The present study presents long-term monitoring data on the dynamics of bedload transport processes in alpine gravel-bed river systems in Austria (Urslau, Strobler-Weißenbach) using radio frequency identification (RFID) technology. The detection of embedded RFID tracers was facilitated by the use of stationary antennas. This methodology enabled the acquisition of high-resolution data on particle transport velocities, transport distances, and sediment dynamics. Monitoring has been in operation permanently over a period of 8 years, including several intense flood events. In total, 1612 RFID-tagged stones were deployed, and the maximum measured particle velocity was 2.47 m s−1. The measurements at the Urslau stream revealed seasonal variability and long-term trends, while targeted short-term measurements at the Strobler-Weißenbach stream provided valuable insights into the dynamics of flood events. The results underscore the significance of environmental factors, including the grain size, river gradient, and hydraulic parameters, in the dynamics of bedload transport in alpine gravel bed streams. Furthermore, the efficiency of stationary antennas was optimised to ensure uninterrupted monitoring. This study underscores the importance of contemporary monitoring technologies in analysing river processes and addressing challenges, including those brought about by climate change.

Tulip tree leaf-shaped microstrip MIMO antenna utilizing the superformula

The emergence of sixth-generation (6G) wireless networks demands broadband antennas capable of ultra-high data throughput and seamless global connectivity. This study presents a genetic-algorithm (GA) optimization framework to enhance antenna performance, focusing on patch dimensions, ground-plane size, and feed position. Full-wave electromagnetic simulations were performed in CST Microwave Studio and ANSYS HFSS, employing defined mesh sizes, solver types, and boundary conditions to ensure accurate evaluation. The GA-based optimization achieved an impedance bandwidth of 3.2–6.1 GHz, a peak gain improvement of 2.8 dB, and radiation efficiency exceeding 92%, outperforming conventional gradient-based tuning. The optimized antenna exhibited stable S-parameters and an omnidirectional radiation pattern across the target spectrum, confirming reliable operation at high frequencies. This approach highlights the advantages of evolutionary algorithms in enabling efficient, manufacturable, and high-performance broadband antenna designs for next-generation wireless systems. Beyond immediate 6G applications, the methodology can be extended to millimeter-wave and terahertz antennas, supporting continued innovation in ultra-reliable, high-capacity wireless communications.

Highly sensitive, gain and efficient metamaterial THz antenna for biosensing

This paper presents a low-frequency self-biased magnetoelectric (ME) antenna with enhanced radiation performance through synergistic operation with a coil resonant circuit. For a given drive voltage, the inductance of the series-resonant circuit can be optimized by adjusting the number of turns of the coil, thus enabling the circuit’s reactance to approach zero under optimal bias magnetic field conditions. This design enhances the antenna’s radiation performance and eliminates the need for external permanent magnets, simplifying the device structure and improving reliability. Experimental results indicate that the magnetic induction strength of the self-biased ME antenna is 3.17 times greater than that of conventional ME antennas, and the 3-dB bandwidth is significantly expanded at two different resonant frequencies, achieving increases of 4.32 and 7.09 times, respectively. Meanwhile, the magnetic induction intensity and antenna efficiency of Composite source radiation magnetoelectric (CSRME) antenna have been greatly improved.

ABSTRACT An equivalent circuit‐based microstrip antenna of dual‐band characteristics has been planned by cutting six vertical rectangular notches of different sizes in this article. The bandwidth of the presented antenna is achieved 23.77% (420 MHz) and 5.46% (137 MHz). The antenna is resonating in dual band at 1.903 and 2.489 GHz with return losses of −35.28 and −23.10 dB, respectively. The suggested antenna structure have frequency band between 1.557 and 1.977 GHz in the lower band and 2.441 and 2.578 GHz in the upper band. The gain of the suggested antenna is 3.760 dBi at 1.903 GHz and 3.803 dBi at 2.489 GHz. The efficiency of proposed antenna is 90% and 89% at both resonating frequencies 1.903 and 2.489 GHz, respectively. However, more than 81% antenna efficiency is observed in both operating bands. The suggested microstrip antenna is fabricated on FR‐4 substrate of size 39.04 × 47.64 mm 2 (0.25 × 0.30 at frequency 1.903 GHz) and excited by microstrip line feed of 50 Ω. The presented design of antenna is validated with measurement and equivalent circuit. The lower resonating band 1.557–1.977 GHz is suitable for GPS (1.575 GHz), GSM 2G (1.8 GHz), and PCS (1.90 GHz). However, upper resonating band 2.441–2.578 GHz is suitable for Bluetooth (2.45 GHz), ISM band (2.45 GHz), and 4G (2.5 GHz) applications.

