduced computational complexity. Advanced DSP also plays an important role for the realization of space division multiplexing (SDM). SDM techniques have been developed recently to enhance the system capacity by at least one order of magnitude. Some impressive results have been reported and have outperformed the nonlinear Shannon limit of the single-mode fiber (SMF). SDM introduces the space dimension to the optical fiber communication. The few-mode fiber (FMF) and multi-core fiber (MCF) have been manufactured for novel multiplexing techniques such as mode-division multiplexing (MDM) and multi-core multiplexing (MCM). Each mode or core can be considered as an independent degree of freedom, but unfortunately, signals will suffer serious coupling during the propagation. Multi-input−multi-output (MIMO) DSP can equalize the signal coupling and makes SDM transmission feasible. The machine learning (ML) technique has attracted worldwide attention and has been explored for advanced DSP. In this paper, we firstly introduce the principle and scheme of coherent detection to explain why the DSP techniques can compensate for transmission impairments. Then corresponding technologies related to the DSP, such as nonlinearity compensation, FDE, SDM and ML will be discussed. Relevant techniques will be analyzed, and representational results and experimental verifications will be demonstrated. In the end, a brief conclusion and perspective will be provided

Machine Learning for Multi-Layer Open and Disaggregated Optical Networks

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

Advanced Technique and Future Perspective for Next Generation Optical Fiber Communications

Optical fiber communication industry has gained unprecedented opportunities and achieved rapid progress in recent years. However, with the increase of data transmission volume and the enhancement of transmission demand, the optical communication field still needs to be upgraded to better meet the challenges in the future development. Artificial intelligence technology in optical communication and optical network is still in its infancy, but the existing achievements show great application potential. In the future, with the further development of artificial intelligence technology, AI algorithms combining channel characteristics and physical properties will shine in optical communication. This reprint introduces some recent advances in optical fiber communication and optical network, and provides alternative directions for the development of the next generation optical fiber communication technology

Self-Evaluation Applied Mathematics 2003-2008 University of Twente

This report contains the self-study for the research assessment of the Department of Applied Mathematics (AM) of the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) at the University of Twente (UT). The report provides the information for the Research Assessment Committee for Applied Mathematics, dealing with mathematical sciences at the three universities of technology in the Netherlands. It describes the state of affairs pertaining to the period 1 January 2003 to 31 December 2008

PSO Algorithm Based Resource Allocation for OFDM Cognitive Radio

With the development of remote correspondences, the issue of data transmission lack has turned out to be more conspicuous. Then again, to sense the presence of authorized clients, range detecting procedures are utilized. Vitality recognition, Matched channel identification and Cyclo-stationary component location are the three ordinary techniques utilized for range detecting. However there are a few downsides of these strategies. The execution of vitality indicator is helpless to instability in noise power. Coordinated channel range detecting strategies require a devoted collector for each essential client. Cyclo-stationary element Detection requires parcel of calculation exertion and long perception time. This proposition talks about the routine vitality location strategy and proposed enhanced vitality identification technique utilizing cubing operation. Additionally, cyclic prefix based range detecting is talked about in this theory. Scientific Description of vitality location and cyclic prefix based range detecting strategies is likewise delineated for fading channels