5,660 research outputs found
Beam scanning by liquid-crystal biasing in a modified SIW structure
A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium
Intelligent computing : the latest advances, challenges and future
Computing is a critical driving force in the development of human civilization. In recent years, we have witnessed the emergence of intelligent computing, a new computing paradigm that is reshaping traditional computing and promoting digital revolution in the era of big data, artificial intelligence and internet-of-things with new computing theories, architectures, methods, systems, and applications. Intelligent computing has greatly broadened the scope of computing, extending it from traditional computing on data to increasingly diverse computing paradigms such as perceptual intelligence, cognitive intelligence, autonomous intelligence, and human computer fusion intelligence. Intelligence and computing have undergone paths of different evolution and development for a long time but have become increasingly intertwined in recent years: intelligent computing is not only intelligence-oriented but also intelligence-driven. Such cross-fertilization has prompted the emergence and rapid advancement of intelligent computing
Diseño y aplicaciones de sistemas de antenas inteligentes para redes inalámbricas en el contexto de la internet de las cosas
[SPA] Esta tesis doctoral se presenta bajo la modalidad de compendio de publicaciones. Las antenas de onda de fuga (LWA) consisten en una estructura de guía de onda que permite la fuga de parte de la potencia a lo largo de la estructura. Por esta razón, la radiación de la antena se produce por la fuga de energía. Para producir una radiación coherente, es necesario controlar esta tasa de radiación a lo largo de la estructura radiante. Así, ajustando con precisión la tasa de radiación, se controla la forma del diagrama de radiación. Las LWAs han sido ampliamente estudiadas por la comunidad científica debido a sus ventajas, tales como, red de alimentación simple, alta directividad y escaneo en frecuencia pasivo. Sin embargo, presentan ciertas desventajas entre las cuales, la más importante a destacar es el efecto de beam-squinting. Éste se produce por la propiedad dispersiva inherente a este tipo de antenas. Además, presentan dificultades a la hora de generar radiación coherente en las direcciones broadside y endfire, aumentando la complejidad del diseńo para la radiación en dichas direcciones. Las LWA han sido relativamente poco utilizadas en aplicaciones prácticas hasta la fecha, a pesar de sus ventajas. Las pocas aplicaciones en las que se han utilizado son los radares de onda continua modulada en frecuencia y los sistemas de enfoque controlado en frecuencia de campo cercano. Esta tesis propone el uso de las LWAs en aplicaciones prácticas aprovechando las ventajas mencionadas anteriormente y teniendo en cuenta los inconvenientes de este tipo de antenas para que su uso no sea limitado. Recientemente, las LWAs han sido propuestas para aplicaciones de localización de bajo coste, ya que permiten el diseńo de estructuras planas con haces directivos. Además, debido al aumento exponencial del uso de la tecnología, es necesario encontrar nuevas tecnologías para una transmisión de datos mayor, más rápida y más eficiente, manteniendo bajos costes de fabricación. Por lo tanto las LWAs pueden ser una solución crucial al mezclar bajos costes de fabricación, alta integrabilidad en diferentes sistemas debido a su tecnología impresa planar y alta directividad al mismo tiempo que se aprovecha su característica dispersiva que proporciona un escaneo pasivo en frecuencia. En este contexto, la principal aportación de esta Tesis consiste en el estudio, análisis, diseńo e integración de LWAs en aplicaciones reales y prácticas. Esta Tesis presenta las siguientes tres contribuciones principales, definidas en los tres bloques principales de este documento: • Estudio y análisis de LWAs para su uso en sistemas de estimación de dirección de llegada basados en técnicas de amplitud de monopulso. Comparar las características y prestaciones de las LWAs junto con las antenas comerciales más utilizadas. Para ello, diseńar y fabricar las HWM-LWAs con el fin de comparar sus prestaciones con las antenas de panel adquiridas comercialmente. Dado que cada aplicación requiere el diseńo de una HWM-LWA nueva y diferente, estudiar y proponer una técnica eficiente de análisis y diseńo de antenas para obtener fácilmente diagramas de radiación monopulso escaneados en frecuencia. • Una vez analizado que las HWM-LWA son una solución factible para su uso en aplicaciones