10 research outputs found
Throughput Maximization for UAV-enabled Integrated Periodic Sensing and Communication
Unmanned aerial vehicle (UAV) is expected to revolutionize the existing
integrated sensing and communication (ISAC) system and promise a more flexible
joint design. Nevertheless, the existing works on ISAC mainly focus on
exploring the performance of both functionalities simultaneously during the
entire considered period, which may ignore the practical asymmetric sensing and
communication requirements. In particular, always forcing sensing along with
communication may make it is harder to balance between these two
functionalities due to shared spectrum resources and limited transmit power. To
address this issue, we propose a new integrated periodic sensing and
communication mechanism for the UAV-enabled ISAC system to provide a more
flexible trade-off between two integrated functionalities. Specifically, the
system achievable rate is maximized via jointly optimizing UAV trajectory, user
association, target sensing selection, and transmit beamforming, while meeting
the sensing frequency and beam pattern gain requirement for the given targets.
Despite that this problem is highly non-convex and involves closely coupled
integer variables, we derive the closed-form optimal beamforming vector to
dramatically reduce the complexity of beamforming design, and present a tight
lower bound of the achievable rate to facilitate UAV trajectory design. Based
on the above results, we propose a penalty-based algorithm to efficiently solve
the considered problem. The optimal achievable rate and the optimal UAV
location are analyzed under a special case of infinity number of antennas.
Furthermore, we prove the structural symmetry between the optimal solutions in
different ISAC frames without location constraints and propose an efficient
algorithm for solving the problem with location constraints.Comment: 32 pages, This work has been submitted to the IEEE for possible
publicatio
Digital Signal Processing for Optical Communications and Coherent LiDAR
Internet data traffic within data centre, access and metro networks is experiencing
unprecedented growth driven by many data-intensive applications. Significant
efforts have been devoted to the design and implementation of low-complexity
digital signal processing (DSP) algorithms that are suitable for these short-reach
optical links. In this thesis, a novel low-complexity frequency-domain (FD)
multiple-input multiple-output (MIMO) equaliser with momentum-based gradient
descent algorithm is proposed, capable of mitigating both static and dynamic
impairments arising from the optical fibre. The proposed frequency-domain
equaliser (FDE) also improves the robustness of the adaptive equaliser against
feedback latencies which is the main disadvantage of FD adaptive equalisers under
rapid channel variations.
The development and maturity of optical fibre communication techniques over
the past few decades have also been beneficial to many other fields, especially
coherent light detection and ranging (LiDAR) techniques. Many applications
of coherent LiDAR are also cost-sensitive, e.g., autonomous vehicles (AVs).
Therefore, in this thesis, a low-cost and low-complexity single-photodiode-based
coherent LiDAR system is investigated. The receiver sensitivity performance of this
receiver architecture is assessed through both simulations and experiments, using
two ranging waveforms known as double-sideband (DSB) amplitude-modulated
chirp signal and single-sideband (SSB) frequency-modulated continuous-wave
(FMCW) signals. Besides, the impact of laser phase noise on the ranging precision
when operating within and beyond the laser coherence length is studied. Achievable
ranging precision beyond the laser coherence length is quantified
Mehrdimensionale Kanalschätzung für MIMO-OFDM
DIGITAL wireless communication started in the 1990s with the wide-spread deployment of GSM. Since then, wireless systems evolved dramatically. Current wireless standards approach the goal of an omnipresent communication system, which fulfils the wish to communicate with anyone, anywhere at anytime. Nowadays, the acceptance of smartphones and/or tablets is huge and the mobile internet is the core application. Given the current growth, the estimated data traffic in wireless networks in 2020 might be 1000 times higher than that of 2010, exceeding 127 exabyte.
Unfortunately, the available radio spectrum is scarce and hence, needs to be utilized efficiently. Key technologies, such as multiple-input multiple-output (MIMO), orthogonal frequency-division multiplexing (OFDM) as well as various MIMO precoding techniques increase the theoretically achievable channel capacity considerably and are used in the majority of wireless standards. On the one hand, MIMO-OFDM promises substantial diversity and/or capacity gains. On the other hand, the complexity of optimum maximum-likelihood detection grows exponentially and is thus, not sustainable. Additionally, the required signaling overhead increases with the number of antennas and thereby reduces the bandwidth efficiency. Iterative receivers which jointly carry out channel estimation and data detection are a potential enabler to reduce the pilot overhead and approach optimum capacity at often reduced complexity.
