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

High Capacity Mode Division Multiplexing Based MIMO Enabled All-Optical Analog Millimeter-Wave Over Fiber Fronthaul Architecture for 5G and Beyond

The ever-increasing proliferation of mobile users and new technologies, and the demands for ubiquitous connectivity, high data capacity, faster data speed, low latency, and reliable services have been driven the quest for the next generation, fifth generation (5G), of the wireless networks. Cloud radio access network (C-RAN) has been identified as a promising architecture for addressing 5G requirements. However, C-RAN enforces stringent requirements on the fronthaul capacity and latency. To this end, several fronthaul solutions have been proposed in the literature, ranging from transporting digitized radio signals over fiber and functional splits to an entirely analog-radio-over fiber (A-RoF) based fronthual. A-RoF is a highly appealing transport solution for fronthual of 5G and beyond owing to its high bandwidth and energy efficiency, low system complexity, small footprint, cost-effectiveness, and low latency. In this paper, a high capacity multiple-input-multiple-output (MIMO) enabled all-optical analog-millimeter-wave-over fiber (A-MMWoF) fronthaul architecture is proposed for 5G and beyond of wireless networks. The proposed architecture employs photonic MMW signals generation and mode division multiplexing (MDM) along with wavelength division multiplexing (WDM) for transporting MMW MIMO signals in the optical domain. In support of the proposed architecture design, a comprehensive state-of-the-art literature review on the recent research works in high capacity A-RoF fronthaul systems and related transport technologies is presented. In addition, the corresponding potential challenges and solutions along with potential future directions are highlighted. The proposed design is flexible and scalable for achieving high capacity, high speed, and low latency fronthaul links

Enabling Technology in Optical Fiber Communications: From Device, System to Networking

This book explores the enabling technology in optical fiber communications. It focuses on the state-of-the-art advances from fundamental theories, devices, and subsystems to networking applications as well as future perspectives of optical fiber communications. The topics cover include integrated photonics, fiber optics, fiber and free-space optical communications, and optical networking

