Programa del congreso

En este artículo se resumen las especificaciones técnicas de radio distribuida que se implementan en el proyecto europeo 6G-REFERENCE (6G - Hardware Enablers for Cell Free Coherent Communications and Sensing).

Este artículo describe el análisis, diseño y construcción de un dispositivo de microcinta capaz de detectar hidrógeno a frecuencias de microondas. La estructura propuesta consiste en una línea de transmisión tipo microstrip híbrida de 10 cm de longitud, en la que parte de la línea de cobre (Cu) se sustituye por una lámina de paladio (Pd) de 10 nm de espesor. Para un dispositivo con una sección de Pd de 2 cm de longitud, expuesto a un 1,6 % de hidrógeno a una presión de 0,4 bar en nitrógeno gaseoso, la detección se realizó midiendo los cambios producidos en una de las resonancias del parámetro de dispersión S21 en la región de frecuencias de alrededor de 3,2 GHz. Los resultados obtenidos demuestran que la detección de hidrógeno es posible mediante la implementación de bajo costo propuesta. Este hallazgo abre la posibilidad de construir sensores de hidrógeno simples mediante la incorporación de películas ultrafinas de Pd en circuitos de microondas planares.

Este trabajo describe brevemente la concepción y el desarrollo del hardware y el software integrado en el nodo sensor inalámbrico de dimensiones compactas e independiente, llamado SensorQ, sus dimensiones y peso finales son 200 × 80 × 60 mm y 0,422 kg, respectivamente. El nodo SensorQ propuesto se desarrolló específicamente para detectar agentes de guerra química (CWA), con especial el sustituto del gas Sarín, conocido como dimetilmetilfosfonato (DMMP). Además, se describen la arquitectura del sistema, los protocolos de comunicación empleados, el diseño del cabezal sensor óptico y los resultados de la validación experimental realizada en un entorno de laboratorio. Los hallazgos experimentales demuestran el potencial para detectar vapor de DMMP (en concentraciones de 10, 150 y 400 ppm) en el aire utilizando el cabezal sensor óptico propuesto. Esperamos que el nodo de sensor inalámbrico SensorQ sea un candidato prometedor para integrarse en redes de sensores inalámbricos (WSN) en aplicaciones de defensa, ya que está diseñado para detectar CWA en escenarios complejos.

The development of devices that integrate sensing and communication is an area of increasing interest in research on connectivity systems for autonomous vehicles. This paper experimentally implements this concept using commercial radars. By utilizing the capabilities of two radars designed exclusively for sensing, the radar signals are modulated in such a way that one radar can transmit encoded information about its own sensing data, while the other radar receives, decodes, and analyses the information. The communication showed error free ranging from 0 to 45 m, in an outdoor environment with realistic conditions.

Many cryogenic missions for space observation have been launched in the past. In all of them, it was key to insulate the observation devices from thermal and electromagnetic perturbations. A solid understanding of materials and signal propagation is therefore essential to achieve full spectral isolation for cryogenic systems. This work introduces a non-resonant electromagnetic characterization method to extract permittivity and loss in dielectric materials at extreme temperatures. The authors design, simulate and validate a double microstrip transmission line and implement a flexible extraction method to measure permittivity over a wide frequency range, using materials such as CuClad 250, ROGERS 4350B and FR-4. Albeit refinements to the extraction process and comparison with real measurements in a cryogenic setting are possible, the resulting system is shown to be consistent and reliable across all simulations.

This study analyzed how 2.45 GHz radiofrequency (RF) radiation affects the immediate immune response in the RAW-264.7 macrophage cell line previously stimulated with the SARS-CoV-2 spike protein (CSP), bacterial LPS endotoxin or with both LPS and CSP. The RAW 264.7 cell line was continuously exposed for 24 hours in a GTEM chamber to a 2.45 GHz RF field at non-thermal SAR levels. Biological parameters of cellular metabolism such as cell viability and oxidative stress were studied by measuring nitrite levels, and progression of cell death was examined by measuring apoptosis and necrosis levels. The sustained effect of exposure to 2.45 GHz RF for 24 hours enhanced nitric oxide production and reduced cell death in macrophages stimulated with bacterial LPS. However, in the macrophages stimulated with LPS and CSP, exposure to RF did not modulate nitric oxide production or modify the progression of cell death.

