Dielectric Properties of Materials Used for Microwave-Based NOx Gas Dosimeters.

Nitrogen oxides (NOx), primarily generated from combustion processes, pose significant health and environmental risks. To improve the coordination of measures against excessive NOx emissions, it is necessary to effectively monitor ambient NOx concentrations, which requires the development of precise and cost-efficient detection methods. This study focuses on developing a microwave- or radio frequency (RF)-based gas dosimeter for NOx detection and addresses the optimization of the dosimeter design by examining the dielectric properties of LTCC-based (Low-Temperature Co-fired Ceramics) sensor substrates and barium-based NOx storage materials. The measurements taken utilizing the Microwave Cavity Perturbation (MCP) method revealed that these materials exhibit more pronounced changes in dielectric losses when storing NOx at elevated temperatures. Consequently, operating such a dosimeter at high temperatures (above 300 °C) is recommended to maximize the sensor signal. To evaluate their high-temperature applicability, LTCC substrates were analyzed by measuring their dielectric losses at temperatures up to 600 °C. In terms of NOx storage materials, coating barium on high-surface-area alumina resolved issues related to limited NOx adsorption in pure barium carbonate powders. Additionally, the adsorption of both NO and NO2 was enabled by the application of a platinum catalyst. The change in dielectric losses, which provides the main signal for an RF-based gas dosimeter, only depends on the stored amount of NOx and not on the specific type of nitrogen oxide. Although the change in dielectric losses increases with the temperature, the maximum storage capacity of the material decreases significantly. In addition, at temperatures above 350 °C, NOx is mostly weakly bound, so it will desorb in the absence of NOx. Therefore, in the future development of a reliable RF-based NOx dosimeter, the trade-off between the sensor signal strength and adsorption behavior must be addressed.

Modulated Radio Frequency Stealth Waveforms for Ultra-Wideband Radio Fuzes.

The increasingly complex electromagnetic environment of modern warfare and the proliferation of intelligent jamming threaten to reduce the survival rate of radio fuzes on the battlefield. Radio frequency (RF) stealth technology can fundamentally improve the anti-interception and reconnaissance capabilities of radio fuzes, thereby lessening the probability of them being intercepted, recognized, and jammed by the enemy. In this paper, an RF stealth waveform based on chaotic pulse-position modulation is proposed for ultra-wideband (UWB) radio fuzes. Adding a perturbation signal based on the Tent map ensures that the chaotic sequences have sufficiently long periods despite hardware byte limitations. Measuring the approximate entropy and sequence period shows that the Tent map with the addition of perturbation signals can maintain good randomness under byte constraints, closely approximating the Tent map with ideal precision. Simulations verify that the proposed chaotic mapping used to modulate the pulse position of an ultra-wideband radio fuze signal results in superior detection, anti-interception, and anti-jamming performance.

Frontiers in the Application of RF Vacuum Electronics.

The application of radio frequency (RF) vacuum electronics for the betterment of the human condition began soon after the invention of the first vacuum tubes in the 1920s and has not stopped since. Today, microwave vacuum devices are powering important applications in health treatment, material and biological science, wireless communication-terrestrial and space, Earth environment remote sensing, and the promise of safe, reliable, and inexhaustible energy. This article highlights some of the exciting application frontiers of vacuum electronics.

Design and Analysis of a Fluid-Filled RF MEMS Switch.

In the present study, a fluid-filled RF MEMS (Radio Frequency Micro-Electro-Mechanical Systems) switch is proposed and designed. In the analysis of the operating principle of the proposed switch, air, water, glycerol and silicone oil were adopted as filling dielectric to simulate and research the influence of the insulating liquid on the drive voltage, impact velocity, response time, and switching capacity of the RF MEMS switch. The results show that by filling the switch with insulating liquid, the driving voltage can be effectively reduced, while the impact velocity of the upper plate to the lower plate is also reduced. The high dielectric constant of the filling medium leads to a lower switching capacitance ratio, which affects the performance of the switch to some extent. By comparing the threshold voltage, impact velocity, capacitance ratio, and insertion loss of the switch filled with different media with the filling media of air, water, glycerol, and silicone oil, silicone oil was finally selected as the liquid filling medium for the switch. The results show that the threshold voltage is 26.55 V after filling with silicone oil, which is 43% lower under the same air-encapsulated switching conditions. When the trigger voltage is 30.02 V, the response time is 10.12 µs and the impact speed is only 0.35 m/s. The frequency 0-20 GHz switch works well, and the insertion loss is 0.84 dB. To a certain extent, it provides a reference value for the fabrication of RF MEMS switches.