High Sensitivity Optical Fiber Interferometric Sensors

Optical fiber interferometers have been widely employed and investigated for monitoring the changes in both physical and chemical parameters, with the advantages of compact size, light weight, immunity to electromagnetic interference, high sensitivity, capability to work in harsh environments and remote operation capabilities. Among the different kinds of fiber sensors based on interferometry, singlemode-multimode-singlemode (SMS) structures has attracted considerable interest due to their inherent advantages of high sensitivity, ease of fabrication and interconnection to other fiber systems and low cost. However, the challenge is that the sensitivity of the traditional SMS based fiber structure is not sufficient in some cases, for example in bio-chemical applications, where detection of a very small variation in a bio-chemicals’ concentration is required. There is thus a need to investigate how to modify or enhance an SMS structure to achieve ultrahigh sensitivity. This thesis presents research and its applications concerning approaches to improve the sensitivity and detection accuracy of a traditional SMS fiber structure based sensor. The key achievements of this thesis include: Traditional SMS fiber structure for breathing state monitoring A bend SMS structure is investigated as a breathing sensor by attaching it to a thin plastic film in an oxygen mask. Breath rate can be monitored using this sensor by detecting power variations due to the macro bending applied to the SMS section during each inhalation and exhalation cycles. Different types of breathing conditions including regular and irregular breath patterns can be distinguished. The proposed sensor is capable of working in a strong electromagnetic field and radioactive environment. Tapered small core singlemode fiber (SCSMF) for the detection of refractive index (RI), ammonia, and volatile organic compounds (VOCs) A modified SMS structure based on a tapered SCSMF is proposed and investigated with significantly improved RI sensitivity. It is found that the sample with a smaller waist diameter gives higher sensitivity. In the experiment, a maximum sensitivity of 19212.5 nm/RIU (RI unit) in the RI range from 1.4304 to 1.4320 has been demonstrated when the waist diameter of the SCSMF is tapered down to 12.5 μm. The best corresponding theoretical resolution of the proposed sensor is 5.025 × 10-7 RIU which is over 10 times higher than that of many previous reported optical fiber based RI sensors. The proposed structure is capable of monitoring relative humidity level change even without coating of the fiber sensor’s surface with a layer of hygroscopic material. A silica sol-gel based coating has been used as a sensitive material to ammonia for the first time, by applying it to the surface of the tapered SCSMF for the detection of ammonia in water. The proposed sensor shows an ultra-high sensitivity of 2.47 nm/ppm with short response and recovery time of less than 2 and 5 minutes respectively. The corresponding theoretical detection limit of ammonia in water is calculated to be 4 ppb, which is 3 orders of magnitude improvement compared to the previous reported interferometry based ammonia sensor. In addition, the sensor has good performance in terms of repeatability of measurement and selectivity for sensing ammonia compared to that of other common ions and organic molecules in water. VOCs sensors are also demonstrated by coating a mixture of sol-gel silica and Nile red on the surface of two different types of tapered fiber sensors (tapered SCSMF) and a microfiber coupler (MFC)). The MFC based sensor shows better sensitivities to ethanol and methanol than that based on a tapered SCSMF due to its smaller waist diameter. The detectable gas concentration changes of the MFC based sensor are calculated to be ~77 ppb and ~281 ppb for ethanol and methanol respectively which are over one order of magnitude improvement than many other reports. The sensors also show fast response times of less than 5 minutes and recovery times varied from 7 to 12 minutes. Simultaneous measurement of ethanol and methanol is achieved by utilizing two different coating recipes. Hollow core fiber (HCF) structure for high temperature and twist sensing. A modified SMS structure with much improved spectral quality factor (Q) is investigated both theoretically and experimentally. The modified structure is based on a HCF. It is found that periodic transmission dips with high spectral extinction ratio and high Q factor are excited because of the multiple beam interferences introduced by the cladding of the HCF. The HCF structure can be used as a high sensitivity (up to 33.4 pm/°C) temperature sensor in a wide working temperature range (from room temperature to 1000 °C). By coating a thin layer of silver (~ 6.7 nm) on one side of the HCF surface, a twist sensor with a maximum sensitivity of 0.717 dB/°has been achieved, which is the highest twist sensitivity reported for intensity modulation based fiber sensors, with excellent measurement repeatability. Further theoretical and experimental investigation attributes this high twist sensitivity to the polarization dependent reflection coefficient at the outer HCF surface associated with the partial silver coating

Sistemas de posicionamento baseados em comunicação por luz para ambientes interiores