Se presenta el diseño de un prototipo de sistema de exposición a radiofrecuencias de un modelo de laboratorio con gran potencial en el ámbito de la toxicología, poco a poco introducido para el estudio de los bioefectos de los campos electromagnéticos: el embrión del pez cebra. A pesar de que son varios los trabajos publicados con este modelo, la diversidad de configuraciones experimentales y de protocolos para la exposición RF del embrión en desarrollo dificulta la extracción de conclusiones fiables. Además, son escasos los estudios que evalúan la exposición mediante un análisis computacional y, en ningún caso, disponen de parámetros eléctricos específicos del embrión en desarrollo. Este trabajo presenta una propuesta integral, analizando el comportamiento de un sistema de exposición basado en una cámara reverberante y abordando, por primera vez, la evaluación dosimétrica del embrión del pez caracterizado eléctricamente. Se empleará para ello diversas técnicas y programas computacionales que permitirán comparar y validar los resultados, orientando la implementación futura del sistema de exposición a RF.

Hepatocellular carcinoma (HCC) accounts for 75% of primary liver tumors. Controlling risk factors and implementing screenings in risk populations does not seem sufficient to improve the prognosis at diagnosis. The development of a predictive prognostic model for mortality at the diagnosis of HCC is proposed. In this retrospective multicenter study, the analysis of data from 191 HCC patients was conducted using machine learning (ML) techniques to analyze the prognostic factors of mortality that are significant at diagnosis. Clinical and analytical data were gathered. Meeting Milan criteria, Barcelona Clinic Liver Cancer (BCLC) classification and albumin levels were the variables with the greatest impact on the prognosis of HCC patients. The ML algorithm that achieved the best results was random forest (RF). RF is useful and reliable in the analysis of prognostic factors in the diagnosis of HCC. The search for new prognostic factors is still necessary in patients with HCC

La pandemia de COVID-19 aceleró los avances en biología molecular y virología, facilitando la identificación de biomarcadores que diferencian los casos graves de los leves. Este estudio empleó inteligencia artificial y aprendizaje automático para analizar datos clínicos, epidemiológicos, analíticos y radiológicos de pacientes admitidos de manera consecutiva. Utilizando el algoritmo Random Forest, se procesaron más de 89 variables, logrando una precisión equilibrada del 92,61%. Los biomarcadores más predictivos de mortalidad fueron la procalcitonina, la lactato deshidrogenasa y la proteína C-reactiva, con especial énfasis en los infiltrados intersticiales observados en las radiografías de tórax y niveles elevados de dímero D. Estos hallazgos subrayan la eficacia del aprendizaje automático en entornos de emergencia para la identificación rápida de biomarcadores, mejorando en última instancia la precisión del pronóstico e informando estrategias de tratamiento personalizadas en pandemias emergentes.

Breast cancer is one of the most common types worldwide, and in many cases, it is treated with chemotherapy. To improve treatment follow-up, electromagnetic field-based technologies offer a non-invasive alternative for real-time monitoring. This study focuses on in vivo measurements of the dielectric permittivity of healthy, chemotherapy-treated, and tumor-affected breast tissues, aiming to assess their usefulness in monitoring treatment progress.

A coaxial probe (DAK 3.5) operating in the 1–8 GHz frequency range was used, following a standardized experimental protocol. Measurements were taken from 30 female volunteers. Results indicate an approximate 30% decrease in real and imaginary permittivity in breast tissue treated with chemotherapy compared to healthy tissue. Additionally, clear differences were observed between tumor and non-tumor tissues, suggesting the potential of this technique for therapeutic monitoring.