A Review of Hybrid VLC/RF Networks: Features, Applications, and Future Directions.

The expectation for communication systems beyond 5G/6G is to provide high reliability, high throughput, low latency, and high energy efficiency services. The integration between systems based on radio frequency (RF) and visible light communication (VLC) promises the design of hybrid systems capable of addressing and largely satisfying these requirements. Hybrid network design enables complementary cooperation without interference between the two technologies, thereby increasing the overall system data rate, improving load balancing, and reducing non-coverage areas. VLC/RF hybrid networks can offer reliable and efficient communication solutions for Internet of Things (IoT) applications such as smart lighting, location-based services, home automation, smart healthcare, and industrial IoT. Therefore, hybrid VLC/RF networks are key technologies for next-generation communication systems. In this paper, a comprehensive state-of-the-art study of hybrid VLC/RF networks is carried out, divided into four areas. First, indoor scenarios are studied considering lighting requirements, hybrid channel models, load balancing, resource allocation, and hybrid network topologies. Second, the characteristics and implementation of these hybrid networks in outdoor scenarios with adverse conditions are analyzed. Third, we address the main applications of hybrid VLC/RF networks in technological, economic, and socio-environmental domains. Finally, we outline the main challenges and future research lines of hybrid VLC/RF networks.

Soot Monitoring of Gasoline Particulate Filters Using a Radio-Frequency-Based Sensor.

Owing to increasingly stringent emission limits, particulate filters have become mandatory for gasoline-engine vehicles. Monitoring their soot loading is necessary for error-free operation. The state-of-the-art differential pressure sensors suffer from inaccuracies due to small amounts of stored soot combined with exhaust gas conditions that lead to partial regeneration. As an alternative approach, radio-frequency-based (RF) sensors can accurately measure the soot loading, even under these conditions, by detecting soot through its dielectric properties. However, they face a different challenge as their sensitivity may depend on the engine operation conditions during soot formation. In this article, this influence is evaluated in more detail. Various soot samples were generated on an engine test bench. Their dielectric properties were measured using the microwave cavity perturbation (MCP) method and compared with the corresponding sensitivity of the RF sensor determined on a lab test bench. Both showed similar behavior. The values for the soot samples themselves, however, differed significantly from each other. A way to correct for this cross-sensitivity was found in the influence of exhaust gas humidity on the RF sensor, which can be correlated with the engine load. By evaluating this influence during significant humidity changes, such as fuel cuts, it could be used to correct the influence of the engineon the RF sensor.

Modelling, Validation and Experimental Analysis of Diverse RF-MEMS Ohmic Switch Designs in View of Beyond-5G, 6G and Future Networks-Part 1.

The emerging paradigms of Beyond-5G (B5G), 6G and Future Networks (FN), will capsize the current design strategies, leveraging new technologies and unprecedented solutions. Focusing on the telecom segment and on low-complexity Hardware (HW) components, this contribution identifies RF-MEMS, i.e., Radio Frequency (RF) passives in Microsystem (MEMS) technology, as a key-enabler of 6G/FN. This work introduces four design concepts of RF-MEMS series ohmic switches realized in a surface micromachining process. S-parameters (Scattering parameters) are measured and simulated with a Finite Element Method (FEM) tool, in the frequency range from 100 MHz to 110 GHz. Based on such a set of data, three main aspects are covered. First, validation of the FEM-based modelling methodology is carried out. Then, pros and cons in terms of RF characteristics for each design concept are identified and discussed, in view of B5G, 6G and FN applications. Moreover, ad hoc metrics are introduced to better quantify the S-parameters predictive errors of simulated vs. measured data. In particular, the latter items will be further exploited in the second part of this work (to be submitted later), in which a discussion around compact modelling techniques applied to RF-MEMS switching concepts will also be included.