reales de localización debido a sus diversas ventajas. Integrar las HWM-LWAs diseńadas en sistemas digitales para estimación del ángulo de llegada en interiores. Por lo tanto, diseńar, desarrollar, configurar e integrar las LWAs en diferentes sistemas basados en las bandas de frecuencia Wi-Fi ISM de 2,4 GHz y 5 GHz. Finalmente, comparar los resultados de estimación obtenidos con otras soluciones propuestas para corroborar que los LWAs pueden ser utilizados en aplicaciones reales. • Asimismo, debido a su bajo coste de fabricación y a su principal propiedad de escaneo en frecuencia. Ampliar el uso de las LWAs para la localización angular en redes de sensores inalámbricas (WSN) utilizando la banda de frecuencias UHF de 900 MHz. Utilizando así etiquetas RFID pasivas. También estudiar su aplicabilidad en WSNs utilizando etiquetas LoRa activas. Este documento se presenta como una Tesis por compendio, por lo que se presentarán y explicarán brevemente los 4 artículos de revistas que se han publicado durante el programa de doctorado. Además, también se presentarán algunos artículos de conferencias y otros trabajos en revisión para exponer algunas de las investigaciones que no han sido publicadas en revistas hasta la fecha de depósito de tesis. El documento está organizado como se indica a continuación: En la Introducción, se presenta una contextualización del estado del arte y una explicación rigurosa sobre las LWAs y las aplicaciones anteriormente mencionadas. Las dos partes siguientes se vi dedican a presentar y explicar brevemente los trabajos publicados que contribuyen a esta Tesis. En la parte II, se presentan los cuatro artículos que conforman el compendio. Esto es, el análisis de las LWAs para la estimación de la dirección del ángulo de llegada y la integración de las LWAs en sistemas de localización digital usando el protocolo Wi-Fi en el Capítulo 1, la banda de frecuencias ISM UHF 900 MHz se utiliza junto con los HWM-LWAs en el Capítulo 2, luego se implementa en un sistema en tiempo real para la estimación de la dirección de llegada de múltiples tags pasivos en el Capítulo 3 y la integración de LoRa en el Capítulo 4. Finalmente, en la Parte III, se discuten las conclusiones generales y las futuras líneas de investigación. [ENG] This doctoral dissertation has been presented in the form of thesis by publication. Leaky-Wave Antennas (LWA) consist on a waveguide structure which allows the leakage of part of the power along the structure. For this reason, the radiation of the antenna is produced by the leakage of power. In order to produce coherent radiation, it is necessary to control this leakage rate along the radiating structure. Thus, precisely adjusting the leakage rate, the shape of the radiation pattern is controlled. LWAs have been widely studied by the scientific community due to their advantages, such as, simple feeding network, high directivity and passive frequency-scanning performance. However, they present certain disadvantages among which, the most important to highlight is the beam-squinting effect. TThis is due to the inherent dispersion property of this type of antenna. In addition, LWAs present difficulties when generating coherent radiation in broadside and endfire directions, increasing the complexity of the design for radiation in these directions. LWAs have been relatively unused in practical applications to date, despite of their benefits. The few applications in which they have been used are frequency modulated continuous wave radars and near-field frequency controlled focusing systems.This thesis proposes the use of LWAs in practical applications by exploiting the advantages mentioned above while taking into account the drawbacks of this type of antennas so that their use is not limited. Recently, LWAs have been proposed for low-cost localization applications, as they allow the design of planar structures with directive beams. In addition, due to the exponential increase in the use of technology, it is necessary to find new technologies for higher, faster and more efficient data transmission while maintaining low manufacturing costs. Therefore, LWAs can be a crucial solution mixing low manufacturing costs, high integrability in different systems due to their planar printed technology and high directivity while taking advantage of their dispersive characteristic that provides passive frequency scanning. In this context, the main contribution of this Thesis consist of the study, analysis, design and integration of LWAs in real and practical applications. This Thesis presents the following three main contributions, defined in the three main blocks of this