Computational electromagnetics (CEM) has become essential in aerospace and naval engineering, particularly for analyzing electromagnetic interference (EMI) and compatibility (EMC) in defense applications involving complex platforms. As hyper-sensorization trends emerge, the need for enhanced CEM methods becomes evident to manage electromagnetically dense environments while meeting strict EMC/EMI and radiation hazard (RADHAZ) requirements. Confidentiality concerns pose challenges in information sharing among international partners, complicating the design of subsystems. This work proposes an EPA-based domain decomposition scheme that encapsulates electromagnetic interactions of large-scale platforms using small-scale Huygens’ surfaces. The method significantly improves efficiency and accuracy in the design of antennas and sensors onboard platforms without requiring detailed geometric knowledge. Additionally, it allows assessment of antennas’ contributions to radar cross-section (RCS) while maintaining safety and confidentiality standards. Integrated with advanced techniques based on the domain decomposition method and multitrace (MT) formulations, this approach also ensures robust modeling of near-field interactions among encapsulated objects.

In this work we use the Reduced Basis Method (RBM) as a parametric reduced order model for electromagnetic problems depending on multiple variables. The RBM approach carries out a simultaneous fast sweep in two variables, namely, the frequency and the dielectric permittivity in a dual cavity sensor. This device is aimed to detect dielectric permittivities in the X-band and accurate fast electromagnetic simulations are critical to enhance the sensor performance. This method enables fast EM simulations while maintains the same accuracy as other high-fidelity full-wave methods such as the Finite Element Method.

This work introduces a preliminary exploration of the Finite Element-Boundary Integral (FEBI) method for addressing the scattering problem in open regions. The FEBI method discretizes the wave equation in a region surrounding the scattering object and sets a truncation boundary by imposing that the fields radiated by the currents on the object surface fulfill a Robin-type boundary condition. This, unlike more common approaches such as Absorbing Boundary Conditions (ABCs) or Perfectly Matched Layers (PMLs), allows an asymptotically exact truncation condition with no spurious effects such as internal reflections. Also, it allows placing the truncation boundary very close to the object surface—thus reducing the computational domain—while supporting concave or disjoint boundaries. The formulation presented here is quite general and aims to offer insight into the formal aspects of the method. We also present proof-of-concept examples to illustrate some features of the method, such as the preconditioning.

Efficient and accurate electromagnetic simulations are crucial for the design and optimization of modern microwave devices. However, as the complexity of these models increases, traditional finite element method simulations become computationally expensive, particularly for parametric analyses involving multiple frequency sweeps and material variations. To address this challenge, this work proposes a parametric reduced basis method (pRBM) to accelerate frequency-domain simulations while maintaining the accuracy of the solution. The proposed approach reduces the computational cost by constructing a reduced order model that captures the electromagnetic dynamics of the high-dimensional system.

The effectiveness of the pRBM is demonstrated through the parametric analysis of an inline dielectric resonator microwave filter. Considering angular frequency and dielectric permittivity as parameters, the method efficiently computes frequency responses with a significant reduction in computational effort. These results highlight the potential of model order reduction techniques for accelerating parametric electromagnetic simulations, making them valuable for iterative design processes and large-scale engineering applications.

Time domain electromagnetic (EM) simulations play a crucial role in understanding electromagnetic field behavior across various engineering and scientific applications. However, traditional numerical techniques, including the finite element method in the time domain (FEMTD), require the solution of large systems of equations at each time step, leading to high computational costs. To address this challenge, a reduced order modeling approach based on dynamic mode decomposition (DMD) is proposed. Dominant spatiotemporal patterns are efficiently extracted from FEMTD solutions using DMD, allowing for the construction of a reduced order model (ROM) that significantly accelerates simulations while preserving accuracy. Using an initial set of FEMTD solutions, the DMD-based ROM enables the reconstruction of the EM response at arbitrary time instances with reduced computational effort. This approach also provides valuable information on the dominant structures that govern the evolution of the EM field. The numerical results demonstrate the effectiveness of DMD in reducing computational complexity while maintaining high-fidelity solutions.