Advances and Challenges in Drone Detection and Classification Techniques: A State-of-the-Art Review.

The fast development of unmanned aerial vehicles (UAVs), commonly known as drones, has brought a unique set of opportunities and challenges to both the civilian and military sectors. While drones have proven useful in sectors such as delivery, agriculture, and surveillance, their potential for abuse in illegal airspace invasions, privacy breaches, and security risks has increased the demand for improved detection and classification systems. This state-of-the-art review presents a detailed overview of current improvements in drone detection and classification techniques: highlighting novel strategies used to address the rising concerns about UAV activities. We investigate the threats and challenges faced due to drones' dynamic behavior, size and speed diversity, battery life, etc. Furthermore, we categorize the key detection modalities, including radar, radio frequency (RF), acoustic, and vision-based approaches, and examine their distinct advantages and limitations. The research also discusses the importance of sensor fusion methods and other detection approaches, including wireless fidelity (Wi-Fi), cellular, and Internet of Things (IoT) networks, for improving the accuracy and efficiency of UAV detection and identification.

Expression and Activity of the Transcription Factor CCAAT/Enhancer-Binding Protein ß (C/EBPß) Is Regulated by Specific Pulse-Modulated Radio Frequencies in Oligodendroglial Cells.

The rapid growth of wireless electronic devices has raised concerns about the harmful effects of leaked electromagnetic radiation (EMR) on human health. Even though numerous studies have been carried out to explore the biological effects of EMR, no clear conclusions have been drawn about the effect of radio frequency (RF) EMR on oligodendrocytes. To this end, we exposed oligodendroglia and three other types of brain cells to 2.4 GHz EMR for 6 or 48 h at an average input power of 1 W in either a continuous wave (CW-RF) or a pulse-modulated wave (PW-RF, 50 Hz pulse frequency, 1/3 duty cycle) pattern. RNA sequencing, RT-qPCR, and Western blot were used to examine the expression of C/EBPß and its related genes. Multiple reaction monitoring (MRM) was used to examine the levels of expression of C/EBPß-interacting proteins. Our results showed that PW-RF EMR significantly increased the mRNA level of C/EBPß in oligodendroglia but not in other types of cells. In addition, the expression of three isoforms and several interacting proteins and targeted genes of C/EBPß were markedly changed after 6-h PW-RF but not CW-RF. Our results indicated that RF EMR regulated the expression and functions of C/EBPß in a waveform- and cell-type-dependent manner.

Mixing Rules for an Exact Determination of the Dielectric Properties of Engine Soot Using the Microwave Cavity Perturbation Method and Its Application in Gasoline Particulate Filters.

In recent years, particulate filters have become mandatory in almost all gasoline-powered vehicles to comply with emission standards regarding particulate number. In contrast to diesel applications, monitoring gasoline particulate filters (GPFs) by differential pressure sensors is challenging due to lower soot masses to be deposited in the GPFs. A different approach to determine the soot loading of GPFs is a radio frequency-based sensor (RF sensor). To facilitate sensor development, in previous work, a simulation model was created to determine the RF signal at arbitrary engine operating points. To ensure accuracy, the exact dielectric properties of the soot need to be known. This work has shown how small samples of soot-loaded filter are sufficient to determine the dielectric properties of soot itself using the microwave cavity perturbation method. For this purpose, mixing rules were determined through simulation and measurement, allowing the air and substrate fraction of the sample to be considered. Due to the different geometry of filter substrates compared to crushed soot samples, a different mixing rule had to be derived to calculate the effective filter properties required for the simulation model. The accuracy of the determined mixing rules and the underlying simulation model could be verified by comparative measurements on an engine test bench.

The New Era of Long-Range "Zero-Interception" Ambient Backscattering Systems: 130 m with 130 nA Front-End Consumption.

