Mode-dependent Loss and Gain Emulation in Coupled SDM Transmission

Space-division multiplexing (SDM) is currently the only solution to cope with the exponential growth of data traffic in optical transmission networks. The performance of long-haul SDM transmission is fundamentally limited by mode-dependent loss (MDL) and mode-dependent gain (MDG) generated in components and amplifiers. To enable the study of MDL/MDG effects in SDM systems as well as MDL/MDG estimation methods within the context of experimental setups, we evaluate an MDL/MDG emulator based on variable optical attenuators (VOAs) and photonic lanterns. We assess MDL/MDG emulation in different attenuation scenarios and demonstrate the capability of the emulator to artificially introduce a wide range of MDL/MDG in a short-reach 3-mode transmission system

Transition technologies towards 6G networks

[EN] The sixth generation (6G) mobile systems will create new markets, services, and industries making possible a plethora of new opportunities and solutions. Commercially successful rollouts will involve scaling enabling technologies, such as cloud radio access networks, virtualization, and artificial intelligence. This paper addresses the principal technologies in the transition towards next generation mobile networks. The convergence of 6G key-performance indicators along with evaluation methodologies and use cases are also addressed. Free-space optics, Terahertz systems, photonic integrated circuits, softwarization, massive multiple-input multiple-output signaling, and multi-core fibers, are among the technologies identified and discussed. Finally, some of these technologies are showcased in an experimental demonstration of a mobile fronthaul system based on millimeter 5G NR OFDM signaling compliant with 3GPP Rel. 15. The signals are generated by a bespoke 5G baseband unit and transmitted through both a 10 km prototype multi-core fiber and 4 m wireless V-band link using a pair of directional 60 GHz antennas with 10 degrees beamwidth. Results shown that the 5G and beyond fronthaul system can successfully transmit signals with both wide bandwidth (up to 800 MHz) and fully centralized signal processing. As a result, this system can support large capacity and accommodate several simultaneous users as a key candidate for next generation mobile networks. Thus, these technologies will be needed for fully integrated, heterogeneous solutions to benefit from hardware commoditization and softwarization. They will ensure the ultimate user experience, while also anticipating the quality-of-service demands that future applications and services will put on 6G networks.This work was partially funded by the blueSPACE and 5G-PHOS 5G-PPP phase 2 projects, which have received funding from the European Union's Horizon 2020 programme under Grant Agreements Number 762055 and 761989. D. PerezGalacho acknowledges the funding of the Spanish Science Ministry through the Juan de la Cierva programme.Raddo, TR.; Rommel, S.; Cimoli, B.; Vagionas, C.; Pérez-Galacho, D.; Pikasis, E.; Grivas, E.... (2021). Transition technologies towards 6G networks. EURASIP Journal on Wireless Communications and Networking. 2021(1):1-22. https://doi.org/10.1186/s13638-021-01973-91222021

Algoritmos de machine learning para minimización de errores y caracterización de distorsiones en sistemas Nyquist-WDM

RESUMEN: La necesidad de incrementar la velocidad de transmisión en los sistemas de comunicaciones ópticas debido al aumento en la demanda de datos por parte de los usuarios finales ha dado el surgimiento al paradigma conocido como redes ópticas elásticas. Estas redes, principalmente basadas en sistemas Nyquist-WDM, permiten el aumento de la eficiencia espectral resultando en mayor capacidad de transmisión. Sin embargo, el espaciamiento reducido entre los canales ópticos generados en estas redes, resulta en Interferencia Inter-Canal (ICI, del inglés Inter-Channel Interference). Este fenómeno se ha modelado como ruido Gaussiano. Por lo tanto, su mitigación y diagnóstico es una tarea compleja que es actualmente investigado. Técnicas basadas en algoritmos de aprendizaje automático (en inglés Machine Learning) han surgido como herramientas para monitoreo y mitigación de diferentes efectos que ocurren en sistemas de comunicaciones ópticas. En este trabajo de grado, se proponen 2 técnicas para diagnosticar la ICI. La primera técnica se basa en el algoritmo Fuzzy c-Means (FCM) junto con el algoritmo K-Nearest Neighbors (KNN) para estimar el porcentaje de traslape espectral. La segunda técnica se basa en el cálculo de histogramas de la señal en fase y cuadratura, y posterior estimación de traslape espectral apoyado del algoritmo KNN. Se lograron porcentajes de acierto de hasta 92% y 70%, respectivamente para cada técnica. Para mitigación de la ICI, se aplicaron los algoritmos k-Means y KNN, donde, en escenarios simulados se alcanzaron ganancias de hasta 2 dB en términos de señal a ruido óptico (OSNR, del inglés Optical Signal to Noise Ratio) y para escenarios experimentales, se obtuvieron ganancias de hasta 1.3 dB. Finalmente, se pudo concluir que técnicas basadas en algoritmos de aprendizaje automático podrán ser útiles tanto para monitoreo de red, por ejemplo, para controlar frecuencias de las portadoras en futuros sistemas Nyquist-WDM, así como para la mitigación de diferentes fenómenos lineales y no lineales que afectan la transmisión de señales ópticas

