Search Results (267)

This paper proposes a novel dual-functional radar-communication (DFRC) framework that integrates unmanned aerial vehicle (UAV) communications into an integrated sensing and communication (ISAC) system, termed the ISAC-UAV architecture. In this system, the UAV’s mobility is leveraged to simultaneously serve multiple single-antenna uplink users (UEs) and perform radar-based sensing tasks. A key challenge stems from the target position uncertainty due to movement, which impairs matched filtering and beamforming, thereby degrading both uplink reception and sensing performance. Moreover, UAV energy consumption associated with mobility must be considered to ensure energy-efficient operation. We aim to jointly maximize radar sensing accuracy and minimize UAV movement energy over multiple time steps, while maintaining reliable uplink communications. To address this multi-objective optimization, we propose a deep reinforcement learning (DRL) framework based on a long short-term memory (LSTM)-enhanced deep deterministic policy gradient (DDPG) network. By leveraging historical target trajectory data, the model improves prediction of target positions, enhancing sensing accuracy. The proposed DRL-based approach enables joint optimization of UAV trajectory and uplink power control over time. Extensive simulations validate that our method significantly improves communication quality and sensing performance, while ensuring energy-efficient UAV operation. Comparative results further confirm the model’s adaptability and robustness in dynamic environments, outperforming existing UAV trajectory planning and resource allocation benchmarks. Full article

Space-based gravitational wave detectors, such as the Laser Interferometer Space Antenna (LISA) and Taiji, will observe GWs from $O\left({10}^8\right)$ galactic binary systems, allowing a completely unobscured view of the Milky Way structure. While previous studies have established theoretical expectations based on idealized data-analysis methods that use the true catalog of sources, we present an end-to-end analysis pipeline for inferring galactic structure parameters based on the detector output alone. We employ the GBSIEVER algorithm to extract GB signals from LISA Data Challenge data and develop a maximum likelihood approach to estimate a bulge-disk galactic model using the resolved GBs. We introduce a two-tiered selection methodology, combining frequency derivative thresholding and proximity criteria, to address the systematic overestimation of frequency derivatives that compromises distance measurements. We quantify the performance of our pipeline in recovering key Galactic structure parameters and the potential biases introduced by neglecting the errors in estimating the parameters of individual GBs. Our methodology represents a step forward in developing practical techniques that bridge the gap between theoretical possibilities and observational implementation. Full article

Two-dimensional (2D) materials have been proposed for use in a multitude of applications, with graphene being one of the most well-known 2D materials. Despite their potential to contribute to innovative solutions, the fabrication of such devices still faces significant challenges. One of the key challenges is the fabrication at a wafer-level scale, a fundamental step for allowing reliable and reproducible fabrication of a large volume of devices with predictable properties. Overcoming this barrier will allow further integration with sensors and actuators, as well as enabling the fabrication of complex circuits based on 2D materials. This work presents the fabrication steps for a process that allows the on-wafer fabrication of active and passive radiofrequency (RF) devices enabled by graphene. Two fabrication processes are presented. In the first one, graphene is transferred to a back gate surface using critical point drying to prevent cracks in the graphene. In the second process, graphene is transferred to a flat surface planarized by ion milling, with the gate being buried beneath the graphene. The fabrication employs a damascene-like process, ensuring a flat surface that preserves the graphene lattice. RF transistors, passive RF components, and antennas designed for backscatter applications are fabricated and measured, illustrating the versatility and potential of the proposed method for 2D material-based RF devices. The integration of graphene on devices is also demonstrated in an antenna. This aimed to demonstrate that graphene can also be used as a passive device. Through this device, it is possible to measure different backscatter responses according to the applied graphene gating voltage, demonstrating the possibility of wireless sensor development. With the proposed fabrication processes, a flat graphene with good quality is achieved, leading to the fabrication of RF active devices (graphene transistors) with intrinsic f_T and f_max of 14 GHz and 80 GHz, respectively. Excellent yield and reproducibility are achieved through these methods. Furthermore, since the graphene membranes are grown by Chemical Vapor Deposition (CVD), it is expected that this process can also be applied to other 2D materials. Full article

Deployable thin-film antennas deliver large aperture gains and high stowage efficiency for spaceborne phased arrays but suffer wrinkling-induced planarity loss and radiation distortion. To bridge the lack of electromechanical coupling models for tensioned thin-film patch antennas, we present a unified framework combining structural deformation and electromagnetic simulation. We derive a coupling model capturing the increased bending stiffness of stepped-thickness membranes, formulate a wrinkling analysis algorithm to compute tension-induced displacements, and fit representative unit-cell deformations to a dual-domain displacement model. Parametric studies across stiffness ratios confirm the framework’s ability to predict shifts in pattern, gain, and impedance due to wrinkling. This tool supports the optimized design of wrinkle-resistant thin-film phased arrays for reliable, high-performance space communications. Full article