Internet of Things applications based on backscatter radio principles have appeared to address the limitations of high cost and high power consumption. While radio-frequency identification (RFID) sensor nodes are among the most commonly utilized state-of-the-art technologies, their range for passive implementations is typically short and well below 10 m being impractical for "rugged" applications where approaching the tag at such proximity, is not convenient or safe. In this work, we propose a long-range "zero interception" ambient backscatter (LoRAB) communication system relying on low power sensor (tag) deployments. Without employing a dedicated radio transmission, our technology enables the "zero interception" communication of the tags with portable receivers over hundreds of meters. This enables low-cost and low-power communications across a wide range of missions by using chirp spread spectrum (CSS) modulation on ambient FM signals. A laboratory prototype exploiting commercial components (laptops, DAQ, software-defined radios (SDR) platform) have demonstrated the potential by achieving 130 m tag-to-reader distance for a low bit rate of 88 bps with the modulator current consumption at around 103 nA.

A Survey of Hybrid Free Space Optics (FSO) Communication Networks to Achieve 5G Connectivity for Backhauling.

Increased capacity, higher data rate, decreased latency, and better service quality are examples of the primary objectives or needs that must be catered to in the near future, i.e., fifth-generation (5G) and beyond. To fulfil these needs, cellular network design must be drastically improved. The 5G cellular network design, huge multiple-input multiple-output (MIMO) technology, and device-to-device communication are all highlighted in this comprehensive study. Hence, free-space optics (FSO) is a promising solution to address this field. However, FSO standalone is insufficient during turbulent weather conditions. FSO systems possess some limitations, such as being able to be disturbed by any interference between sender and receiver such as a flying bird and a tree, as it requires line-of-sight (LOS) connectivity. Moreover, it is sensitive to weather conditions; the FSO performance significantly decreases in bad weather conditions such as fog and snow; those factors deteriorate the performance of FSO. This paper conducts a systematic survey on the existing projects in the same area of research such as the hybrid FSO/Radio frequency (RF) communication system by listing each technique used for each model to achieve optimum performance in terms of data rate and Bit Error Rate (BER) to be implemented in 5G networks.

Modelling the Influence of Different Soot Types on the Radio-Frequency-Based Load Detection of Gasoline Particulate Filters.

Gasoline particulate filters (GPFs) are an appropriate means to meet today's emission standards. As for diesel applications, GPFs can be monitored via differential pressure sensors or using a radio-frequency approach (RF sensor). Due to largely differing soot properties and engine operating modes of gasoline compared to diesel engines (e.g., the possibility of incomplete regenerations), the behavior of both sensor systems must be investigated in detail. For this purpose, extensive measurements on engine test benches are usually required. To simplify the sensor development, a simulation model was developed using COMSOL Multiphysics® that not only allowed for calculating the loading and regeneration process of GPFs under different engine operating conditions but also determined the impact on both sensor systems. To simulate the regeneration behavior of gasoline soot accurately, an oxidation model was developed. To identify the influence of different engine operating points on the sensor behavior, various samples generated at an engine test bench were examined regarding their kinetic parameters using thermogravimetric analysis. Thus, this compared the accuracy of soot mass determination using the RF sensor with the differential pressure method. By simulating a typical driving condition with incomplete regenerations, the effects of the soot kinetics on sensor accuracy was demonstrated exemplarily. Thereby, the RF sensor showed an overall smaller mass determination error, as well as a lower dependence on the soot kinetics.

A Sensor Fusion Based Nonholonomic Wheeled Mobile Robot for Tracking Control.

In this paper, a detail design procedure of the real-time trajectory tracking for the nonholonomic wheeled mobile robot (NWMR) is proposed. A 9-axis micro electro-mechanical systems (MEMS) inertial measurement unit (IMU) sensor is used to measure the posture of the NWMR, the position information of NWMR and the hand-held device are acquired by global positioning system (GPS) and then transmit via radio frequency (RF) module. In addition, in order to avoid the gimbal lock produced by the posture computation from Euler angles, the quaternion is utilized to compute the posture of the NWMR. Furthermore, the Kalman filter is used to filter out the readout noise of the GPS and calculate the position of NWMR and then track the object. The simulation results show the posture error between the NWMR and the hand-held device can converge to zero after 3.928 seconds for the dynamic tracking. Lastly, the experimental results show the validation and feasibility of the proposed results.