This work explores the integration of Artificial Intelligence (AI) models to predict key components of the simulation pipeline of the Fast Multipole Method (FMM).

This contribution presents a practical proposal for the analysis and visualization of satellite signal coverage using the Iridium constellation as a reference scenario. By modeling the orbital geometry of the satellites and the radiation pattern of their antennas, students can compute the received power on the ground and represent it over a geographic map. The activity is implemented in MATLAB using the Satellite Communications Toolbox and allows students to reinforce key concepts related to radio link modeling, such as antenna gain, propagation losses, and free-space transmission equation, within the context of a real low Earth orbit (LEO) system.

En este trabajo, se propone una metodología que combina el aprendizaje cooperativo y el aprendizaje basado en juegos como alternativa a la docencia expositiva en clases teóricas. Para sistematizar la aplicación de esta innovación y evaluar su impacto real sin sesgos, se ha decido utilizar una aproximación basada en el proceso de investigación-acción. Los resultados obtenidos son prometedores y muestran la capacidad de la metodología propuesta para mejorar diferentes aspectos del proceso de aprendizaje.

This communication describes the study and evaluation of low-cost RF measurement instruments intended for educational use. To this end, a separate analysis of the principles of operation is included for each type of typical RF test-equipment (i.e., a function generator, a spectrum analyzer, and a vector network analyzer). Then, an evaluation of the performance of these instruments is conducted for measurements in undergraduate laboratory experiments (e.g., transmission lines, characterization of antennas and/or passive filters). The values of some characteristic parameters are confronted with measurements made with high-performance commercial RF equipment. In conclusion, reasonable accuracy can be achieved using low-cost equipment. Thus, the use of low-cost RF instrumentation is validated to increase educational activities related to hardware testing, which has a positive influence on learning quality.

When learning analog and digital communications, students often remain in a theoretical environment, missing out on the practical aspects of wireless applications. Fortunately, the growing use of software-defined radio (SDR) devices is bridging the gap between what students learn and what they will face in industry. In this work, an app-based platform for transmitting and receiving signals using two SDR devices is presented. Students will be able to generate and transmit a basic signal with a message encoded. Then, upon receiving the signal, they will be able to interactively correct frequency and phase offsets before demodulating and decoding the message. This platform gives a baseline understanding of practical wireless communications systems and the impairments these real-world applications have.

This article presents a collaborative initiative between professors of Telecommunications Engineering and Nautical Science, with the objective of providing students with multidisciplinary and transversal training. The collaboration focuses on marine radars, a topic that is common to both degrees, but approached from different perspectives. For Telecommunication Engineering students, the initiative aims at incorporating operational and functional aspects in real contexts into theoretical design tasks; for Nautical Science students, it looks for relating the usual radar operation to further theoretical foundations, and to better understand the radar performance for different configurations, scenarios and goals. The teaching methodology is based on joint sessions between professors and students of both degrees, in order to share teaching approaches and laboratory equipment. This initiative has been conducted during eight-courses, with a positive evaluation from professors and students.

ERMES 20.0 is the latest release of an open-source C++ finite element software designed to solve Maxwell's equations in the frequency domain. This version introduces new features, modules, and finite element formulations to address the complex challenges commonly encountered in the design and analysis of electromagnetic systems. Examples of ERMES 20.0 applications are: bio-electromagnetics, electrostatic discharges, electromagnetic compatibility, microwave engineering, and plasma-wave interactions. This paper highlights the key advancements in ERMES 20.0, detailing its new capabilities and demonstrating its potential to help in the numerical modeling and analysis of electromagnetic design problems.