This paper presents a slot array antenna composed of H-plane horns as radiating slots and a pillbox feeding mechanism in gap waveguide (GW) technology. This new configuration presents a new full-metal slot array antenna with low complexity, fabrication cost, and high gain with directive radiation, which can make it a good candidate for use in long-range wireless systems. Making use of an H-plane reflector in the feeding part of the antenna has removed the need for a corporate feed network and enhanced the structure’s simplicity. Moreover, the use of semi-horn-shaped radiating slots has improved the antenna efficiency by resolving the grating lobe issue associated with transverse slots. These features make the proposed antenna easily scalable for higher gains without imposing extra complexity on the design and fabrication process. The GW technology also lets the proposed antenna be a promising solution for the next-generation millimeter-wave systems. In addition, the proposed fully metallic antenna leverages a design that offers high efficiency and a flat gain response over the desired bandwidth. A fabricated prototype exhibits 60–90% overall efficiency over an impedance bandwidth of about 8% (:{S}_{11} < -10 dB), and a 2.5 dB gain variation across the operating bandwidth.

A Deep Learning Approach for Classifying the Efficiency of Dual-Band Wearable Antennas in Remote Healthcare

Abstract A stepped C shaped patch with parasitic elements symmetrically placed along the width of the driven patch produces a moderate gain 8.24 dBi at center frequency 3.5 GHz and wide band from 3.29 to 3.71 GHz (12 %). It covers both n77 and n78 band of 5G New Radio (NR) frequencies ranging from 3.3–4.2 GHz and 3.3–3.8 GHz respectively. C-Band (3.4–4.2 GHz) used for 5G, satellite communications and wireless broadband and 3GPP LTE-42 band (3.4–3.6 GHz) used for Long Term Evolution (LTE) and 5G deployments. The proposed design has a planar structure with substrate height 3.2 mm and ground plane dimension 41 mm × 110 mm. Fabricated prototype is tested with measured S 11 of &lt;−10 dB throughout the intended bandwidth and provides unidirectional radiation pattern used for small cell outdoor applications. The antenna has an excellent overall efficiency of 97.73 %. Therefore, the proposed antenna prototype is suitable for outdoor small cell with broad spectrum under 5G new Radio 1(nR1) band.

ABSTRACT The evolution of wireless communication systems has driven the demand for efficient, compact, and versatile antenna designs. Among the various types of antennas, microstrip planar antennas have gained significant attention due to their low‐profile structure, compatibility with modern electronic circuits, and ease of fabrication. Designing a microstrip planar antenna using optimization techniques involves finding the optimal parameters that result in the best performance for specific design criteria, which significantly improves the performance of the antenna while also minimizing costs and space requirements. Accordingly, this paper proposes a novel optimal design for a microstrip planar antenna. This study focused on designing an optimal microstrip planar antenna by a new optimization algorithm termed rhinopithecus swarm assisted hippopotamus optimization (RAHO) by carefully considering key parameters and that significantly influence the antenna's performance. The analysis proves the performance of the proposed antenna design with maximization of antenna gain with 6.41% enhancement than the RSOA algorithm.

A meander line antenna (MLA) is well known for its compact size and efficient performance in terms of antenna efficiency, input resistance, and bandwidth. This study investigates MLA performance in human body environments, focusing on medical devices and wireless implants. Due to their small size, MLAs are ideal for use in biological tissues with complex and lossy properties. The study analyzes MLA behavior in fat and muscle tissues, considering key parameters such as conductivity, radiation efficiency, and self-resonance. Input resistance and Voltage Standing Wave Ratio (VSWR) are examined. The smallest antenna size of (14.9 × 4.1 × 0.1) mm³ is achieved. Human body phantoms for fat and muscle tissues were successfully formulated and fabricated, with dielectric constants aligning with reference values. A Q factor of approximately 2 was obtained through VSWR characteristics and validated against theoretical calculations, showing a 92% agreement. MLA gains of −30 dBi and −40 dBi were recorded in fat and muscle phantoms, respectively. These findings enhance the understanding of MLA performance in human tissue environments, supporting the development of next-generation implanted technologies for clinical and therapeutic applications.