In this thesis, a graph-based receiver is developed, which iteratively performs joint data detection and channel estimation. The proposed multi-dimensional factor graph introduces transfer nodes that exploit correlation of adjacent channel coefficients in an arbitrary number of dimensions (e.g. time, frequency, and space). This establishes a simple and flexible receiver structure that facilitates soft channel estimation and data detection in multi-dimensional dispersive channels, and supports arbitrary modulation and channel coding schemes. However, the factor graph exhibits suboptimal cycles. In order to reach the maximum performance, the message exchange schedule, the process of combining messages, and the initialization are adapted. Unlike conventional approaches, which merge nodes of the factor graph to avoid cycles, the proposed message combining methods mitigate the impairing effects of short cycles and retain a low computational complexity. Furthermore, a novel detection algorithm is presented, which combines tree-based MIMO detection with a Gaussian detector. The resulting detector, termed Gaussian tree search detection, integrates well within the factor graph framework and reduces further the overall complexity of the receiver. Additionally, particle swarm optimization (PSO) is investigated for the purpose of initial channel estimation. The bio-inspired algorithm is particularly interesting because of its fast convergence to a reasonable MSE and its versatile adaptation to a variety of optimization problems. It is especially suited for initialization since no a priori information is required. A cooperative approach to PSO is proposed for large-scale antenna implementations as well as a multi-objective PSO for time-varying frequency-selective channels.
The performance of the multi-dimensional graph-based soft iterative receiver is evaluated by means of Monte Carlo simulations. The achieved results are compared to the performance of an iterative state-of-the-art receiver. It is shown that a similar or better performance is achieved at a lower complexity.
An appealing feature of iterative semi-blind channel estimation is that the supported pilot spacings may exceed the limits given the by Nyquist-Shannon sampling theorem. In this thesis, a relation between pilot spacing and channel code is formulated. Depending on the chosen channel code and code rate, the maximum spacing approaches the proposed “coded sampling bound”.Die digitale drahtlose Kommunikation begann in den 1990er Jahren mit der zunehmenden Verbreitung von GSM. Seitdem haben sich Mobilfunksysteme drastisch weiterentwickelt. Aktuelle Mobilfunkstandards nähern sich dem Ziel eines omnipräsenten Kommunikationssystems an und erfüllen damit den Wunsch mit jedem Menschen zu jeder Zeit an jedem Ort kommunizieren zu können. Heutzutage ist die Akzeptanz von Smartphones und Tablets immens und das mobile Internet ist die zentrale Anwendung. Ausgehend von dem momentanen Wachstum wird das Datenaufkommen in Mobilfunk-Netzwerken im Jahr 2020, im Vergleich zum Jahr 2010, um den Faktor 1000 gestiegen sein und 100 Exabyte überschreiten.
Unglücklicherweise ist die verfügbare Bandbreite beschränkt und muss daher effizient genutzt werden. Schlüsseltechnologien, wie z.B. Mehrantennensysteme (multiple-input multiple-output, MIMO), orthogonale Frequenzmultiplexverfahren (orthogonal frequency-division multiplexing, OFDM) sowie weitere MIMO Codierverfahren, vergrößern die theoretisch erreichbare Kanalkapazität und kommen bereits in der Mehrheit der Mobil-funkstandards zum Einsatz. Auf der einen Seite verspricht MIMO-OFDM erhebliche Diversitäts- und/oder Kapazitätsgewinne. Auf der anderen Seite steigt die Komplexität der optimalen Maximum-Likelihood Detektion exponientiell und ist infolgedessen nicht haltbar. Zusätzlich wächst der benötigte Mehraufwand für die Kanalschätzung mit der Anzahl der verwendeten Antennen und reduziert dadurch die Bandbreiteneffizienz. Iterative Empfänger, die Datendetektion und Kanalschätzung im Verbund ausführen, sind potentielle Wegbereiter um den Mehraufwand des Trainings zu reduzieren und sich gleichzeitig der maximalen Kapazität mit geringerem Aufwand anzunähern.