The demand for highly precise indoor positioning systems (IPSs) is growing rapidly due to its potential in the increasingly popular techniques of the Internet of Things, smart mobile devices, and artificial intelligence. IPS becomes a promising research domain that is getting wide attention due to its benefits in several working scenarios, such as, industries, indoor public locations, and autonomous navigation. Moreover, IPS has a prominent contribution in day-to-day activities in organizations such as health care centers, airports, shopping malls, manufacturing, underground locations, etc., for safe operating environments. In indoor environments, both radio frequency (RF) and optical wireless communication (OWC) based technologies could be adopted for localization. Although the RF-based global positioning system, such as, Global positioning system offers higher penetration rates with reduced accuracy (i.e., in the range of a few meters), it does not work well in indoor environments (and not at all in certain cases such as tunnels, mines, etc.) due to the very weak signal and no direct access to the satellites. On the other hand, the light-based system known as a visible light positioning (VLP) system, as part of the OWC systems, uses the pre-existing light-emitting diodes (LEDs)-based lighting infrastructure, could be used at low cost and high accuracy compared with the RF-based systems. VLP is an emerging technology promising high accuracy, high security, low deployment cost, shorter time response, and low relative complexity when compared with RFbased positioning. However, in indoor VLP systems, there are some concerns such as, multipath reflection, transmitter tilting, transmitter’s position, and orientation uncertainty, human shadowing/blocking, and noise causing the increase in the positioning error, thereby reducing the positioning accuracy of the system. Therefore, it is imperative to capture the characteristics of different VLP channel and properly model them for the dual purpose of illumination and localization. In this thesis, firstly, the impact of transmitter tilting angles and multipath reflections are studied and for the first time, it is demonstrated that tilting the transmitter can be beneficial in VLP systems considering both line of sight (LOS) and non-line of sight transmission paths. With the transmitters oriented towards the center of the receiving plane, the received power level is maximized due to the LOS components. It is also shown that the proposed scheme offers a significant accuracy improvement of up to ~66% compared with a typical non-tilted transmitter VLP. The effect of tilting the transmitter on the lighting uniformity is also investigated and results proved that the uniformity achieved complies with the European Standard EN 12464-1. After that, the impact of transmitter position and orientation uncertainty on the accuracy of the VLP system based on the received signal strength (RSS) is investigated. Simulation results show that the transmitter uncertainties have a severe impact on the positioning error, which can be leveraged through the usage of more transmitters. Concerning a smaller transmitter’s position epochs, and the size of the training set. It is shown that, the ANN with Bayesian regularization outperforms the traditional RSS technique using the non-linear least square estimation for all values of signal to noise ratio. Furthermore, a novel indoor VLP system is proposed based on support vector machines and polynomial regression considering two different multipath environments of an empty room and a furnished room. The results show that, in an empty room, the positioning accuracy improvement for the positioning error of 2.5 cm are 36.1, 58.3, and 72.2 % for three different scenarios according to the regions’ distribution in the room. For the furnished room, a positioning relative accuracy improvement of 214, 170, and 100 % is observed for positioning error of 0.1, 0.2, and 0.3 m, respectively. Ultimately, an indoor VLP system based on convolutional neural networks (CNN) is proposed and demonstrated experimentally in which LEDs are used as transmitters and a rolling shutter camera is used as receiver. A detection algorithm named single shot detector (SSD) is used which relies on CNN (i.e., MobileNet or ResNet) for classification as well as position estimation of each LED in the image. The system is validated using a real-world size test setup containing eight LED luminaries. The obtained results show that the maximum average root mean square positioning error achieved is 4.67 and 5.27 cm with SSD MobileNet and SSD ResNet models, respectively. The validation results show that the system can process 67 images per second, allowing real-time positioning.A procura por sistemas de posicionamento interior (IPSs) de alta precisão tem crescido rapidamente devido ao seu interesse nas técnicas cada vez mais populares da Internet das Coisas, dispositivos móveis inteligentes e inteligência artificial. O IPS tornou-se um domínio de pesquisa promissor que tem atraído grande atenção devido aos seus benefícios em vários cenários de trabalho, como indústrias, locais públicos e navegação autónoma. Além disso, o IPS tem uma contribuição destacada no dia a dia de organizações, como, centros de saúde, aeroportos, supermercados, fábricas, locais