This systematic review explores recent advancements in antenna and rectifier systems for radio frequency (RF) energy harvesting within the gigahertz frequency range, aiming to support the development of sustainable and efficient low-power electronic applications. Conducted under the PRISMA methodology, our review filtered 2465 initial records down to 80 relevant studies, addressing three research questions focused on antenna design, operating frequency bands, and rectifier configurations. Key variables such as antenna type, resonant frequency, gain, efficiency, bandwidth, and physical dimensions were examined. Antenna designs including fractal, spiral, bow-tie, slot, and rectangular structures were analyzed, with fractal antennas showing the highest efficiency, while array antennas exhibited lower performance despite their compact dimensions. Frequency band analysis indicated a predominance of 2.4 GHz and 5.8 GHz applications. Evaluation of substrate materials such as FR4, Rogers, RT Duroid, textiles, and unconventional composites highlighted their impact on performance optimization. Rectifier systems including Schottky, full-wave, half-wave, microwave, multi-step, and single-step designs were assessed, with Schottky rectifiers demonstrating the highest energy conversion efficiency. Additionally, correlation analyses using boxplots explored the relationships among antenna area, efficiency, operating frequency, and gain across design variables. The findings identify current trends and design considerations crucial for enhancing RF energy harvesting technologies. Full article

In this article, we propose a novel near-field holographic microwave imaging technique designed to accelerate the data acquisition process. The system employs a novel electronic switching mechanism utilizing two switching networks that virtually rotate the transmitting and receiving antennas along the azimuthal direction for efficient data collection. This minimizes the need for mechanical scanning of the antennas which, in turn, leads to faster data acquisition. To enhance the quality of the imaging outcome, the number of samples can be increased by combining only a few mechanical scanning steps with the electronic scanning. This data acquisition scheme leverages the system’s space-invariant property to enable convolution-based near-field holographic microwave image reconstruction. By capturing and processing scattered fields over a cylindrical aperture, the system achieves high-resolution imaging of concealed objects across multiple range positions. Both simulation and experimental results validate the effectiveness of the proposed approach in delivering high-quality imaging results. Its ability to provide faster and enhanced imaging outcomes highlights its potential for a wide range of applications, including biomedical imaging, security screening, and non-destructive testing of the materials. Full article

This study introduces a Self-Attention (SA) Generative Adversarial Network (GAN) framework that applies artificial intelligence techniques to microwave sensing for electromagnetic imaging. The approach involves illuminating anisotropic objects using Transverse Magnetic (TM) and Transverse Electric (TE) electromagnetic waves, while sensing antennas collecting the scattered field data. To simplify the training process, a Back Propagation Scheme (BPS) is employed initially to calculate the preliminary permittivity distribution, which is then fed into the GAN with SA for image reconstruction. The proposed GAN with SA offers superior performance and higher resolution compared with GAN, along with enhanced generalization capability. The methodology consists of two main steps. First, TM waves are used to estimate the initial permittivity distribution along the z-direction using BPS. Second, TE waves estimate the x- and y-direction permittivity distribution. The estimated permittivity values are used as inputs to train the GAN with SA. In our study, we add 5% and 20% noise to compare the performance of the GAN with and without SA. Numerical results indicate that the GAN with SA demonstrates higher efficiency and resolution, as well as better generalization capability. Our innovation lies in the successful reconstruction of various uniaxial objects using a generator integrated with a self-attention mechanism, achieving reduced computational time and real-time imaging. Full article

This paper presents the design of an orientation-independent non-invasive glucose sensor based on a meta-structured antenna. The sensor is designed for blood glucose measurement through fingertip placement on the sensor and features a mushroom structure to generate zeroth-order resonance (ZOR). Moreover, the mushroom structure has a hexagonal patch for orientation-independent non-invasive sensing. The operating frequency of the sensor is 4 GHz, and the overall size is 55 mm × 55 mm. In our study, the range of glucose concentration is from 50 to 250 mg/dL, with a step size of 50 mg/dL. The simulated and measured results show a linear relationship between the resonance frequency and the glucose concentration in the solution, and the linear shift of 0.352 MHz/mg/dL has been observed. On the other hand, the reflection coefficient level variation is a nonlinear function of the glucose concentration for the considered concentration ranges. Mathematical models describing the sensor response across all fingertip orientations are developed for the designed sensor using the regression analysis (R² ≥ 0.993) relating the glucose concentration to the measured resonance frequency and reflection coefficient level. While the reflection coefficient shows a nonlinear response, the resonance frequency exhibits a strong linear correlation with glucose concentration, making it a more reliable parameter for accurate prediction in the proposed sensing model. Full article