Abstract Photoconductive antennas (PCAs), known for their broad bandwidth, high data rates, and simple structure, are gaining significant attention in terahertz (THz) applications. Over the past decade, THz PCAs have been extensively researched, demonstrating diverse applications across multiple fields. This paper provides a comprehensive review of PCA theory and design, along with an in-depth analysis of their relative advantages. Additionally, various strategies for enhancing antenna efficiency are discussed, focusing on material selection and geometric design. This review aims to offer researchers a consolidated resource, presenting key insights into the challenges and advancements in PCA research.

This research paper presents the results of an analysis conducted on a microstrip patch antenna designed to operate within the 1.559–1.591 GHz frequency band, which encompasses three major satellite constellations: GPS, Galileo and BeiDou. The objective of this study is to perform a comparative evaluation of the materials used in the antenna design, assess the geometric configuration and analyze the key performance parameters of the proposed microstrip patch antenna. Prior to the numerical modeling and simulation process, a preliminary assessment was conducted to evaluate how different substrate materials influence antenna efficiency. For instance, a comparison between FR-4 and RT Duroid 5880 dielectric substrates revealed signal attenuation differences of approximately −1 dB at the target frequency. The numerical simulations were carried out using Ansys HFSS design. The antenna was mounted on a dielectric substrate, which was also mounted on a ground plane. The microstrip antenna was fed using a coaxial cable at a single point, strategically positioned to achieve circular polarization within the operating frequency band. The aim of this study is to design and analyze a microstrip antenna that operates within the previously specified frequency range, ensuring optimal impedance matching of 50 Ω with a return loss of S11 &lt; −10 dB at the operating frequency (with these parameters also contributing to the definition of the antenna’s operational bandwidth). Furthermore, the antenna is required to provide a gain greater than 3 dB for integration into GNSS’ receivers and to achieve an Axial Ratio value below 3 dB in order to ensure circular polarization, thereby facilitating the antenna’s integration into GNSSs.

ABSTRACTMicrostrip patch antenna (MPA) single‐element, half‐array, and multiple‐input multiple‐output (MIMO) designs, with an overall MIMO antenna size of 32.02 × 32.02 mm2, are built and analyzed in this study. The bandwidth of 4.12 GHz and the band of frequencies 25.605–29.727 GHz are the values used in the simulation. Rogers RT/duroid 5880, a low‐loss dielectric material, is used in the antenna's fabrication. This material has a dielectric constant of 2.2, a tangent loss of 0.0009, and an ultrathin height of 0.8 mm. The analogous model of the proposed MPA is constructed using an advanced design system (ADS) in contrast to the reflection coefficient gained using CST. The return loss of the prototype is also measured and is in contrast to the return loss seen in CST simulations. In the end, 120 data samples are collected through the simulation by using CST MWS, and five machine learning (ML) approaches, such as Nonparametric regression, random forest regression (RFR), decision tree regression (DTR), support vector regression model (SVRM), and extreme gradient boosting (XGB) regression, are implemented to evaluate the efficiency of the patch antenna. Mean square error, mean absolute error, root mean square error, R square, and the variance score are used to assess the efficacy of the five ML models. Nonparametric Regression outperforms the other ML models in terms of prediction accuracy (MSE = 2.31%, MAE = 1.77%, RMSE = 3.33%, R square = 94.28%, and var. score = 95.62%). This article describes analyzing the constructed antenna's performance by a combination of modeling, measurement, building the RLC equivalent circuit model, and incorporating machine learning approaches.