subterrâneos, etc. As tecnologias baseadas em radiofrequência (RF) e comunicação óptica sem fio (OWC) podem ser adotadas para localização em ambientes interiores. Embora o sistema de posicionamento global (GPS) baseado em RF ofereça taxas de penetração mais altas com precisão reduzida (ou seja, na faixa de alguns metros), não funciona bem em ambientes interiores (e não funciona bem em certos casos como túneis, minas, etc.) devido ao sinal muito fraco e falta de acesso direto aos satélites. Por outro lado, o sistema baseado em luz conhecido como sistema de posicionamento de luz visível (VLP), como parte dos sistemas OWC, usa a infraestrutura de iluminação baseada em díodos emissores de luz (LEDs) pré-existentes, é um sistemas de baixo custo e alta precisão quando comprado com os sistemas baseados em RF. O VLP é uma tecnologia emergente que promete alta precisão, alta segurança, baixo custo de implantação, menor tempo de resposta e baixa complexidade relativa quando comparado ao posicionamento baseado em RF. No entanto, os sistemas VLP interiores, exibem algumas limitações, como, a reflexão multicaminho, inclinação do transmissor, posição do transmissor e incerteza de orientação, sombra/bloqueio humano e ruído, que têm como consequência o aumento do erro de posicionamento, e consequente redução da precisão do sistema. Portanto, é imperativo estudar as características dos diferentes canais VLP e modelá-los adequadamente para o duplo propósito de iluminação e localização. Esta tesa aborda, primeiramente, o impacto dos ângulos de inclinação do transmissor e reflexões multipercurso no desempenho do sistema de posicionamento. Demonstra-se que a inclinação do transmissor pode ser benéfica em sistemas VLP considerando tanto a linha de vista (LOS) como as reflexões. Com os transmissores orientados para o centro do plano recetor, o nível de potência recebido é maximizado devido aos componentes LOS. Também é mostrado que o esquema proposto oferece uma melhoria significativa de precisão de até ~66% em comparação com um sistema VLP de transmissor não inclinado típico. O efeito da inclinação do transmissor na uniformidade da iluminação também é investigado e os resultados comprovam que a uniformidade alcançada está de acordo com a Norma Europeia EN 12464-1. O impacto da posição do transmissor e incerteza de orientação na precisão do sistema VLP com base na intensidade do sinal recebido (RSS) foi também investigado. Os resultados da simulação mostram que as incertezas do transmissor têm um impacto severo no erro de posicionamento, que pode ser atenuado com o uso de mais transmissores. Para incertezas de posicionamento dos transmissores menores que 5 cm, os erros médios de posicionamento são 23.3, 15.1 e 13.2 cm para conjuntos de 4, 9 e 16 transmissores, respetivamente. Enquanto que, para a incerteza de orientação de um transmissor menor de 5°, os erros médios de posicionamento são 31.9, 20.6 e 17 cm para conjuntos de 4, 9 e 16 transmissores, respetivamente. O trabalho da tese abordou a investigação dos aspetos de projeto de um sistema VLP indoor no qual uma rede neuronal artificial (ANN) é utilizada para estimativa de posicionamento considerando um canal multipercurso. O estudo considerou a influência do ruído como indicador de desempenho para a comparação entre diferentes abordagens de projeto. Três algoritmos de treino de ANNs diferentes foram considerados, a saber, Levenberg-Marquardt, regularização Bayesiana e algoritmos de gradiente conjugado escalonado, para minimizar o erro de posicionamento no sistema VLP. O projeto da ANN foi otimizado com base no número de neurónios nas camadas ocultas, no número de épocas de treino e no tamanho do conjunto de treino. Mostrou-se que, a ANN com regularização Bayesiana superou a técnica RSS tradicional usando a estimação não linear dos mínimos quadrados para todos os valores da relação sinal-ruído. Foi proposto um novo sistema VLP indoor baseado em máquinas de vetores de suporte (SVM) e regressão polinomial considerando dois ambientes interiores diferentes: uma sala vazia e uma sala mobiliada. Os resultados mostraram que, numa sala vazia, a melhoria da precisão de posicionamento para o erro de posicionamento de 2.5 cm são 36.1, 58.3 e 72.2% para três cenários diferentes de acordo com a distribuição das regiões na sala. Para a sala mobiliada, uma melhoria de precisão relativa de posicionamento de 214, 170 e 100% é observada para erro de posicionamento de 0.1, 0.2 e 0.3 m, respetivamente. Finalmente, foi proposto um sistema VLP indoor baseado em redes neurais convolucionais (CNN). O sistema foi demonstrado experimentalmente usando luminárias LED como transmissores e uma camara com obturador rotativo como recetor. O algoritmo de detecção usou um detector de disparo único (SSD) baseado numa CNN pré configurada (ou seja, MobileNet ou ResNet) para classificação. O sistema foi validado usando uma configuração de teste de tamanho real contendo oito luminárias LED. Os resultados obtidos mostraram que o erro de posicionamento quadrático médio alcançado é de 4.67 e 5.27 cm com os modelos SSD MobileNet e SSD ResNet, respetivamente. Os resultados da validação mostram que o sistema pode processar 67 imagens por segundo, permitindo o posicionamento em tempo real.Programa Doutoral em Engenharia Eletrotécnic