The operation of various types of space plasma thrusters relies on heating the plasma with electromagnetic waves, typically in the MHz or GHz range. This is the case of electrodeless plasma thrusters.

To understand and characterize the propagation and absorption of electromagnetic power by the magnetoplasma, a commonly-used approach is to model the plasma as a linear, anisotropic, gyrotropic, dissipative medium based on the cold-plasma assumption.

Simulation codes ranging from finite differences (e.g. Yee scheme) to finite elements (e.g. Nédélec edge elements) are used to find the response of the wavefields to a given geometry, plasma density, and applied magnetic field profiles.

This presentation reviews recent efforts at Universidad Carlos III de Madrid to simulate electrodeless plasma thrusters with finite element schemes, and the occurrence of spurious wave solutions whenever the propagation regime includes so-called resonant cones. To characterize the spurious solutions, we set up a verification simulation case based on the Fresnel problem for a planar wave propagating in vacuum and into a plasma, and compare against the analytical solution. We find perfect agreement with our finite element solution, except for parametric regimes where the plasma has resonant cones.

Analysis of the analytical and numerical dispersion relations helps identify the sources of error, and potential countermeasures are proposed.

The study of electromagnetic waves propagation and plasma-wave coupling is a central aspect for the understanding of plasma thrusters performances, especially those driven by the excitation of radiofrequency waves, such as the Helicon Plasma Thruster. This work presents the design of a B-dot probe and its use for the characterization of the electromagnetic field patterns along the plasma plume ejected by a 450 W class helicon plasma thruster breadboard. The wave propagation results will be correlated with the thruster performances for a set of different operating conditions.

This paper presents a comparative analysis and propagation modeling of path loss (PL) in terahertz (THz) channels for indoor scenarios at 300 GHz. Experimental measurements in a conference room are used to evaluate several literature-based PL models by comparing their root-mean-square error performance. A custom-developed three-dimensional ray-launching simulation tool is introduced and validated against measurement data, yielding a mean absolute error of 0.77 dB. Furthermore, the study examines the impact of receiver height on PL characteristics by applying the Close-In PL model across multiple vertical levels of the conference room, revealing significant variations in the PL exponent and standard deviation. These findings underscore the need for height-specific channel models to support the design of robust THz communication systems for next-generation networks.

Intelligent systems increasingly leverage contextual data, such as air quality or user location, to provide enriched, context-aware services. The widespread use of IoT devices, along with advancements in computational capabilities and deep learning, is driving the development of more complex systems supporting diverse applications. However, these context-aware environments present challenges related to interoperability, scalability, and device/platform heterogeneity. Addressing them requires a structured approach, defining a set of software entities running across different contextual units and information systems that function as data collectors and aggregators. These units may employ from simple decision rules to state-of-the-art machine learning techniques to acquire knowledge and can potentially operate as distributed intelligent agents. A critical aspect of such systems is secure communication between these software entities: robust authentication, integrity, and confidentiality mechanisms are essential to maintaining system trust. This article explores the challenges of secure communications in complex, agent-based, context-aware scenarios. Moreover, it also reviews technologies to ensure confidentiality, integrity, and authentication.

The integration of cognitive systems and ambient intelligence has led to significant advancements in user-adaptive environments, particularly within Ambient Assisted Living applications. Audio-based interactions provide an intuitive and efficient means of communication, enabling a broad range of cognitive and assistive services. However, these advancements introduce substantial security and privacy concerns, particularly when processing and storing the associated data. This article presents a preliminary approach to audio-based authentication, utilizing machine learning techniques to enhance security in cognitive environments by ensuring accurate identification of individuals based on voice fingerprinting. Moreover, it outlines a data protection strategy and discusses privacy-preserving mechanisms to ensure compliance with ethical and regulatory standards.