This paper investigates the potential for interference from multipoint video distribution systems (MVDS) transmissions, specifically side lobe radiation in Lebanon, to geostationary Earth orbit (GEO) satellites. Through simulation and analysis of antenna radiation patterns, the impact of varying MVDS power levels on the carrier-to-noise ratio (C/N) at the satellite receiver is quantified. The results demonstrate a significant degradation in signal quality, with the C/N dropping to −2.29 dB at an MVDS power of 0 dBW for the current system. To mitigate this interference, a two-step potential strategy is proposed and evaluated. The study boosts the potential for the coexistence of MVDS and GEO satellite services in the Ku-band within the Lebanese context. Full article

In this study, a novel improved ultra-wideband (UWB) antipodal Vivaldi antenna suitable for breast cancer detection via microwave imaging was designed. The antenna was made more directional by adding three pairs of nestings to the antenna fins by adding elliptical patches. The frequency operating range of the proposed antenna is UWB 3.6–13 GHz, its directivity is 11 dB, and its gain is 9.27 dB. The antenna is designed with FR4 dielectric material and dimensions of 34.6 mm × 33 mm × 1.6 mm. It was demonstrated that the bandwidth, gain, and directivity of the proposed antenna meet the requirements for UWB radar applications. The Vivaldi antenna was tested on an imaging system developed using the CST Microwave Studio (CST MWS) program. In CST MWS, a hemispherical heterogeneous breast model with a radius of 50 mm was created and a spherical tumor with a diameter of 0.9 mm was placed inside. A Gaussian pulse was sent through Vivaldi antennas and the scattered signals were collected. Then, adaptive Wiener filter and image formation algorithm delay-multiply-sum (DMAS) steps were applied to the reflected signals. Using these steps, the tumor in the breast model was scanned at high resolution. In the simulation application, the tumor in the heterogeneous phantom was detected and imaged in the correct position. A monostatic radar-based system was implemented for scanning a breast phantom in the prone position in an experimental setting. For experimental measurements, homogeneous (fat and tumor) and heterogeneous (skin, fat, glandular, and tumor) breast phantoms were produced according to the electrical properties of the tissues. The phantoms were designed as hemispherical with a diameter of 100 mm. A spherical tumor tissue with a diameter of 16 mm was placed in the phantoms produced in the experimental environment. The dynamic range of the VNA device used allowed us to image a 16 mm diameter tumor in the experimental setting. The developed microwave imaging system shows that it is suitable for the early-stage detection of breast cancer by scanning the tumor in the correct location in breast phantoms. Full article

In the context of Doppler radar, studies have examined the changes in the phase shift of the S₂₁ transmission coefficient related to minute movements of the human chest as a response to breathing or heartbeat. Detecting human vital signs remains a challenge, especially when obstacles interfere with the attempt to detect the presence of life. The sensitivity of a measurement system’s perception of vital signs is highly dependent on the monitoring systems and antennas that are used. The current work proposes a computational approach that aims to extract an empirical law of the dependence of the phase shift of the transmission coefficient (S₂₁) on the sensitivity at reception, based upon a set of four parameters. These variables are as follows: (a) the frequency of the continuous wave utilized; (b) the antenna type and its gain/directivity; (c) the electric field strength distribution on the chest surface (and its average value); and (d) the type of material (dielectric properties) impacted by the incident wave. The investigated frequency range is (1–20) GHz, while the simulations are generated using a doublet of dipole or gain-convenient identical Yagi antennas. The chest surface is represented by a planar rectangle that moves along a path of only 3 mm, with a step of 0.3 mm, mimicking respiration movement. The antenna–target system is modeled in the computational space in each new situation considered. The statistics illustrate the multiple regression function, empirically extracted. This enables the subsequent building of a continuous-wave bio-radar Doppler system with controlled and improved sensitivity. Full article

