Search Results (25)

A physical and mathematical model is proposed that takes into account the sequential interaction of electromagnetic, temperature, and mechanical fields to assess the thermostressed state of an electroconductive body and predict its load-bearing capacity under the action of an external non-stationary electromagnetic field. Initial-boundary problems are formulated to determine the parameters of the electromagnetic field, temperature, dynamic thermoelastic stresses, and their intensities in a long, solid, non-ferromagnetic electroconductive cylinder. Based on the Huber–von Mises criterion, an assessment of the load-bearing capacity of this cylinder is proposed. A numerical analysis of Joule heat, ponderomotive force, temperature, components of the dynamic stress tensor, and their intensities in a solid stainless-steel cylinder under the action of an amplitude-modulated radio pulse is performed. The limiting values of the amplitude–frequency characteristics and the duration of the electromagnetic action, at which the cylinder under consideration retains its load-bearing capacity as a structural element, have been established. Full article

Although high-frequency electromagnetic methods, such as Radio Magnetotellurics (RMT) and Controlled-Source Radio Magnetotellurics (CSRMT), are highly effective for shallow-to-medium depth exploration, deploying traditional transmitter–receiver setups remains labor-intensive and significantly slows down large-scale surveys. To overcome these logistical bottlenecks, we developed a mobile Ultra-Audio Frequency Electromagnetic (UAEM) measurement system. While the hardware is designed with dual-mode capabilities supporting conventional controlled-source operations, this paper specifically focuses on its application in a Signals of Opportunity (SOOP) mode. By utilizing pre-existing, stable anthropogenic signals, including Amplitude Modulation (AM) broadcasts and naval very low frequency communications, the system effectively functions as a broadband RMT receiver. Technical evaluations demonstrate that the instrument operates across a 1 Hz to 1000 kHz bandwidth with a high sampling rate of 2.5 MHz. Furthermore, it achieves a dynamic range of 143 dB and maintains an apparent resistivity measurement accuracy of better than 3%. Thanks to its modular, vehicle-towed design, the UAEM system enables continuous, on-the-move data acquisition wherever ambient field sources are available. This approach eliminates the need for dedicated transmitter deployment, fundamentally reducing exploration costs and boosting overall survey efficiency. Full article

This paper proposes a SIM-compatible hardware coordination architecture for secure radio-frequency (RF)-triggered activation in mobile devices. The proposed concept functions as a passive coordination layer rather than as an additional wireless transceiver, enabling controlled interaction between external low-frequency RFID or high-frequency NFC fields and wireless subsystems already available in the host device. The architecture assumes a flexible nano-SIM-compatible form factor integrating passive RF detection structures, a trusted decision component, and a trigger-generation interface aligned with standard SIM/UICC electrical and logical interaction models. Upon detection of an external electromagnetic field, the coordination layer evaluates predefined authorization conditions and produces a controlled trigger event intended to propagate through existing telephony and system-service pathways. In contrast to architectures that embed active wireless transmitters, the proposed approach seeks to minimize hardware redundancy and reduce potential attack surfaces by relying on the host device’s native Bluetooth Low Energy (BLE) capabilities. Rather than directly controlling wireless modules, the interface operates as a hardware-originated coordination mechanism that may support low-power and context-aware activation scenarios in mobile and embedded environments. This paper focuses on the architectural model, system assumptions, security rationale, and implementation constraints of such a SIM-compatible interface. Particular attention is given to integration considerations related to smartphone baseband architectures, operating-system mediation, and secure-element isolation. The presented concept establishes a foundation for future prototype implementation and platform-specific validation of SIM-compatible RF-triggered coordination mechanisms. Full article