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

Algorithms for propagation-aware underwater ranging and localization

Mención Internacional en el título de doctorWhile oceans occupy most of our planet, their exploration and conservation are one of the crucial research problems of modern time. Underwater localization stands among the key issues on the way to the proper inspection and monitoring of this significant part of our world. In this thesis, we investigate and tackle different challenges related to underwater ranging and localization. In particular, we focus on algorithms that consider underwater acoustic channel properties. This group of algorithms utilizes additional information about the environment and its impact on acoustic signal propagation, in order to improve the accuracy of location estimates, or to achieve a reduced complexity, or a reduced amount of resources (e.g., anchor nodes) compared to traditional algorithms. First, we tackle the problem of passive range estimation using the differences in the times of arrival of multipath replicas of a transmitted acoustic signal. This is a costand energy- effective algorithm that can be used for the localization of autonomous underwater vehicles (AUVs), and utilizes information about signal propagation. We study the accuracy of this method in the simplified case of constant sound speed profile (SSP) and compare it to a more realistic case with various non-constant SSP. We also propose an auxiliary quantity called effective sound speed. This quantity, when modeling acoustic propagation via ray models, takes into account the difference between rectilinear and non-rectilinear sound ray paths. According to our evaluation, this offers improved range estimation results with respect to standard algorithms that consider the actual value of the speed of sound. We then propose an algorithm suitable for the non-invasive tracking of AUVs or vocalizing marine animals, using only a single receiver. This algorithm evaluates the underwater acoustic channel impulse response differences induced by a diverse sea bottom profile, and proposes a computationally- and energy-efficient solution for passive localization. Finally, we propose another algorithm to solve the issue of 3D acoustic localization and tracking of marine fauna. To reach the expected degree of accuracy, more sensors are often required than are available in typical commercial off-the-shelf (COTS) phased arrays found, e.g., in ultra short baseline (USBL) systems. Direct combination of multiple COTS arrays may be constrained by array body elements, and lead to breaking the optimal array element spacing, or the desired array layout. Thus, the application of state-of-the-art direction of arrival (DoA) estimation algorithms may not be possible. We propose a solution for passive 3D localization and tracking using a wideband acoustic array of arbitrary shape, and validate the algorithm in multiple experiments, involving both active and passive targets.Part of the research in this thesis has been supported by the EU H2020 program under project SYMBIOSIS (G.A. no. 773753).This work has been supported by IMDEA Networks InstitutePrograma de Doctorado en Ingeniería Telemática por la Universidad Carlos III de MadridPresidente: Paul Daniel Mitchell.- Secretario: Antonio Fernández Anta.- Vocal: Santiago Zazo Bell

Maximising Achievable Rates of Experimental Nonlinear Optical Fibre Transmission Systems

It is generally expected that the demand for digital data services will continue to grow, placing ever greater requirements on optical fibre networks which carry the bulk of digital data. Research to maximise achievable information rates (AIR) over fibre has led to increasing spectral efficiency, symbol rate and bandwidth use. All of these contribute to transmission impairments due to the nonlinear nature of the optical fibre. This thesis describes research performed to investigate the effects of nonlinear impair- ments on the AIRs of experimental optical fibre transmission. To maximise throughput, the entire available optical bandwidth should be filled with transmission channels. An investigation into large bandwidth transmission through the use of spectrally shaped amplified spontaneous emission noise (SS-ASE) was con- ducted. The enhanced Gaussian noise model is used to analytically describe this tech- nique, and SS-ASE was experimentally shown to provide a lower bound on the AIR. Nonlinear interference (NLI) was modelled from an inter-symbol interference (ISI) model to characterise the noise and was experimentally verified. This new understand- ing helps quantify potential gain available from nonlinearity mitigation. Multicore fibres offer an alternative route to improve AIR, and are susceptible to another noise source known as crosstalk. This inter-core crosstalk can be controlled by suitable design of the fibre, hence in the limiting case, NLI rather than crosstalk will limit AIR. Nonlinearity compensation was, for the first time, experimentally demon- strated in the presence of crosstalk in a homogeneous 7-core fibre and shown to provide an increase in AIR. The results of this thesis can be used to evaluate future transmission systems for maximising information rates. It was shown that experimentally, SS-ASE is a viable transmission tool to evaluate system performance, NLI can be characterised using an ISI model and nonlinearity mitigation is possible in MCF systems limited by crosstalk