4. generációs mobil rendszerek kutatása = Research on 4-th Generation Mobile Systems

A 3G mobil rendszerek szabványosítása a végéhez közeledik, legalábbis a meghatározó képességek tekintetében. Ezért létfontosságú azon technikák, eljárások vizsgálata, melyek a következő, 4G rendszerekben meghatározó szerepet töltenek majd be. Több ilyen kutatási irányvonal is létezik, ezek közül projektünkben a fontosabbakra koncentráltunk. A következőben felsoroljuk a kutatott területeket, és röviden összegezzük az elért eredményeket. Szórt spektrumú rendszerek Kifejlesztettünk egy új, rádiós interfészen alkalmazható hívásengedélyezési eljárást. Szimulációs vizsgálatokkal támasztottuk alá a megoldás hatékonyságát. A projektben kutatóként résztvevő Jeney Gábor sikeresen megvédte Ph.D. disszertációját neurális hálózatokra épülő többfelhasználós detekciós technikák témában. Az elért eredmények Imre Sándor MTA doktori disszertációjába is beépültek. IP alkalmazása mobil rendszerekben Továbbfejlesztettük, teszteltük és általánosítottuk a projekt keretében megalkotott új, gyűrű alapú topológiára épülő, a jelenleginél nagyobb megbízhatóságú IP alapú hozzáférési koncepciót. A témakörben Szalay Máté Ph.D. disszertációja már a nyilvános védésig jutott. Kvantum-informatikai módszerek alkalmazása 3G/4G detekcióra Új, kvantum-informatikai elvekre épülő többfelhasználós detekciós eljárást dolgoztunk ki. Ehhez új kvantum alapú algoritmusokat is kifejlesztettünk. Az eredményeket nemzetközi folyóiratok mellett egy saját könyvben is publikáltuk. | The project consists of three main research directions. Spread spectrum systems: we developed a new call admission control method for 3G air interfaces. Project member Gabor Jeney obtained the Ph.D. degree and project leader Sandor Imre submitted his DSc theses from this area. Application of IP in mobile systems: A ring-based reliable IP mobility mobile access concept and corresponding protocols have been developed. Project member Máté Szalay submitted his Ph.D. theses from this field. Quantum computing based solutions in 3G/4G detection: Quantum computing based multiuser detection algorithm was developed. Based on the results on this field a book was published at Wiley entitled: 'Quantum Computing and Communications - an engineering approach'

Neural networks for optical channel equalization in high speed communication systems