A LoRaWAN application architecture comprises three functional components: (i) nodes, which convert and wirelessly transmit data as LoRaWAN messages; (ii) gateways, which receive and forward these transmissions; and (iii) network servers, which process the received data for application delivery. The nodes convert data into LoRaWAN messages and transmit them wirelessly with the hope that one or more LoRaWAN gateway will receive the messages successfully. Then, the gateways pass on the received messages to a distant network server, where various processing steps occur before the messages are forwarded to the end application. If none of the gateways can receive the messages, then they will be lost. Although this default behaviour is suitable for some applications, there are others where ensuring messages are successfully delivered at a higher rate would be helpful. One such scenario is the application in this paper: monitoring maritime vessels and fishing equipment in offshore environments characterised by intermittent or absent shore connectivity. To address this challenge, the Custodian project was initiated to develop a maritime monitoring solution with enhanced connectivity capabilities. Two additional features are especially welcome in this scenario. The most important feature is the transmission of messages created in offshore areas to end users who are offshore, regardless of the unavailability of the ground network server. An example would be fishermen who are offshore and wish to position their fishing equipment, also offshore, based on location data transmitted from nodes via LoRaWAN, even when both entities are far away from the mainland. The second aspect concerns the potential use of gateway-to-gateway communications, through gateways on various ships, to transmit messages to the coast. This setup enables fishing gear and fishing vessels to be monitored from the coast, even in the absence of a direct connection. The functional constraints of conventional commercial gateways necessitated the conceptualisation and implementation of C-Mesh, a novel relay architecture that extends LoRaWAN functionality beyond standard protocol implementations. The C-Mesh integrates with the Custodian ecosystem, alongside C-Beacon and C-Point devices, while maintaining transparent compatibility with standard LoRaWAN infrastructure components through protocol-compliant gateway emulation. Thus, compatibility with both commercially available nodes and gateways and those already in deployment is guaranteed. We provide a comprehensive description of C-Mesh, describing its hardware architecture (communications, power, and self-monitoring abilities) and data processing ability (filtering duplicate messages, security, and encryption). Sea trials carried out on board a commercial fishing vessel in Sesimbra, Portugal, proved C-Mesh to be effective. Location messages derived from fishing gear left at sea were received by an end user aboard the fishing vessel, independently of the network server on land. Additionally, field tests demonstrated that a single C-Mesh deployment functioning as a signal repeater on a vessel with an antenna elevation of $15m$ above sea level achieved a quantifiable coverage extension of 13 km (representing a 20% increase in effective transmission range), demonstrating the capacity of C-Mesh to increase LoRaWAN’s coverage. Full article

The early diagnosis of Alzheimer’s disease remains an unmet medical need due to the cost and invasiveness of current methods. Early detection would ensure a higher quality of life for patients, enabling timely and suitable treatment. We investigate microwave sensing for low-cost, non-intrusive early detection and assessment of Alzheimer’s disease. This study is based on the emerging evidence that the electromagnetic properties of cerebrospinal fluid are affected by abnormal concentrations of proteins recognized as early-stage biomarkers. We design a conformal six-element antenna array placed on the upper portion of the head, operating in the 500 MHz to 6.5 GHz band. It measures scattering response due to changes in the dielectric properties of intracranial cerebrospinal fluid. A multi-layer perceptron network extracts the diagnostic information. Data classification consists of two steps: binary classification to identify the disease presence and multi-class classification to evaluate its stage. The algorithm is trained and validated through controlled experiments mimicking various pathological severities with an anthropomorphic multi-tissue head phantom. Results support the feasibility of the proposed method using only amplitude data and lay the foundation for more extensive studies on microwave sensing for early Alzheimer’s detection. Full article

This article presents a brief evaluation and discussion of eight proposed printed log-periodic dipole array (PLPDA) antennas that have been introduced in the last decade for EMC applications. These proposed antennas could serve as reference antennas for radiation and immunity tests inside the EMC chamber. Step-by-step design procedures have been detailed with various feeding methods, showing their effect on the wideband characteristic compared to the design complexity. Different miniaturization and bandwidth improvement methods have been utilized to tackle the size reduction and bandwidth enhancement goals. Furthermore, the comprehensive view of the specifications of the reference antenna design inside the EMC chamber has been explained in detail, which presents the motivation for using a printed antenna rather than the classical one for these applications. The achievements of the presented designs have been listed, compared, and discussed with the classical LPDA antenna (HyperLOG 7060) offered for sale. Finally, a brief conclusion presents the recommendations for the design and analysis of the PLPDA antenna for EMC measurements. Full article

The fully polarimetric aperture synthesis radiometer (FPASR) is capable of acquiring the fully polarimetric brightness temperature (BT), which has become increasingly significant in remote sensing. Antenna pattern errors can introduce significant errors to the reconstructed image of the FPASR. Analyzing and correcting the antenna pattern errors is crucial for obtaining high-quality BT images. In this paper, the antenna pattern errors are analyzed and classified into additive and multiplicative errors. A two-step correction method is proposed to reduce the influence of antenna pattern errors on the reconstructed BT. An end-to-end simulator for FPASR has been developed to assess both the antenna pattern errors and the effectiveness of the correction method. The simulation results show that the two-step correction method can reduce the brightness temperature error caused by the antenna pattern errors by over 70%. The successful image of the flight experiment validates the correction method as well. Full article