Health Care Monitoring and Treatment for Coronary Artery Diseases: Challenges and Issues.

In-stent restenosis concerning the coronary artery refers to the blood clotting-caused re-narrowing of the blocked section of the artery, which is opened using a stent. The failure rate for stents is in the range of 10% to 15%, where they do not remain open, thereby leading to about 40% of the patients with stent implantations requiring repeat procedure within one year, despite increased risk factors and the administration of expensive medicines. Hence, today stent restenosis is a significant cause of deaths globally. Monitoring and treatment matter a lot when it comes to early diagnosis and treatment. A review of the present stent monitoring technology as well as the practical treatment for addressing stent restenosis was conducted. The problems and challenges associated with current stent monitoring technology were illustrated, along with its typical applications. Brief suggestions were given and the progress of stent implants was discussed. It was revealed that prime requisites are needed to achieve good quality implanted stent devices in terms of their size, reliability, etc. This review would positively prompt researchers to augment their efforts towards the expansion of healthcare systems. Lastly, the challenges and concerns associated with nurturing a healthcare system were deliberated with meaningful evaluations.

Development and evaluation of a 16-channel receive-only RF coil to improve 7T ultra-high field body MRI with focus on the spine.

PURPOSE: A 16-channel receive (16Rx) radiofrequency (RF) array for 7T ultra-high field body MR imaging is presented. The coil is evaluated in conjunction with a 16-channel transmit/receive (16TxRx) coil and additionally with a 32-channel transmit/receive (32TxRx) remote body coil for RF transmit and serving as receive references. METHODS: The 16Rx array consists of 16 octagonal overlapping loops connected to custom-built detuning boards with preamplifiers. Performance metrics like noise correlation, g-factors, and signal-to-noise ratio gain were compared between 4 different RF coil configurations. In vivo body imaging was performed in volunteers using radiofrequency shimming, time interleaved acquisition of modes (TIAMO), and 2D spatially selective excitation using parallel transmit (pTx) in the spine. RESULTS: Lower g-factors were obtained when using the 16Rx coil in addition to the 16TxRx array coil configuration versus the 16TxRx array alone. Distinct signal-to-noise ratio gain using the 16Rx coil could be demonstrated in the spine region both for a comparison with the 16TxRx coil (>50% gain) in vivo and the 32TxRx coil (>240% gain) in a phantom. The 16Rx coil was successfully applied to improve anatomical imaging in the abdomen and 2D spatially selective excitation in the spine of volunteers. CONCLUSION: The novel 16-channel Rx-array as an add-on to multichannel TxRx RF coil configurations provides increased signal-to-noise ratio, lower g-factors, and thus improves 7T ultra-high field body MR imaging.

Post-processing radio-frequency signal based on deep learning method for ultrasonic microbubble imaging.

BACKGROUND: Improving imaging quality is a fundamental problem in ultrasound contrast agent imaging (UCAI) research. Plane wave imaging (PWI) has been deemed as a potential method for UCAI due to its' high frame rate and low mechanical index. High frame rate can improve the temporal resolution of UCAI. Meanwhile, low mechanical index is essential to UCAI since microbubbles can be easily broken under high mechanical index conditions. However, the clinical practice of ultrasound contrast agent plane wave imaging (UCPWI) is still limited by poor imaging quality for lack of transmit focus. The purpose of this study was to propose and validate a new post-processing method that combined with deep learning to improve the imaging quality of UCPWI. The proposed method consists of three stages: (1) first, a deep learning approach based on U-net was trained to differentiate the microbubble and tissue radio frequency (RF) signals; (2) then, to eliminate the remaining tissue RF signals, the bubble approximated wavelet transform (BAWT) combined with maximum eigenvalue threshold was employed. BAWT can enhance the UCA area brightness, and eigenvalue threshold can be set to eliminate the interference areas due to the large difference of maximum eigenvalue between UCA and tissue areas; (3) finally, the accurate microbubble imaging were obtained through eigenspace-based minimum variance (ESBMV). RESULTS: The proposed method was validated by both phantom and in vivo rabbit experiment results. Compared with UCPWI based on delay and sum (DAS), the imaging contrast-to-tissue ratio (CTR) and contrast-to-noise ratio (CNR) was improved by 21.3 dB and 10.4 dB in the phantom experiment, and the corresponding improvements were 22.3 dB and 42.8 dB in the rabbit experiment. CONCLUSIONS: Our method illustrates superior imaging performance and high reproducibility, and thus is promising in improving the contrast image quality and the clinical value of UCPWI.