La demande future de bande passante pour les données dépassera les capacités des systèmes de communication optique actuels, qui approchent de leurs limites en raison des limitations de la bande passante électrique des composants de l’émetteur. L’interférence intersymbole (ISI) due à cette limitation de bande est le principal facteur de dégradation pour atteindre des débits de données élevés. Dans ce mémoire, nous étudions plusieurs techniques de réseaux neuronaux (NN) pour combattre les limites physiques des composants de l’émetteur pilotés à des débits de données élevés et exploitant les formats de modulation avancés avec une détection cohérente. Notre objectif principal avec les NN comme égaliseurs de canaux ISI est de surmonter les limites des récepteurs optimaux conventionnels, en fournissant une complexité évolutive moindre et une solution quasi optimale. Nous proposons une nouvelle architecture bidirectionnelle profonde de mémoire à long terme (BiLSTM), qui est efficace pour atténuer les graves problèmes d’ISI causés par les composants à bande limitée. Pour la première fois, nous démontrons par simulation que notre BiLSTM profonde proposée atteint le même taux d’erreur sur les bits(TEB) qu’un estimateur de séquence à maximum de vraisemblance (MLSE) optimal pour la modulation MDPQ. Les NN étant des modèles pilotés par les données, leurs performances dépendent fortement de la qualité des données d’entrée. Nous démontrons comment les performances du BiLSTM profond réalisable se dégradent avec l’augmentation de l’ordre de modulation. Nous examinons également l’impact de la sévérité de l’ISI et de la longueur de la mémoire du canal sur les performances de la BiLSTM profonde. Nous étudions les performances de divers canaux synthétiques à bande limitée ainsi qu’un canal optique mesuré à 100 Gbaud en utilisant un modulateur photonique au silicium (SiP) de 35 GHz. La gravité ISI de ces canaux est quantifiée grâce à une nouvelle vue graphique des performances basée sur les écarts de performance de base entre les solutions optimales linéaires et non linéaires classiques. Aux ordres QAM supérieurs à la QPSK, nous quantifions l’écart de performance BiLSTM profond par rapport à la MLSE optimale à mesure que la sévérité ISI augmente. Alors qu’elle s’approche des performances optimales de la MLSE à 8QAM et 16QAM avec une pénalité, elle est capable de dépasser largement la solution optimale linéaire à 32QAM. Plus important encore, l’avantage de l’utilisation de modèles d’auto-apprentissage comme les NN est leur capacité à apprendre le canal pendant la formation, alors que la MLSE optimale nécessite des informations précises sur l’état du canal.The future demand for the data bandwidth will surpass the capabilities of current optical communication systems, which are approaching their limits due to the electrical bandwidth limitations of the transmitter components. Inter-symbol interference (ISI) due to this band limitation is the major degradation factor to achieve high data rates. In this thesis, we investigate several neural network (NN) techniques to combat the physical limits of the transmitter components driven at high data rates and exploiting the advanced modulation formats with coherent detection. Our main focus with NNs as ISI channel equalizers is to overcome the limitations of conventional optimal receivers, by providing lower scalable complexity and near optimal solution. We propose a novel deep bidirectional long short-term memory (BiLSTM) architecture, that is effective in mitigating severe ISI caused by bandlimited components. For the first time, we demonstrate via simulation that our proposed deep BiLSTM achieves the same bit error rate (BER) performance as an optimal maximum likelihood sequence estimator (MLSE) for QPSK modulation. The NNs being data-driven models, their performance acutely depends on input data quality. We demonstrate how the achievable deep BiLSTM performance degrades with the increase in modulation order. We also examine the impact of ISI severity and channel memory length on deep BiLSTM performance. We investigate the performances of various synthetic band-limited channels along with a measured optical channel at 100 Gbaud using a 35 GHz silicon photonic(SiP) modulator. The ISI severity of these channels is quantified with a new graphical view of performance based on the baseline performance gaps between conventional linear and nonlinear optimal solutions. At QAM orders above QPSK, we quantify deep BiLSTM performance deviation from the optimal MLSE as ISI severity increases. While deep BiLSTM approaches the optimal MLSE performance at 8QAM and 16QAM with a penalty, it is able to greatly surpass the linear optimal solution at 32QAM. More importantly, the advantage of using self learning models like NNs is their ability to learn the channel during the training, while the optimal MLSE requires accurate channel state information

The Primary Role of the Electric Near-Field in Brain Function

The origin and spatial-temporal structure of the endogenous (internal) electric near-fields associated with the neurological network activity of the brain are described. Recent discoveries have elevated the importance of the endogenous fields to a leading role of primary phenomena, as opposed to the traditionally thought secondary role of epiphenomena. This implies that the spatial-temporal structures of the brain’s endogenous fields are rich in information that directly convey brain health. Understanding the spatial-temporal structures of the endogenous fields under healthy and unhealthy conditions coupled with the technologies needed to sense and manage these fields opens a world of possibilities for the rational design of clinically accurate, wearable neurodevices to diagnose, therapeutically treat, and manage chronic neurological dysfunctions, mental disorders, and traumatic injuries. The World Health Organization reports that more than 1 billion people worldwide, irrespective of age, sex, education, or income, suffer because of neurological disorders. Devices of the type described here will provide clarity and relief to those individuals that have an impaired neurological system

2022 roadmap on neuromorphic computing and engineering

Modern computation based on von Neumann architecture is now a mature cutting-edge science. In the von Neumann architecture, processing and memory units are implemented as separate blocks interchanging data intensively and continuously. This data transfer is responsible for a large part of the power consumption. The next generation computer technology is expected to solve problems at the exascale with 10$^{18}$ calculations each second. Even though these future computers will be incredibly powerful, if they are based on von Neumann type architectures, they will consume between 20 and 30 megawatts of power and will not have intrinsic physically built-in capabilities to learn or deal with complex data as our brain does. These needs can be addressed by neuromorphic computing systems which are inspired by the biological concepts of the human brain. This new generation of computers has the potential to be used for the storage and processing of large amounts of digital information with much lower power consumption than conventional processors. Among their potential future applications, an important niche is moving the control from data centers to edge devices. The aim of this roadmap is to present a snapshot of the present state of neuromorphic technology and provide an opinion on the challenges and opportunities that the future holds in the major areas of neuromorphic technology, namely materials, devices, neuromorphic circuits, neuromorphic algorithms, applications, and ethics. The roadmap is a collection of perspectives where leading researchers in the neuromorphic community provide their own view about the current state and the future challenges for each research area. We hope that this roadmap will be a useful resource by providing a concise yet comprehensive introduction to readers outside this field, for those who are just entering the field, as well as providing future perspectives for those who are well established in the neuromorphic computing community