Background: With the development of wireless communication technologies, the rapid advancement of 5G and 6G communication systems has spawned an urgent demand for low latency and high data rates. Orthogonal Frequency Division Multiplexing (OFDM) communication using high-order digital modulation has become a key technology due to its characteristics, such as high reliability, high data rate, and low latency, and has been widely applied in various fields. As a component of cognitive radios, automatic modulation classification (AMC) plays an important role in remote sensing and electromagnetic spectrum sensing. However, under current complex channel conditions, there are issues such as low signal-to-noise ratio (SNR), Doppler frequency shift, and multipath propagation. Methods: Coupled with the inherent problem of indistinct characteristics in high-order modulation, these currently make it difficult for AMC to focus on OFDM and high-order digital modulation. Existing methods are mainly based on a single model-driven approach or data-driven approach. The Adaptive Wavelet Mamba Network (AWMN) proposed in this paper attempts to combine model-driven adaptive wavelet transform feature extraction with the Mamba deep learning architecture. A module based on the lifting wavelet scheme effectively captures discriminative time–frequency features using learnable operations. Meanwhile, a Mamba network constructed based on the State Space Model (SSM) can capture long-term temporal dependencies. This network realizes a combination of model-driven and data-driven methods. Results: Tests conducted on public datasets and a custom-built real-time received OFDM dataset show that the proposed AWMN achieves a performance reaching higher accuracies of 62.39%, 64.50%, and 74.95% on the public Rml2016(a) and Rml2016(b) datasets and our formulated EVAS dataset, while maintaining a compact parameter size of 0.44 M. Conclusions: These results highlight its potential for improving the automatic modulation classification of high-order OFDM modulation in 5G/6G systems. Full article

It has recently been recognized that the ionosphere is highly sensitive to pre-seismic effects, and the detection of ionospheric perturbations associated with earthquakes (EQs) is one of the most promising candidates for short-term EQ prediction. In this review, we focus on a possible use of VLF/LF (very low frequency (3–30 kHz)/low frequency (30–300 kHz)) radio sounding of seismo-ionospheric perturbations to study seismogenic effects. Because an understanding of the early history in any area will provide a lot of crucial insights to the readers (especially to young scientists) working in the field of seismo-electromagnetics, we provide a brief history (mainly results reported by a Russian group of scientists) of the initial application of subionospheric VLF/LF propagation for the study of ionospheric perturbations associated with EQs, and then we present our first convincing evidence on the ionospheric perturbation for the disastrous Kobe EQ in 1995, with a new analysis method based on the shifts in terminator times in VLF/LF diurnal variations (minima in the diurnal variations in amplitude and phase). We then summarize our latest results on further evidence of seismo-ionospheric perturbations. Firstly, we present a few statistical studies on the correlation between VLF/LF propagation anomalies and EQs based on long-term data. Secondly, we showcase studies for a few large, recent EQs (including the 2011 Tohoku EQ). Building on those EQ precursor studies, we demonstrate scientific topics and the underlying physics that can be studied using VLF/LF data, highlighting recent achievements including the revolutionary perspective of lithosphere–atmosphere–ionosphere coupling (LAIC) (or how the ionosphere is perturbed due to the lithospheric pre-EQ activity), modulation in VLF/LF data by atmospheric gravity waves (AGWs), Doppler-shift observation, satellite observation of VLF/LF transmitter signals, etc., together with the recommendation of the application of new technologies such as artificial intelligence and critical analysis to VLF/LF analysis. Finally, we want to emphasize again the essential significance of the information on lower-ionospheric perturbations within LAIC studies. Full article

A homogenisation procedure for energy-buffering structural layers with integrated electrical energy storage systems (capacitors) is described with the aim of calculating their shielding effectiveness to the electromagnetic waves when they are installed inside building walls. In fact, these storage systems may attenuate electromagnetic fields in the frequency ranges employed by mobile telephony, radio broadcasting, and wireless data transmission, thus impairing the operation of Internet of Things infrastructures. The capacitors inside the individual energy-buffering modules have a multilayered structure, in which the layers have very small thicknesses, making an analytical solution of the electromagnetic field for this kind of object practically impossible. Similarly, numerical solutions may not be practical due to the very small thickness of the layers compared to the overall object size. Therefore, this paper presents a simple and effective analytical method to model multilayered structures consisting of homogenising the whole capacitor, which can then be treated as a unique block of material with fictitious (but effective) electric and magnetic parameters. The method is based on multi-section transmission lines, and a quick and reliable analytical methodology is proposed to evaluate the shielding capabilities using the homogenised capacitor’s effective parameters. Moreover, experimental measurements on a real prototype have also been carried out to validate the methodology. Results show that the trend of the simulated and measured SE is the same, proving that the method can be employed to obtain a conservative estimation of the SE from numerical simulations. Full article