Towards a System for Tracking Drug Delivery Using Frequency Excited Gold Nanoparticles.

Nanoparticle-based drugs are rapidly evolving to treat different conditions and have considerable potential. A new system based on the combination of electrical impedance tomography (EIT) imaging and a power amplifier with a RF coil has been developed to study the effect of gold nanoparticles (AuNPs) when excited in the MHz frequency range. We show that samples including AuNPs have a temperature increase of 1-1.5 °C due to the presence of RF excitation at 13.56 MHz which provides a higher rate of change for solutions without AuNPs. They also show more than a 50% increase in conductivity in difference imaging as the result of this excitation. The change for samples without AuNPs is 40%.

An Improved Unauthorized Unmanned Aerial Vehicle Detection Algorithm Using Radiofrequency-Based Statistical Fingerprint Analysis.

Unmanned aerial vehicles (UAVs) are now readily available worldwide and users can easily fly them remotely using smart controllers. This has created the problem of keeping unauthorized UAVs away from private or sensitive areas where they can be a personal or public threat. This paper proposes an improved radio frequency (RF)-based method to detect UAVs. The clutter (interference) is eliminated using a background filtering method. Then singular value decomposition (SVD) and average filtering are used to reduce the noise and improve the signal to noise ratio (SNR). Spectrum accumulation (SA) and statistical fingerprint analysis (SFA) are employed to provide two frequency estimates. These estimates are used to determine if a UAV is present in the detection environment. The data size is reduced using a region of interest (ROI), and this improves the system efficiency and improves azimuth estimation accuracy. Detection results are obtained using real UAV RF signals obtained experimentally which show that the proposed method is more effective than other well-known detection algorithms. The recognition rate with this method is close to 100% within a distance of 2.4 km and greater than 90% within a distance of 3 km. Further, multiple UAVs can be detected accurately using the proposed method.

Design and Implementation of Low Power High-Efficient Transceiver for Body Channel Communications.

Body channel communications (BCC) have been researched while an allowing technology to improve necessities for the low power and high reconfiguration power in wireless telemetry systems used at wireless communication purpose. Conventional features on BCC are concentrated mostly on modeling of channels by using of an efficient measurement technique, wireless transceiver design and then by means of a transmission technique. Particularly, the wireless digital transmitting, developed as a personalized method intended for the body channel, offers wanted to develop flexible and low power BCC systems. With the developing level of wearable communication protocol and applications, there may be an increasingly reliable on an adaptable BCC transmitter that helps both data reconfigure power and power reduction condition. In this paper, an extremely reconfigurable Hamming Encoding Digital Transmitter (HEDT) which works with both reconfigurable data and power reduction condition that supports from two innovative operation conditions is suggested. In a HEDT device, the overall data rate is controlled by the level of Hamming codes designed to make use of in the perfect BCC band of 20-100 MHz. The proposed Hamming Encoded Transmission method achieves seven times improved data rate when compared with conventional BCC processors. The next unique implementation technique is based on the usage of Frequency Shift Keying (FSK) of a Hamming encoded HEDT approach. This approach permits the BCC transceiver to use the perfect channel with bandwidth among 40-100 MHz. Thereby half the clock rate reduces 40% of overall power utilization. The HEDT system is completely designed in a 65 nm CMOS procedure. It uses a primary area of 0.14 × 0.2 mm. When functioning below a data-rate of 60 Mb/s (low power) condition, the BCC transmitter utilizes only 1.00 mW.