Este trabajo presenta una solución innovadora basada en la computación Edge y la inteligencia artificial para detectar en tiempo real conductas peligrosas en entornos urbanos multimodales. Las imágenes son procesadas localmente en dispositivos embebidos desplegados en la infraestructura urbana, evitando la transmisión de imágenes sensibles y garantizando plenamente la privacidad de peatones y vehículos según las normativas europeas y españolas (RGPD y LOPDGDD). Mediante modelos avanzados de aprendizaje profundo y técnicas robustas de seguimiento multiobjeto, el sistema genera analíticas anonimizadas y alertas de seguridad proactivas. La solución propuesta contribuye significativamente a mejorar la seguridad vial, la privacidad ciudadana y la gestión inteligente del tráfico dentro del paradigma de ciudades cognitivas.

This paper presents an approach for the periodic collection of environmental data using an autonomous heterogeneous fleet of Automated Guided Vehicles (AGVs). The system integrates SLAM-based navigation, a decentralized architecture leveraging ROS 2, and secure communication protocols to ensure resilience in cognitive environments. A deployment in a real-world university setting is discussed, highlighting system performance and validation results. The proposed solution enhances se-

cure data acquisition while maintaining adaptability to dynamic environments. Additionally, its modular and scalable design makes it particularly well-suited for cognitive environments, such as smart campuses or industrial testbeds, where autonomous perception, decision-making, and interoperability are critical.

This paper focuses on the importance of radio planning and assessment of industrial environments for the future Cognitive Industry and Industry 5.0. The current and most commonly used wireless communication technologies, such as those based on the standard IEEE 802.11, Bluetooth, ZigBee, UWB, LoRaWAN, SigFox or NB-IoT already pose significant challenges regarding coexistence, coverage/capacity and noise, and interference immunity in industrial environments. The implantation of new rising technologies (e.g., Mioty, WiFi HaLow), the deployment of 5G networks in such environments (for the use of complete 5G services or RedCap devices) and the new frequency bands coming with 6G networks will create much more complex industrial environments in terms of radio planning tasks. Considering that, this work presents a deterministic simulation tool for volumetric RF analysis of industrial environments, showing the relevance of such accurate tools for the development of the future cognitive industry based on reliable and resilient wireless communication systems.

Wearable devices have gained significant popularity recently due to their ability to collect vast amounts of physiological data non-intrusively. However, these devices' resource-constrained nature often prioritises their operations' efficiency while security considerations are overlooked. This paper identifies the security vulnerabilities of EmotiBit bracelets, an open-source wearable device commonly used in healthcare and education projects. To address concerns related to data confidentiality and device authentication within this ecosystem, we propose two security schemes based on pre-shared keys and public-key cryptography. Additionally, the paper discusses the details of the implementation of these schemes and provides an evaluation of their strengths and limitations.

In 5G NR Release 18, 3GPP introduced enhanced demodulation reference signal (DMRS) to support uplink (UL) multiple user (MU) massive multiple-input multiple-output (mMIMO), enabling multiple terminals to transmit simultaneously data over the same time-frequency resources towards a gNB equipped with a large antenna array.

This paper evaluates the performance of UL MU-mMIMO, starting with a detailed analysis of the DMRS framework. We then compare the aggregated throughput to its theoretical limit, considering the typical application of adaptive modulation and coding. Our results show that throughput is strongly influenced by the number of receiving antennas. Additionally, we examine the trade-off between resource allocation overhead and channel estimation processing gain among different DMRS configurations.

Esta contribución presenta un estudio experimental del canal de propagación en interiores en la banda de 8–12 GHz, correspondiente al espectro midband/FR3, a partir de medidas de canal en banda ancha. Se adopta el modelo estadístico de Saleh–Valenzuela (S-V) para caracterizar la dispersión temporal del canal. Las componentes de trayecto múltiple se extraen mediante el algoritmo SAGE, obteniendo estimaciones de su retardo, amplitud y ángulo de llegada. A continuación, se aplican técnicas de agrupamiento basadas en el algoritmo k-means para agrupar dichas componentes y estimar los parámetros del modelo S-V. Los resultados muestran que el modelo S-V describe con precisión el comportamiento del canal en la mayoría de las posiciones del transmisor, permitiendo una representación estadística compacta y significativa del entorno de propagación.