Quantum Machine Learning for 6G Communication Networks: State-of-the-Art and Vision for the Future

The upcoming 5th Generation (5G) of wireless networks is expected to lay a foundation of intelligent networks with the provision of some isolated Artificial Intelligence (AI) operations. However, fully-intelligent network orchestration and management for providing innovative services will only be realized in Beyond 5G (B5G) networks. To this end, we envisage that the 6th Generation (6G) of wireless networks will be driven by on-demand self-reconfiguration to ensure a many-fold increase in the network performanceandservicetypes.Theincreasinglystringentperformancerequirementsofemergingnetworks may finally trigger the deployment of some interesting new technologies such as large intelligent surfaces, electromagnetic-orbital angular momentum, visible light communications and cell-free communications – tonameafew.Ourvisionfor6Gis–amassivelyconnectedcomplexnetworkcapableofrapidlyresponding to the users’ service calls through real-time learning of the network state as described by the network-edge (e.g., base-station locations, cache contents, etc.), air interface (e.g., radio spectrum, propagation channel, etc.), and the user-side (e.g., battery-life, locations, etc.). The multi-state, multi-dimensional nature of the network state, requiring real-time knowledge, can be viewed as a quantum uncertainty problem. In this regard, the emerging paradigms of Machine Learning (ML), Quantum Computing (QC), and Quantum ML (QML) and their synergies with communication networks can be considered as core 6G enablers. Considering these potentials, starting with the 5G target services and enabling technologies, we provide a comprehensivereviewoftherelatedstate-of-the-artinthedomainsofML(includingdeeplearning),QCand QML, and identify their potential benefits, issues and use cases for their applications in the B5G networks. Subsequently,weproposeanovelQC-assistedandQML-basedframeworkfor6Gcommunicationnetworks whilearticulatingitschallengesandpotentialenablingtechnologiesatthenetwork-infrastructure,networkedge, air interface and user-end. Finally, some promising future research directions for the quantum- and QML-assisted B5G networks are identified and discussed

VCSEL-based optical frequency comb generation, expansion and optimization: an experimental study