document: • Study and analysis of LWAs for its use in direction of arrival estimation systems based on monopulse amplitude techniques. Compare the characteristics and performance of LWAs along with widely used commercial antennas. For this purpose, design and manufacture the HWM-LWAs in order to compare their performance with commercially acquired panel antennas. Since each application requires the design of a new and different HWM-LWA, a main objective of this block is to study and propose an efficient antenna analysis and design technique to facilitate obtaining frequency-scanned monopulse patterns. • Once analyzed that LWAs are a feasible solution for its use in real localization applications due to their several advantages, integrate the designed half-width microstrip (HWM-LWAs) in digital indoor angle-of-arrival estimation systems. Therefore, design, develop, configure and integrate LWAs in different systems based on the Wi-Fi ISM 2.4 GHz and 5 GHz frequency bands. Finally, compare the obtained estimation results with other proposed solutions to corroborate that LWAs can be used in real applications. • Extending the use of antennas for angular localization in sensor networks using the 900 MHz UHF frequency band: the main properties of low manufacturing cost and passive frequency beam scanning can be used in other applications. Thus, the localization estimation of passive RFID tags is studied, as well as their application in Wireless Sensor Networks (WSNs) using active tags with LORA technology. This document is presented as a Thesis by compilation, so the 4 journal articles that have been published during the Ph.D program will be presented and briefly explained. Besides, some conference articles and other work under review will be also presented to expose some of the research that has not been published in journals. The document is organized as outlined hereafter: In Part I, a state-of-the-art contextualization, a rigorous explanation about LWAs and the previous applications mentioned above is presented. The next two parts are dedicated to present and briefly explain the published works included in this Thesis and their main contributions. In Part II the explanation of the four papers which compose the compendium are presented. This is, LWAs analysis for direction of arrival estimation and the integration of LWAs in digital Wi-Fi localization systems in chapter 1, the UHF 900 MHz ISM frequency band is used in conjunction with HWM-LWAs in chapter 2, then, it is implemented in a real time system for direction of arrival estimation of multi RFID tags in chapter 3 and LoRa integration in chapter 4. Finally, in Part III, the overall conclusions and the future research lines are discussed.Esta tesis doctoral se presenta bajo la modalidad de compendio de publicaciones. Está formada por un total de cuatro artículos. Article 1.-: A. Gil-Martinez, M. Poveda-Garcia, J. A. Lopez-Pastor, J. C. Sanchez-Aarnoutse and J. L. Gomez-Tornero, Wi-Fi Direction Finding with Frequency-Scanned Antenna and Channel Hopping Scheme IEEE sensors Journal, , vol. 22, no. 6, pp. 5210-5222, 2022. DOI: 10.1109/JSEN.2021.3122232. Article 2.-: A. Gil-Martinez, M. Poveda-Garcia, D. Cañete-Rebenaque, and J. L. Gomez-Tornero, Frequency-Scanned Monopulse Antenna for RSSI-based Direction Finding of UHF RFID tags IEEE Antennas and Wireless Propagation Letters,, vol. 21, no. 1, pp. 158-162, 2022. DOI: 10.1109/LAWP.2021.3122232. Article 3.-: A. Gil-Martinez, M. Poveda-Garcia, J. Garcia-Fernandez, M. Campo-Valera, D. Cañete-Rebenaque, and J. L. Gomez-Tornero, Direction Finding of RFID tags in UHF Band Using a Passive Beam-Scanning Leaky-Wave Antenna IEEE Journal of Radio Frequency Identi cation, doi: 10.1109/JRFID.2021.3122233. Article 4.-: J. L. Gomez-Tornero, A. Gil-Martinez, M. Poveda-Garcia and D. Cañete-Rebenaque, ARIEL: Passive Beam-Scanning Antenna TeRminal for Iridiscent and E cient LEO Satellite Connectivity in IEEE Antennas and Wireless Propagation Letters, doi: 10.1109/LAWP.2022.3193040.Escuela Internacional de Doctorado de la Universidad Politécnica de CartagenaUniversidad Politécnica de CartagenaPrograma Doctorado en Tecnologías de la Información y las Comunicacione
The Metaverse: Survey, Trends, Novel Pipeline Ecosystem & Future Directions
The Metaverse offers a second world beyond reality, where boundaries are
non-existent, and possibilities are endless through engagement and immersive
experiences using the virtual reality (VR) technology. Many disciplines can
benefit from the advancement of the Metaverse when accurately developed,
including the fields of technology, gaming, education, art, and culture.