Im Rahmen dieser Arbeit wird ein graphenbasierter Empfänger für iterative Datendetektion und Kanalschätzung entwickelt. Der vorgeschlagene multidimensionale Faktor Graph führt sogenannte Transferknoten ein, die die Korrelation benachbarter Kanalkoeffizienten in beliebigen Dimensionen, z.B. Zeit, Frequenz und Raum, ausnutzen. Hierdurch wird eine einfache und flexible Empfängerstruktur realisiert mit deren Hilfe weiche Kanalschätzung und Datendetektion in mehrdimensionalen, dispersiven Kanälen mit beliebiger Modulation und Codierung durchgeführt werden kann. Allerdings weist der Faktorgraph suboptimale Schleifen auf. Um die maximale Performance zu erreichen, wurde neben dem Ablauf des Nachrichtenaustausches und des Vorgangs zur Kombination von Nachrichten auch die Initialisierung speziell angepasst. Im Gegensatz zu herkömmlichen Methoden, bei denen mehrere Knoten zur Vermeidung von Schleifen zusammengefasst werden, verringern die vorgeschlagenen Methoden die leistungsmindernde Effekte von Schleifen, erhalten aber zugleich die geringe Komplexität des Empfängers. Zusätzlich wird ein neuartiger Detektionsalgorithmus vorgestellt, der baumbasierte Detektionsalgorithmen mit dem sogenannten Gauss-Detektor verknüpft. Der resultierende baumbasierte Gauss-Detektor (Gaussian tree search detector) lässt sich ideal in das graphenbasierte Framework einbinden und verringert weiter die Gesamtkomplexität des Empfängers. Zusätzlich wird Particle Swarm Optimization (PSO) zum Zweck der initialen Kanalschätzung untersucht. Der biologisch inspirierte Algorithmus ist insbesonders wegen seiner schnellen Konvergenz zu einem akzeptablen MSE und seiner vielseitigen Abstimmungsmöglichkeiten auf eine Vielzahl von Optimierungsproblemen interessant. Da PSO keine a priori Informationen benötigt, ist er speziell für die Initialisierung geeignet. Sowohl ein kooperativer Ansatz für PSO für Antennensysteme mit extrem vielen Antennen als auch ein multi-objective PSO für Kanäle, die in Zeit und Frequenz dispersiv sind, werden evaluiert.
Die Leistungsfähigkeit des multidimensionalen graphenbasierten iterativen Empfängers wird mit Hilfe von Monte Carlo Simulationen untersucht. Die Simulationsergebnisse werden mit denen eines dem Stand der Technik entsprechenden Empfängers verglichen. Es wird gezeigt, dass ähnliche oder bessere Ergebnisse mit geringerem Aufwand erreicht werden.
Eine weitere ansprechende Eigenschaft von iterativen semi-blinden Kanalschätzern ist, dass der mögliche Abstand von Trainingssymbolen die Grenzen des Nyquist-Shannon Abtasttheorem überschreiten kann. Im Rahmen dieser Arbeit wird eine Beziehung zwischen dem Trainingsabstand und dem Kanalcode formuliert. In Abhängigkeit des gewählten Kanalcodes und der Coderate folgt der maximale Trainingsabstand der vorgeschlagenen “coded sampling bound”
Advanced CMOS Integrated Circuit Design and Application
The recent development of various application systems and platforms, such as 5G, B5G, 6G, and IoT, is based on the advancement of CMOS integrated circuit (IC) technology that enables them to implement high-performance chipsets. In addition to development in the traditional fields of analog and digital integrated circuits, the development of CMOS IC design and application in high-power and high-frequency operations, which was previously thought to be possible only with compound semiconductor technology, is a core technology that drives rapid industrial development. This book aims to highlight advances in all aspects of CMOS integrated circuit design and applications without discriminating between different operating frequencies, output powers, and the analog/digital domains. Specific topics in the book include: Next-generation CMOS circuit design and application; CMOS RF/microwave/millimeter-wave/terahertz-wave integrated circuits and systems; CMOS integrated circuits specially used for wireless or wired systems and applications such as converters, sensors, interfaces, frequency synthesizers/generators/rectifiers, and so on; Algorithm and signal-processing methods to improve the performance of CMOS circuits and systems
Semiconductor Laser Dynamics
This is a collection of 18 papers, two of which are reviews and seven are invited feature papers, that together form the Photonics Special Issue “Semiconductor Laser Dynamics: Fundamentals and Applications”, published in 2020. This collection is edited by Daan Lenstra, an internationally recognized specialist in the field for 40 years
Enabling technologies and cyber-physical systems for mission-critical scenarios
Programa Oficial de Doutoramento en Tecnoloxías da Información e Comunicacións en Redes Móbiles . 5029P01[Abstract]
Reliable transport systems, defense, public safety and quality assurance in the Industry 4.0 are essential in a modern society. In a mission-critical scenario, a mission failure would jeopardize human lives and put at risk some other assets whose impairment or loss would significantly harm society or business results. Even small degradations of the communications supporting the mission could have large and possibly dire consequences.