In the field of the Internet of Things (IoT), technical solutions that enable information transmission with minimal energy consumption are of particular interest. Common solutions frequently used in the field of radio frequency identification (RFID) involve utilizing electromagnetic waves to power tags and employing backscattering for communication. Detecting the received signal in a coherent manner enables increased reliability in tag reading. This paper proposes a method for coherent signal detection in a bistatic backscatter communication system (BBCS), which includes coarse carrier frequency offset (CFO) from preamble and fine phase correction from data symbols. The proposed method outperforms the detection approach based on maximum likelihood estimation (MLE) of CFO from the preamble, particularly in scenarios with higher CFO values. The proposed detection method is well suited for implementation in software-defined radios, particularly in low-cost devices characterized by less stable oscillators. It is also shown that a preamble of six symbols is sufficient to perform a coarse CFO estimation. Since the analyzed system is equivalent to binary frequency-shift keying (FSK) modulation, the performance of FSK is presented as the theoretical upper bound in the results. Full article

For high-power magnetic resonance imaging (MRI) radio frequency (RF) combiners operating in the frequency range from 60 MHz to 300 MHz, the primary challenges lie in achieving high-power transmission capability while minimizing the insertion loss (IL), reducing the physical dimensions, and meeting application bandwidth requirements. This paper presents a high-performance RF power combiner based on capacitor-loaded microstrip technology for 3.0T MRI radio frequency power amplifier (RFPA) systems. The proposed combiner features low loss, high integration, and miniaturization, and it comprises multiple branches, each employing microstrip lines and capacitors in a series–parallel arrangement to achieve an impedance transformation of 50 Ω to 100 Ω. Each branch was designed through theoretical analysis and electromagnetic simulations to achieve a line length 30% shorter than λ/4, a 6.2 mm line width, and 0.08 dB IL at the 3.0T MRI operation frequency band. A two-way to one-way combiner was further designed using this branch structure to achieve 0.2 dB IL through simulation optimization. A four-way to one-way combiner was then constructed by cascading two-way combiners and optimized via ADS-HFSS software(ADS2014 HFSS19) co-simulation. The fabricated combiner module uses an FR4 substrate and achieves a 0.4 dB insertion loss, −25 dB return loss, and 25 dB port isolation at 128 MHz ± 1 MHz, with compact dimensions (320 × 200 × 10 mm). To ensure high power capability, thermal analysis was performed to confirm that the module’s power-handling capacity exceeded 8 kW, and experimental validation with the 8 kW 3.0T RFPA demonstrated a stable temperature rise of approximately 2 °C. In this study, the innovative single-branch topology and the RF high-power four-to-one combiner for 3.0T MRI systems were used, resolving the trade-offs between power-handling capability, insertion loss, structural compactness, and operating bandwidth in MRI power combiners. The combiner was successfully integrated into the 3.0T MRI RFPA system, reducing the overall dimensions of the RFPA system and simplifying its installation, thereby enabling high-quality imaging validation. This solution demonstrates the scalable potential of the design for other high-field MRI systems operating in the MHz range (from tens to hundreds of MHz), including in 1.5T and 7.0T MRI systems. Full article

The integration of information and communication technologies in the field of healthcare has generated a positive transformation in the traditional way of providing patient care, optimizing medical services, and streamlining healthcare operations. Traditionally, healthcare systems have relied on radio frequency (RF) signals for data transmission. However, the conventional RF wireless network faces ever-increasing challenges, such as spectrum shortage and a congested frequency spectrum. Moreover, issues such as interference, security vulnerabilities, and potential health risks associated with prolonged exposure to RF electromagnetic radiation complicate its application in healthcare environments. To address these challenges, visible light communication (VLC) systems, which offer dual functionalities, data transmission, and illumination, have emerged as a promising complementary solution to traditional RF-based options. VLC provides secure, high-speed data communication that is immune to RF interference, making it particularly suitable for healthcare settings. This research examines the advancements in e-health systems that utilize VLC technology, considering various modulation and channel coding techniques, with a focus on evaluating the effectiveness and limitations of these techniques to determine their impact on overall performance. Full article