Nevertheless, developing the Metaverse environment to its full potential is an
ambiguous task that needs proper guidance and directions. Existing surveys on
the Metaverse focus only on a specific aspect and discipline of the Metaverse
and lack a holistic view of the entire process. To this end, a more holistic,
multi-disciplinary, in-depth, and academic and industry-oriented review is
required to provide a thorough study of the Metaverse development pipeline. To
address these issues, we present in this survey a novel multi-layered pipeline
ecosystem composed of (1) the Metaverse computing, networking, communications
and hardware infrastructure, (2) environment digitization, and (3) user
interactions. For every layer, we discuss the components that detail the steps
of its development. Also, for each of these components, we examine the impact
of a set of enabling technologies and empowering domains (e.g., Artificial
Intelligence, Security & Privacy, Blockchain, Business, Ethics, and Social) on
its advancement. In addition, we explain the importance of these technologies
to support decentralization, interoperability, user experiences, interactions,
and monetization. Our presented study highlights the existing challenges for
each component, followed by research directions and potential solutions. To the
best of our knowledge, this survey is the most comprehensive and allows users,
scholars, and entrepreneurs to get an in-depth understanding of the Metaverse
ecosystem to find their opportunities and potentials for contribution
Recommended from our members
Ensuring Access to Safe and Nutritious Food for All Through the Transformation of Food Systems
Aerial Network Assistance Systems for Post-Disaster Scenarios : Topology Monitoring and Communication Support in Infrastructure-Independent Networks
Communication anytime and anywhere is necessary for our modern society to function. However, the critical network infrastructure quickly fails in the face of a disaster and leaves the affected population without means of communication. This lack can be overcome by smartphone-based emergency communication systems, based on infrastructure-independent networks like Delay-Tolerant Networks (DTNs). DTNs, however, suffer from short device-to-device link distances and, thus, require multi-hop routing or data ferries between disjunct parts of the network. In disaster scenarios, this fragmentation is particularly severe because of the highly clustered human mobility behavior. Nevertheless, aerial communication support systems can connect local network clusters by utilizing Unmanned Aerial Vehicles (UAVs) as data ferries. To facilitate situation-aware and adaptive communication support, knowledge of the network topology, the identification of missing communication links, and the constant reassessment of dynamic disasters are required. These requirements are usually neglected, despite existing approaches to aerial monitoring systems capable of detecting devices and networks.
In this dissertation, we, therefore, facilitate the coexistence of aerial topology monitoring and communications support mechanisms in an autonomous Aerial Network Assistance System for infrastructure-independent networks as our first contribution. To enable system adaptations to unknown and dynamic disaster situations, our second contribution addresses the collection, processing, and utilization of topology information. For one thing, we introduce cooperative monitoring approaches to include the DTN in the monitoring process. Furthermore, we apply novel approaches for data aggregation and network cluster estimation to facilitate the continuous assessment of topology information and an appropriate system adaptation. Based on this, we introduce an adaptive topology-aware routing approach to reroute UAVs and increase the coverage of disconnected nodes outside clusters.
We generalize our contributions by integrating them into a simulation framework, creating an evaluation platform for autonomous aerial systems as our third contribution. We further increase the expressiveness of our aerial system evaluation, by adding movement models for multicopter aircraft combined with power consumption models based on real-world measurements. Additionally, we improve the disaster simulation by generalizing civilian disaster mobility based on a real-world field test. With a prototypical system implementation, we extensively evaluate our contributions and show the significant benefits of cooperative monitoring and topology-aware routing, respectively. We highlight the importance of continuous and integrated topology monitoring for aerial communications support and demonstrate its necessity for an adaptive and long-term disaster deployment. In conclusion, the contributions of this dissertation enable the usage of autonomous Aerial Network Assistance Systems and their adaptability in dynamic disaster scenarios
Analyzing Usage Conflict Situations in Localized Spectrum Sharing Scenarios: An Agent-Based Modeling and Machine Learning Approach
As spectrum sharing matures, different approaches have been proposed for a more efficient allocation, assignment, and usage of spectrum resources. These approaches include cognitive radios, multi-level user definitions, radio environment maps, among others. However, spectrum usage conflicts (e.g., "harmful" interference) remain a common challenge in spectrum sharing schemes. In particular, in conflict situations where it is necessary to take actions to ensure the sound operations of sharing agreements. A typical example of a usage conflict is where incumbents' tolerable levels of interference (i.e., interference thresholds) are surpassed. In this work, we present a new method to examine and study spectrum usage conflicts. A fundamental goal of this project is to capture local resource usage patterns to provide more realistic estimates of interference. For this purpose, we have defined two spectrum and network-specific characteristics that directly impact the local interference assessment: resource access strategy and governance framework. Thus, we are able to test the viability in spectrum sharing situations of distributed or decentralized governance systems, including polycentric and self-governance. In addition, we are able to design, model, and test a multi-tier spectrum sharing scheme that provides stakeholders with more flexible resource access opportunities.