Los sistemas de comunicación acústica submarina (UAC, Underwater Acoustic Communications) son uno de los canales de comunicación más difíciles debido a su inherente selectividad temporal y frecuencial, debida a la dispersión Doppler y a la dispersión por retardo respectivamente, especialmente en aguas poco profundas.

Este trabajo presenta la implementación de un receptor SIMO OFDM (Single-Input Multiple-Output, Orthogonal Frequency Division Multiplexing) empleando modulación QPSK (Quadrature Phase Shift Keying) diseñado para comunicaciones acústicas en aguas poco profundas. El sistema funciona en un rango ultrasónico de banda ancha de 32 kHz a 128 kHz. Se utiliza SIMO para explotar la diversidad espacial con la técnica MRC (Maximum Ratio Combining). Además, incorpora codificación de canal, utilizando un esquema LDPC (Low-Density Parity-Check) para mejorar la robustez de la transmisión. Las prestaciones del sistema se evalúan utilizando señales reales obtenidas a partir de medidas en aguas poco profundas realizadas en el Mar Mediterráneo.

Network Slicing (NS) es una tecnología clave en las redes 5G, ya que permite la creación de redes virtuales personalizadas para satisfacer los diversos requisitos de servicios como Vehicle-to-Everything (V2X) y enhanced Mobile Broadband (eMBB).

Este artículo analiza el impacto de diferentes configuraciones de partición de Physical Resource Blocks (PRBs) en un escenario multi-slice, donde dos segmentos atienden tráfico eMBB y los otros dos atienden tráfico V2X.

Utilizando un simulador de red a nivel de sistema con capacidad de slicing, evaluamos cómo la asignación de PRBs entre los segmentos afecta las métricas clave de rendimiento de la red, y en particular el cumplimiento de los requisitos de latencia para aplicaciones V2X, considerando el retardo experimentado por los paquetes.

Los resultados de este estudio ofrecen información sobre cómo la distribución de PRBs influye en la latencia de V2X y el throughput de eMBB, sentando las bases para futuras estrategias de optimización dirigidas a minimizar la latencia en aplicaciones V2X críticas.

The sensors and cameras in a car are limited to the information that the vehicle receives and processes in its immediate environment and line-of-sight applications. To further extend these data collection capabilities (with the intention of increasing traffic efficiency and safety), Cooperative Intelligent Transportation Systems (C-ITS) technologies are based on the exchange of information between vehicles through wireless communication systems and networks. This paper shows how IDIADA addresses this reality and proposes a pioneering and innovative solution for wireless networks. IDIADA has built a Connected Vehicle Hub, equipped with the latest mobile communication technologies and in compliance with the ETSI ITS G5 standard, to facilitate the construction of increasingly reliable systems, offering its facilities and adapting the platform to the needs of specific test scenarios, in order to repeat tests and evaluations that are difficult or even impossible to perform on the public road due to the constant changes in the road environment and in the networks themselves.

According to the European Road Safety Observatory, annual cyclist fatalities reached 2,035 in 2019 (41\% occurring in rural areas), with serious injuries numbering over 30,000. Innovative automotive systems and road solutions have been proposed to address many safety and emergency issues. These solutions typically involve the introduction of sensors and wireless network communications, the majority based on 5G, and recently, 6G, or 802.11p technologies. However, mobile communication systems coverage in rural areas outside sparsely populated centers is deficient. This deficiency results in many stretches, some extensive, of rural and mountainous roads lacking any form of connectivity, leading to potential communication, navigation, and emergency service access issues. This paper proposes the use of Bluetooth technology to solve the lack of connectivity, implementing a real test-bed and analyzing some key performance indicators as the coverage radio, packet error rate, and latency.