The Spaceborne Global Lightning Location Network (SGLLN) serves the purpose of identifying transient lightning events occurring beneath the ionosphere, playing a significant role in detecting and warning of disaster weather events. To ensure the effective functioning of the wideband electromagnetic pulse detector, which is a crucial component of the SGLLN, it must be tested and verified with specific signals. However, the inherent randomness and unpredictability of lightning occurrences pose challenges to this requirement. Consequently, a high-power electromagnetic pulse radiation system with a 20 m aperture reflector is designed. This system is capable of emitting nanosecond electromagnetic pulse signals under pre-set spatial and temporal conditions, providing a controlled environment for assessing the detection capabilities of SGLLN. In the design phase, an exponentially TEM feed antenna has been designed firstly based on the principle of high-gain radiation. The feed antenna adopts a pulser-integrated design to mitigate insulation risks, and it is equipped with an asymmetric protective loading to reduce reflected energy by 85.7%. Moreover, an innovative assessment method for gain loss, based on the principle of Love’s equivalence, is proposed to quantify the impact of feed antenna on the radiation field. During the experimental phase, a specialized E-field sensor is used in the far-field experiment at a distance of 400 m. The measurements indicate that at this distance, the signal has a peak field strength of 2.2 kV/m, a rise time of 1.9 ns, and a pulse half-width of 2.5 ns. Additionally, the beamwidth in the time domain is less than 10°. At an altitude of 500 km, the spaceborne detector records a signal with a peak field strength of approximately 10 mV/m. Particularly, this signal transformed into a nonlinear frequency-modulated signal in the microsecond range across its frequency spectrum, which is consistent with the law of radio wave propagation in the ionosphere. This study offers a stable and robust radiation source for verifying spaceborne detectors and establishes an empirical foundation for investigating the impact of the ionosphere on signal propagation characteristics. Full article

The radio spectrum is a scarce and extremely valuable resource that demands careful real-time monitoring and dynamic resource allocation. Dynamic spectrum access (DSA) is a new paradigm for managing the radio spectrum, which requires AI/ML-driven algorithms for optimum performance under rapidly changing channel conditions and possible cyber-attacks in the electromagnetic domain. Fast sensing across multiple directions using array processors, with subsequent AI/ML-based algorithms for the sensing and perception of waveforms that are measured from the environment is critical for providing decision support in DSA. As part of directional and wideband spectrum perception, the ability to finely channelize wideband inputs using efficient Fourier analysis is much needed. However, a fine-grain fast Fourier transform (FFT) across a large number of directions is computationally intensive and leads to a high chip area and power consumption. We address this issue by exploiting the recently proposed approximate discrete Fourier transform (ADFT), which has its own sparse factorization for real-time implementation at a low complexity and power consumption. The ADFT is used to create a wideband multibeam RF digital beamformer and temporal spectrum-based attention unit that monitors 32 discrete directions across 32 sub-bands in real-time using a multiplierless algorithm with low computational complexity. The output of this spectral attention unit is applied as a decision variable to an intelligent receiver that adapts its center frequency and frequency resolution via FFT channelizers that are custom-built for real-time monitoring at high resolution. This two-step process allows the fine-gain FFT to be applied only to directions and bands of interest as determined by the ADFT-based low-complexity 2D spacetime attention unit. The fine-grain FFT provides a spectral signature that can find future use cases in neural network engines for achieving modulation recognition, IoT device identification, and RFI identification. Beamforming and spectral channelization algorithms, a digital computer architecture, and early prototypes using a 32-element fully digital multichannel receiver and field programmable gate array (FPGA)-based high-speed software-defined radio (SDR) are presented. Full article

The processing of dielectric materials in the radio frequency field continues to be a concern in engineering. This procedure involves a rigorous analysis of the electromagnetic field based on specific numerical methods. This paper presents an original method for analysing the process of drying wooden boards in a radio frequency (RF) installation. The electromagnetic field and thermal field are calculated using the finite element method (FEM). The load capacity of the installation is also calculated, since the material being heated in the radio frequency heating installations is placed in a capacitor-type applicator. A specific method is created in order to solve the problem related to mass, a quantity which tends to change during the drying of the dielectric. In addition, special consideration is given to issues regarding the coupling of the electromagnetic field and the thermal field, along with aspects pertaining to mass. These are implemented numerically using a program written in the Fortran language, which takes the distribution of finite elements from the Flux2D program, the dielectric thermal module, intended only for the study of RF heating. The results obtained after running the program are satisfactory and they represent a support for future studies, especially if the movement of the dielectric is taken into account. Full article