On the one hand, mission-critical organizations wish to utilize the most modern, disruptive and innovative communication systems and technologies, and yet, on the other hand, need to comply with strict requirements, which are very different to those of non critical scenarios. The aim of this thesis is to assess the feasibility of applying emerging technologies like Internet of Things (IoT), Cyber-Physical Systems (CPS) and 4G broadband communications in mission-critical scenarios along three key critical infrastructure sectors: transportation, defense and public safety, and shipbuilding.
Regarding the transport sector, this thesis provides an understanding of the progress of communications technologies used for railways since the implantation of Global System for Mobile communications-Railways (GSM-R). The aim of this work is to envision the potential contribution of Long Term Evolution (LTE) to provide additional features that GSM-R would never support. Furthermore, the ability of Industrial IoT for revolutionizing the railway industry and confront today's challenges is presented. Moreover, a detailed review of the most common flaws found in Radio Frequency IDentification (RFID) based IoT systems is presented, including the latest attacks described in the literature. As a result, a novel methodology for auditing security and reverse engineering RFID communications in transport applications is introduced.
The second sector selected is driven by new operational needs and the challenges that arise from modern military deployments. The strategic advantages of 4G broadband technologies massively deployed in civil scenarios are examined. Furthermore, this thesis analyzes the great potential for applying IoT technologies to revolutionize modern warfare and provide benefits similar to those in industry. It identifies scenarios where defense and public safety could leverage better commercial IoT capabilities to deliver greater survivability to the warfighter or first responders, while reducing costs and increasing operation efficiency and effectiveness.
The last part is devoted to the shipbuilding industry. After defining the novel concept of Shipyard 4.0, how a shipyard pipe workshop works and what are the requirements for building a smart pipe system are described in detail. Furthermore, the foundations for enabling an affordable CPS for Shipyards 4.0 are presented. The CPS proposed consists of a network of beacons that continuously collect information about the location of the pipes. Its design allows shipyards to obtain more information on the pipes and to make better use of it. Moreover, it is indicated how to build a positioning system from scratch in an environment as harsh in terms of communications as a shipyard, showing an example of its architecture and implementation.[Resumen]
En la sociedad moderna, los sistemas de transporte fiables, la defensa, la seguridad pública y el control de la calidad en la Industria 4.0 son esenciales. En un escenario de misión crítica, el fracaso de una misión pone en peligro vidas humanas y en riesgo otros activos cuyo deterioro o pérdida perjudicaría significativamente a la sociedad o a los resultados de una empresa. Incluso pequeñas degradaciones en las comunicaciones que apoyan la misión podrían tener importantes y posiblemente terribles consecuencias.
Por un lado, las organizaciones de misión crítica desean utilizar los sistemas y tecnologías de comunicación más modernos, disruptivos e innovadores y, sin embargo, deben cumplir requisitos estrictos que son muy diferentes a los relativos a escenarios no críticos. El objetivo principal de esta tesis es evaluar la viabilidad de aplicar tecnologías emergentes como Internet of Things (IoT), Cyber-Physical Systems (CPS) y comunicaciones de banda ancha 4G en escenarios de misión crítica en tres sectores clave de infraestructura crítica: transporte, defensa y seguridad pública, y construcción naval.