Esta tesis contiene artículos de investigación en anexoLas fuentes ópticas multimodo o peines en frecuencia (Optical Frequency Comb o OFC) han sido y son objeto de investigación en los últimos años dado que ofrecen numerosas posibilidades en diferentes campos como espectroscopía, comunicaciones ópticas, generación de terahercios, generación de señales arbitrarias ópticas, metrología o generación óptica de señales de radiofrecuencia. Los OFC son sistemas típicamente basados en equipos de sobremesa y componentes a medida, obteniendo sistemas robustos y señales de alta calidad pero difíciles de implementar y reproducir al mismo tiempo. Algunas de las aplicaciones de los OFCs tienen como elementos clave la eficiencia en tamaño, coste y consumo, de manera que es importante obtener combs con capacidades más moderadas pero que, a su vez, sean sistemas más flexibles, compactos y fáciles de implementar. Para ello, centramos nuestra atención en sistemas OFCs realizados con componentes comerciales que sean útiles para aplicaciones como generación de THz o espectroscopía. Para mantener estos objetivos, hemos elegido la generación de combs directa en diodos láser (laser diodes o LDs), dado que el OFC es creado en el interior de la cavidad láser sin necesidad de añadir componentes extra ni aumentar excesivamente la potencia necesaria por el sistema. Entre los diodos láser, los láseres de emisión superficial y cavidad vertical (Vertical-Cavity Surface-Emitting Lasers o VCSELs) son un tipo de láseres de diodo que han experimentado una gran evolución en los últimos años debido a las características que presentan: los VCSELs son dispositivos de bajo coste y pequeño tamaño, por lo que ofrecen la posibilidad de ser modulados a altas frecuencias con muy poco consumo de potencia. En este trabajo se estudiará el uso de láseres VCSEL (1550nm 10Gbps VCSELs fabricados por Vertilas GmbH) como elemento base de los OFCs utilizando una técnica de modulación no lineal conocida como Gain Switching (GS). Gracias a la modulación GS, el comb generado hereda el ruido del equipo usado para la modulación, obteniendo así alta correlación de fase entre sus modos. Con el dispositivo VCSEL bajo GS se ha obtenido un comb de hasta 135GHz de ancho en los 20dB superiores del espectro, llamado VCSEL-OFC. Los resultados presentados en esta Tesis demuestran que el uso de VCSELs permite la generación de combs más anchos y planos que con otras tecnologías y record en bajo consumo de energía. El comportamiento del VCSEL bajo GS se comparará con un sistema similar usando otro tipo de fuente láser que ha sido usado con buenos resultados anteriormente, un láser Discrete Mode, también bajo régimen GS. Sin embargo, el VCSEL-OFC sigue limitando su aplicación en algunos campos de nuestro interés como síntesis de THz o espectroscopía dado que necesitan combs más anchos. Esto fundamentó otro de los aspectos clave de este trabajo: la expansión de los combs, usando el VCSEL-OFC como semilla. Tres técnicas para expandir el VCSEL-OFC han sido implementadas, basándonos en fibras altamente no lineales (Highly Nonlinear Fibers, HNLF), lazos ópticos no lineales (Nonlinear Optical Loop Mirrors, NOLM) y moduladores Electro- Ópticos (EO). Con estos sistemas hemos expandido el comb resultante un factor 3, obteniendo combs de alrededor de 450GHz y manteniendo alta correlación entre modos. Posteriormente, dos de estas etapas de expansión, EO y HNLF, han sido implementadas en cascada para aunar sus efectos y se ha conseguido un comb de 1THz de ancho a 20dB, según nuestro conocimiento, el comb más ancho conseguido usando fuentes VCSELs y tecnologías disponibles comercialmente. Este comb es extraordinariamente ancho pero, sin embargo, necesita ser estudiado con más detalle para mejorar otras de sus características como la igualdad de potencia entre los modos considerados (flatness) o el rango dinámico. Por ello, para profundizar en el conocimiento del VCSEL como fuente para generar combs y así optimizar el VCSEL-OFC y todas sus expansiones implementadas, se ha realizado un estudio más profundo de dicho comb en relación a sus componentes de polarización. Los VCSELs típicamente se consideran fuentes monomodo pero tienen un segundo modo con polarización linear y ortogonal. Este modo es residual y se reduce su efecto durante la fabricación de la cavidad pero hemos comprobado que genera un comb residual, con menor potencia y este comb juega un papel fundamental si se equilibraran las potencias de ambos modos de polarización. Además, el uso de GS para la generación del comb hace que tanto los modos del comb principal como de este comb residual tienen alta correlación de fase. Para equilibrar las potencias de ambos modos de polarización, hemos incluido en nuestros experimentos la técnica de inyección (Optical Injection Locking, OIL) en la que una luz externa se inyecta en el láser para mejorar la señal a la salida. Jugando con la polarización de la señal inyectada, hemos conseguido equilibrar los combs correspondientes a ambos estados de polarización y también suprimir uno de ellos manteniendo únicamente el otro. En conclusión, un tipo de diodo laser de emisión vertical, VCSEL, ha sido evaluado para generación de peines ópticos multifrecuenciales. Para ello, se ha estudiado su comportamiento bajo GS, optimizando el ancho del comb generado. Posteriormente, se han implementado distintas técnicas para expandir y optimizar dichos combs. Los resultados han sido significativos, teniendo en cuenta el ancho del comb con respecto a la potencia necesaria y el coste y complejidad de los sistemas. Los combs basados en VCSELs prometen ser dispositivos a tener en cuenta para