Modern wearable devices show promising results in terms of detecting vital bodily signs from the wrist. However, there remains a considerable need for a device that can conform to the human body’s variable geometry to accurately detect those vital signs and to understand health better. Flexible radio frequency (RF) resonators are well poised to address this need by providing conformable bio-interfaces suitable for different anatomical locations. In this work, we develop a compact wearable RF biosensor that detects multisite hemodynamic events due to pulsatile blood flow through noninvasive tissue–electromagnetic (EM) field interaction. The sensor consists of a skin patch spiral resonator and a wearable transceiver. During resonance, the resonator establishes a strong capacitive coupling with layered dielectric tissues due to impedance matching. Therefore, any variation in the dielectric properties within the near-field of the coupled system will result in field perturbation. This perturbation also results in RF carrier modulation, transduced via a demodulator in the transceiver unit. The main elements of the transceiver consist of a direct digital synthesizer for RF carrier generation and a demodulator unit comprised of a resistive bridge coupled with an envelope detector, a filter, and an amplifier. In this work, we build and study the sensor at the radial artery, thorax, carotid artery, and supraorbital locations of a healthy human subject, which hold clinical significance in evaluating cardiovascular health. The carrier frequency is tuned at the resonance of the spiral resonator, which is 34.5 ± 1.5 MHz. The resulting transient waveforms from the demodulator indicate the presence of hemodynamic events, i.e., systolic upstroke, systolic peak, dicrotic notch, and diastolic downstroke. The preliminary results also confirm the sensor’s ability to detect multisite blood flow events noninvasively on a single wearable platform. Full article

Chronic studies in the fasting and fed states of conscious subjects are fundamental for understanding the pathophysiological significance of functional gastrointestinal (GI) disorders and motility dysfunctions. To study the electrophysiology of the GI tract in the long term, the development of gastric implants is essential. This paper presents the development of an implantable system capable of monitoring the bioelectrical activity of the gastric system and modulating the activity in freely behaving rodents. The system consists of a miniature-sized implantable unit (IU), a stationary unit (SU) that communicates with the IU over a 2.4 GHz far-field radio frequency (RF) bidirectional link, and a charging unit (CU) that establishes an inductive 13.56 MHz near-field communication (NFC) with the IU, implementing an adaptive wireless power transfer (WPT). The CU can generate an adjustable power between +20 dBm and +30 dBm, and, in the presence of body movements and stomach motility, can deliver a constant rectified voltage to the IU. The live subject’s exposure to the electromagnetic WPT in the developed system complies with the RF energy absorption restrictions for health and safety concerns. The system can be utilized to investigate the relationship between functional GI disorders and dysrhythmias in the gastric bioelectrical activity and study the potential of electroceutical therapies for motility dysfunctions in clinical settings. Full article

Modulation recognition is the indispensable part of signal interception analysis, which has always been the research hotspot in the field of radio communication. With the increasing complexity of the electromagnetic spectrum environment, interference in signal propagation becomes more and more serious. This paper proposes a modulation recognition scheme based on multimodal feature fusion, which attempts to improve the performance of modulation recognition under different channels. Firstly, different time- and frequency-domain features are extracted as the network input in the signal preprocessing stage. The residual shrinkage building unit with channel-wise thresholds (RSBU-CW) was used to construct deep convolutional neural networks to extract spatial features, which interact with time features extracted by LSTM in pairs to increase the diversity of the features. Finally, the PNN model was adapted to make the features extracted from the network cross-fused to enhance the complementarity between features. The simulation results indicated that the proposed scheme has better recognition performance than the existing feature fusion schemes, and it can also achieve good recognition performance in multipath fading channels. The test results of the public dataset, RadioML2018.01A, showed that recognition accuracy exceeds 95% when the signal-to-noise ratio (SNR) reaches 8dB. Full article