Respecto al sector del transporte, esta tesis permite comprender el progreso de las tecnologías de comunicación en el ámbito ferroviario desde la implantación de Global System for Mobile communications-Railway (GSM-R). El objetivo de este trabajo es analizar la contribución potencial de Long Term Evolution (LTE) para proporcionar características adicionales que GSM-R nunca podría soportar. Además, se presenta la capacidad de la IoT industrial para revolucionar la industria ferroviaria y afrontar los retos actuales. Asimismo, se estudian con detalle las vulnerabilidades más comunes de los sistemas IoT basados en Radio Frequency IDentification (RFID), incluyendo los últimos ataques descritos en la literatura. Como resultado, se presenta una metodología innovadora para realizar auditorías de seguridad e ingeniería inversa de las comunicaciones RFID en aplicaciones de transporte.
El segundo sector elegido viene impulsado por las nuevas necesidades operacionales y los desafíos que surgen de los despliegues militares modernos. Para afrontarlos, se analizan las ventajas estratégicas de las tecnologías de banda ancha 4G masivamente desplegadas en escenarios civiles. Asimismo, esta tesis analiza el gran potencial de aplicación de las tecnologías IoT para revolucionar la guerra moderna y proporcionar beneficios similares a los alcanzados por la industria. Se identifican escenarios en los que la defensa y la seguridad pública podrían aprovechar mejor las capacidades comerciales de IoT para ofrecer una mayor capacidad de supervivencia al combatiente o a los servicios de emergencias, a la vez que reduce los costes y aumenta la eficiencia y efectividad de las operaciones.
La última parte se dedica a la industria de construcción naval. Después de definir el novedoso concepto de Astillero 4.0, se describe en detalle cómo funciona el taller de tubería de astillero y cuáles son los requisitos para construir un sistema de tuberías inteligentes. Además, se presentan los fundamentos para posibilitar un CPS asequible para Astilleros 4.0. El CPS propuesto consiste en una red de balizas que continuamente recogen información sobre la ubicación de las tuberías. Su diseño permite a los astilleros obtener más información sobre las tuberías y hacer un mejor uso de las mismas. Asimismo, se indica cómo construir un sistema de posicionamiento desde cero en un entorno tan hostil en términos de comunicaciones, mostrando un ejemplo de su arquitectura e implementación
Quality of Service in Vehicular Ad Hoc Networks: Methodical Evaluation and Enhancements for ITS-G5
After many formative years, the ad hoc wireless communication between vehicles has become a vehicular technology available in mass production cars in 2020. Vehicles form spontaneous Vehicular Ad Hoc Networks (VANETs), which enable communication whenever vehicles are nearby without need for supportive infrastructure. In Europe, this communication is standardised comprehensively as Intelligent Transport Systems in the 5.9 GHz band (ITS-G5).
This thesis centres around Quality of Service (QoS) in these VANETs based on ITS-G5 technology. Whilst only a few vehicles communicate, radio resources are plenty, and channel congestion is a minor issue. With progressing deployment, congestion control becomes crucial to preserve QoS by preventing high latencies or foiled information dissemination. The developed VANET simulation model, featuring an elaborated ITS-G5 protocol stack, allows investigation of QoS methodically. It also considers the characteristics of ITS-G5 radios such as the signal attenuation in vehicular environments and the capture effect by receivers.
Backed by this simulation model, several enhancements for ITS-G5 are
proposed to control congestion reliably and thus ensure QoS for its applications. Modifications at the GeoNetworking (GN) protocol prevent massive packet occurrences in a short time and hence congestion. Glow Forwarding is introduced as GN extension to distribute delay-tolerant information. The revised Decentralized Congestion Control (DCC) cross-layer supports low-latency transmission of event-triggered, periodic and relayed packets. DCC triggers periodic services and manages a shared duty cycle budget dedicated to packet forwarding for this purpose.
Evaluation in large-scale networks reveals that this enhanced ITS-G5 system can reliably reduce the information age of periodically sent messages. The forwarding budget virtually eliminates the starvation of multi-hop packets and still avoids congestion caused by excessive forwarding. The presented enhancements thus pave the way to scale up VANETs for wide-spread deployment and future applications