To perform this dynamic and localized study of spectrum usage and conflicts, we rely on Agent-Based Modeling (ABM) as our main analysis instrument. A crucial component for capturing local resource usage patterns is to provide agents with local information about their spectrum situation. Thus, the environment of the models presented in this dissertation are given by the REM's Interference Cartography (IC) map. Additionally, the agents' definitions and actions are the results of the interaction of the technical aspects of resource access and management, stakeholder interactions, and the underlying usage patterns as defined in the Common Pool Resource (CPR) literature. Finally, to capture local resource usage patterns and, consequently, provide more realistic estimates of conflict situations, we enhance the classical rule-based ABM approach by using Machine Learning (ML) techniques. Via ML algorithms, we refine the internal models of agents in an ABM. Thus, the agents' internal models allow them to choose more suitable responses to changes in the environment
Fast fluorescence lifetime imaging and sensing via deep learning
Error on title page – year of award is 2023.Fluorescence lifetime imaging microscopy (FLIM) has become a valuable tool in diverse disciplines. This thesis presents deep learning (DL) approaches to addressing two major challenges in FLIM: slow and complex data analysis and the high photon budget for precisely quantifying the fluorescence lifetimes. DL's ability to extract high-dimensional features from data has revolutionized optical and biomedical imaging analysis. This thesis contributes several novel DL FLIM algorithms that significantly expand FLIM's scope.
Firstly, a hardware-friendly pixel-wise DL algorithm is proposed for fast FLIM data analysis. The algorithm has a simple architecture yet can effectively resolve multi-exponential decay models. The calculation speed and accuracy outperform conventional methods significantly.
Secondly, a DL algorithm is proposed to improve FLIM image spatial resolution, obtaining high-resolution (HR) fluorescence lifetime images from low-resolution (LR) images. A computational framework is developed to generate large-scale semi-synthetic FLIM datasets to address the challenge of the lack of sufficient high-quality FLIM datasets. This algorithm offers a practical approach to obtaining HR FLIM images quickly for FLIM systems.
Thirdly, a DL algorithm is developed to analyze FLIM images with only a few photons per pixel, named Few-Photon Fluorescence Lifetime Imaging (FPFLI) algorithm. FPFLI uses spatial correlation and intensity information to robustly estimate the fluorescence lifetime images, pushing this photon budget to a record-low level of only a few photons per pixel.
Finally, a time-resolved flow cytometry (TRFC) system is developed by integrating an advanced CMOS single-photon avalanche diode (SPAD) array and a DL processor. The SPAD array, using a parallel light detection scheme, shows an excellent photon-counting throughput. A quantized convolutional neural network (QCNN) algorithm is designed and implemented on a field-programmable gate array as an embedded processor. The processor resolves fluorescence lifetimes against disturbing noise, showing unparalleled high accuracy, fast analysis speed, and low power consumption.Fluorescence lifetime imaging microscopy (FLIM) has become a valuable tool in diverse disciplines. This thesis presents deep learning (DL) approaches to addressing two major challenges in FLIM: slow and complex data analysis and the high photon budget for precisely quantifying the fluorescence lifetimes. DL's ability to extract high-dimensional features from data has revolutionized optical and biomedical imaging analysis. This thesis contributes several novel DL FLIM algorithms that significantly expand FLIM's scope.
Firstly, a hardware-friendly pixel-wise DL algorithm is proposed for fast FLIM data analysis. The algorithm has a simple architecture yet can effectively resolve multi-exponential decay models. The calculation speed and accuracy outperform conventional methods significantly.
Secondly, a DL algorithm is proposed to improve FLIM image spatial resolution, obtaining high-resolution (HR) fluorescence lifetime images from low-resolution (LR) images. A computational framework is developed to generate large-scale semi-synthetic FLIM datasets to address the challenge of the lack of sufficient high-quality FLIM datasets. This algorithm offers a practical approach to obtaining HR FLIM images quickly for FLIM systems.
Thirdly, a DL algorithm is developed to analyze FLIM images with only a few photons per pixel, named Few-Photon Fluorescence Lifetime Imaging (FPFLI) algorithm. FPFLI uses spatial correlation and intensity information to robustly estimate the fluorescence lifetime images, pushing this photon budget to a record-low level of only a few photons per pixel.
Finally, a time-resolved flow cytometry (TRFC) system is developed by integrating an advanced CMOS single-photon avalanche diode (SPAD) array and a DL processor. The SPAD array, using a parallel light detection scheme, shows an excellent photon-counting throughput. A quantized convolutional neural network (QCNN) algorithm is designed and implemented on a field-programmable gate array as an embedded processor. The processor resolves fluorescence lifetimes against disturbing noise, showing unparalleled high accuracy, fast analysis speed, and low power consumption
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