In the design and fabrication of ceramic filters, the quality of metallization is crucial for minimizing resistive losses and ensuring optimal resonator performance. This work presents the design and fabrication of a fully canonical dual-mode monoblock filter, based on BaTiO3 ceramics, operating at S-band frequencies. Sputtering deposition was used to create a 5 nm gold seed layer, on which a 30 μm copper metallization is grown through electroplating. This method guarantees high conductivity in the resonator coating, and the test results demonstrated that the fabricated device offers outstanding filtering performance with a minimal insertion loss of 0.73 dB.

We present a Low Noise Amplifier (LNA) implemented in Silicon-Germanium Heterojunction Bipolar Transistor (SiGe HBT) technology for Band C applications. This SiGe LNA is broadband, covering the frequency range of 4-8 GHz, and achieves a gain of 28 dB. The Noise Figure (NF) of the LNA is 1.5-3.5 dB across the band of interest and an output 1-dB compression point of 10 dBm. The MMIC LNA was mounted and measured to test the similarity with simulations.

RF/Microwave systems require high-speed switches, lower power consumption, smaller footprints, better power handling, and high integration. In this regard, non-volatile switches emerge as a suitable alternative to CMOS- or MEMS-based technologies, mainly due to their ability to maintain a given state without power consumption. In this article, RF memristive switches based on HfO₂ with different active area sizes were developed, fabricated, and characterized. The DC and RF cycling behavior up to 50 GHz was measured and analyzed for various configurations. An 8.1 GHz cutoff frequency was achieved for switches with a 9 µm² active area, and insertion loss lower than -2.1 dB across the entire analyzed frequency range.

Direct synthesis has been shown to provide complete control over the transfer function both in-band and out-of-band. However, finding physically realizable topologies has always been a challenge. This work introduces a methodology to assist in this process, which involves transforming the transversal matrix into a target topology, systematically progressing from the source to the load while applying step-by-step conditions to ensure a manufacturable outcome. User-friendly tools are employed, such as similarity transformations, null eigenvalue splitting, and conditions that allow isolating asymmetries outside the main path of the filter topology to extract the circuital elements. Additionally, the methodology allows for the exploration of an infinite number of possible solutions for a given topology, providing flexibility in the selection of elements to achieve a desired response.

Finding a solution for a given topology in parallel-connected filters can be challenging, particularly due to the existence of multiple possible solutions. This paper introduces a method to handle this solution multiplicity in high-order filters by focusing on the restructuring of the coupling matrix (CM). Unlike traditional approaches that analyze the entire network, this method examines each filter branch separately, where the available solutions are determined by the grouping of eigenvalues within each branch. It is further shown that the analysis may be performed for an inner transversal sub-network by first reconfiguring the N+2 transversal CM to a transversal CM of lower order than N+2. To verify the proposed approach, the results are compared against all known solutions using verification software based on the Numerical Interval Newton Algorithm (NINA), ensuring the global convergence of all solutions. As a demonstration, a 7th-order topology is presented as an example.

This paper presents the design, fabrication and characterization of a Dual-Input Load Modulated Balance Amplifier (LMBA), targeting the efficiency of the amplifier over a wide frequency range (1.4 – 2.1 GHz). This amplifier utilizes load modulation techniques to dynamically adjust the impedance seen by the transistors, ensuring high efficiency even under the amplitude variations typical of modern telecommunications systems, such as those employing QAM modulation. The prototype delivers a saturated power over 39 dBm to the load by both branches with 6 W transistors on RO4003C substrate with ε_r = 3.55 and h = 813 μm. Measurements demonstrate that at saturation, the amplifier achieves 47.7–56.2% Power Added Efficiency (PAE) in saturation and >25% at 9 dB back-off across the 1.4–2.1 GHz band.