implementaciones de combs versátiles y compactos de bajo coste y bajo consumo de energía.Optical Frequency Combs (OFCs) are versatile systems and therefore many researchers have been interested in them during the last years as they open possibilities in a large variety of fields like spectroscopy, optical communications, THz generation, optical arbitrary waveform generation, metrology, or microwave photonic. OFCs systems are typically based on bench top lasers sources, often built with tailored components which make them robust and powerful but complex and difficult to reproduce at the same time. Some of the fields of application of OFCs do not need that bespoke systems but, on the contrary, more straightforward, flexible and compact systems are needed for applications aiming for size, cost and energy efficient set- ups. These features can be further enhanced by using only Off the Shelf components obtaining suitable combs for applications like THz generation or spectroscopy. This is the approach in which our attention is centered. Trying to maintain this idea as the horizon of this work, direct OFC generation in laser diodes (LDs), in which the comb is generated inside the LD cavity, has been the focus of the present work. With such an approach, the component count is not increased and the energy consumption remains low. Among the numerous laser diode technologies available, Vertical-Cavity Surface-Emitting Lasers (VCSELs) are cost effective devices with small size. On top of this, they offer high speed capabilities with a very small amount of injected power. These special features are the reason why, in this work, VCSELs (1550nm 10Gbps VCSELs from Vertilas GmbH) are analyzed as the main source to be used for comb generation based on a well stablished nonlinear radio-frequency modulation technique: Gain Switching (GS). Thanks to the GS regime, an optical comb is generated with a very special feature: its modes inherit the stability of the radio-frequency source used for the laser modulation. Hence, the resulting comb exhibits a very high correlation between its modes. With this, a comb of 135GHz in the 20dB span is generated (VCSEL-OFC). The results presented in this Thesis demonstrate that the use of high performance VCSELs permits the generation of very flat optical combs with enhanced optical span and record energy efficiency. The VCSEL performance to generate OFCs is compared in this study to a different type of LD source: Discrete Mode (DM) laser under GS. The results showed that VCSEL-OFC is significantly broader than the comb obtained with other LD technologies under GS. However, the overall optical span that VCSEL based combs provide still needs to be increased to match the majority of the applications targeted. Especially for THz generation or dual-comb spectroscopy, two of the applications that launched our interest in LD combs, this is an important issue. Finding a way to overcome this limitation was the beginning of another of the key studies presented here. The expansion of the VCSEL-OFC, the seed comb. For this purpose, three different expansion techniques were implemented to increment the total span: Highly Nonlinear Fibers (HNLF), Nonlinear Optical Loop Mirrors (NOLM) and Electro-Optic (EO) Modulators. The resulting combs are 3 times broader than the seed VCSEL-OFC, thus combs around 450GHz in the 20dB span have been achieved maintaining high correlation between the comb lines. Subsequently, two of these expansion techniques, the EO and HNLF, have been cascaded to join their expansion effects and a comb of 1THz in the 20dB span has been generated, which is, to our knowledge, the broadest comb achieved using LDs and off the Shelf components. Even when this comb is remarkably broad some other features should be improved: the flatness and the dynamic range. Then, more efforts should be done to study the nature of the VCSEL-OFC. In order to deepen into the VCSEL knowledge for comb generation, to optimize both the VCSEL-OFC and the expansion stages implemented, polarization dynamics studies on the VCSEL in CW emission and the VCSEL under GS were performed. VCSELs are considered monomode laser sources but they present a residual orthogonally polarized mode whose emission is suppressed during fabrication. However, we observed that this residual mode also generates a comb that could play an important role. Using GS for the generation provides high phase correlation among the teeth in the main comb and also in this orthogonally-polarized residual comb. Trying to achieve a balance between both polarization components, Optical Injection Locking (OIL) was implemented. Playing with the injected state of polarization, the combs correspondent to the two states of polarization in VSCELs were balanced and the resulting comb was slightly broader and flatter. Also, one of the optical combs could be enhanced suppressing the other state of polarization with OIL. To conclude, Vertical-Cavity Surface-Emitting Lasers (VCSELs) have been evaluated for optical frequency comb generation. For this, their behavior under GS has been studied, focusing on the optimization of the optical span. Subsequently, different techniques for comb expansion and optimization have been implemented obtaining remarkable results, taking into account the optical span, the energy needs and the complexity of the set-ups. For all this, VCSELs are devices to be used to build versatile, compact, low cost and low energy consumption comb generation systems.Programa Oficial de Doctorado en Ingeniería Eléctrica, Electrónica y AutomáticaPresidente: Víctor Torres Company.- Secretario: Ana Quirce Teja.- Vocal: Borja Vidal Rodrígue