Simulation of the Antenna–Plasma Coupling Efficiency of the Three-Loop ICR Antenna of the T-15MD Tokamak

Microstrip patch antennas are extensively utilized in modern communication systems because of their small size and simple fabrication process. Among the different patch geometries, triangular patches offer size reduction compared to their rectangular and circular counterparts, making them suitable for space-constrained applications. This study focuses on the design and analysis of an equilateral triangular microstrip antenna (ETMSA) using proximity coupled feed with a triangular slot, targeting optimal performance at 2.2 GHz. The antenna is constructed using two FR4 substrates of identical permittivity but different thicknesses (h1 and h2), with a 50-ohm microstrip line feed positioned between them. The aim is to determine the optimal values of patch surface area, slot dimensions, and upper substrate thickness to achieve maximum bandwidth, minimal return loss, and ideal voltage standing wave ratio (VSWR). Simulations and measurements confirm that the antenna achieves a 120 MHz bandwidth achieving a return loss of –42 dB and a VSWR of 1.03, demonstrating excellent agreement. These results confirm the antenna's effectiveness for fixed-beam applications in wireless communication systems, highlighting its potential for efficient and compact antenna solutions.

This paper presents an innovative end-to-end framework for conformal antenna array design and beam steering in Low Earth Orbit (LEO) satellite-based IoT communication systems. We propose a multi-stage learning architecture that integrates machine learning (ML) for antenna parameter prediction with reinforcement learning (RL) for adaptive beam steering. The ML module predicts optimal geometric and material parameters for conformal antenna arrays based on mission-specific performance requirements such as frequency, gain, coverage angle, and satellite constraints with an accuracy of 99%. These predictions are then passed to a Deep Q-Network (DQN)-based offline RL model, which learns beamforming strategies to maximize gain toward dynamic ground terminals, without requiring real-time interaction. To enable this, a synthetic dataset grounded in statistical principles and a static dataset is generated using CST Studio Suite and COMSOL Multiphysics simulations, capturing the electromagnetic behavior of various conformal geometries. The results from both the machine learning and reinforcement learning models show that the predicted antenna designs and beam steering angles closely align with simulation benchmarks. Our approach demonstrates the potential of combining data-driven ensemble models with offline reinforcement learning for scalable, efficient, and autonomous antenna synthesis in resource-constrained space environments.

The rapid advancement of wireless biomedical systems necessitates the development of compact, efficient, and reliable antennas capable of operating across multiple frequency bands. Traditional designs, such as bow-tie antennas, offer broadband performance but often face drawbacks including limited selectivity, reduced isolation, and lower suitability for medical applications. To overcome these limitations, this study introduces a dual circular patch antenna integrated with a metasurface layer. The design objective is to enhance the performance of bow-tie antennas for microwave applications in biomedical and biological phantoms, using metasurfaces within a transmission line model. The metasurface facilitates improved impedance matching, enhances directivity, and minimizes mutual coupling, thereby ensuring stable multi-band operation. Simulation results demonstrate notable improvements in directivity making the antenna well-suited for biomedical applications such as microwave imaging, implantable devices, and wireless body area networks. The proposed circular patch design further emphasizes the effectiveness of metasurfaces in achieving safer, more accurate, and efficient biomedical communication systems.

Since the beginning of the 21st century, mobile technology has become a core infrastructure across various industries, such as healthcare, manufacturing, military, and home appliances. Microwave and RF electromagnetic waves are essential for mobile devices such as smartphones; however, they can cause tissue damage when absorbed by human tissues. Thus, countries worldwide have established regulations on specific absorption rate (SAR) based on international standards and legally require disclosure of SAR values for devices. Various technologies have been developed to reduce SAR, mainly by increasing the distance between the antenna and the head using RF shielding materials, or considering antenna structure in the early stages of product design. However, these methods can degrade antenna efficiency, which directly affects communication performance. This study investigated the conditions under which an anisotropic magneto-dielectric sheet can be placed between a mobile device and the human head to effectively reduce SAR without degrading antenna performance. The material properties of the anisotropic magneto-dielectric sheet were varied through simulations to derive the optimal combinations for SAR reduction.

The fifth-generation (5G) wireless communication system demands compact and efficient antenna architectures capable of supporting dual-band operation. This work proposes a hybrid multiple-input multiple-output (MIMO) antenna system integrating planar dipole elements for Sub-6 GHz operation and tapered slot Vivaldi antennas for millimeter-wave (mmWave) bands. The antenna is fabri- cated on a Rogers RT/Duroid 5880 substrate and covers two frequency ranges: 3.4–10 GHz and 22.1–40 GHz. Simulations performed using ANSYS HFSS show that the antenna achieves wide impedance bandwidth, high gain (up to 7.18 dBi), and mutual coupling below –20 dB. These features support omnidirectional and directional radiation patterns, making the design suitable for compact 5G terminals.