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Developers of electronics for the Internet of Things are considering nonstandard substrate materials like recyclable, low-cost, and eco-friendly cardboard paper. From this perspective, this article reviews the design and experimental results of a 2D-rectenna for scavenging radio-frequency energy at 2.45 GHz on various cardboard paper substrates for both the antenna and rectifier. Four types of recycled cardboard material, each with different thicknesses, air gaps, and surface roughness, are selected for characterization. A linearly polarized rectangular microstrip patch antenna with microstrip transmission feeding is adopted for ease of fabrication. At 2.45 GHz, the antenna has a simulated and measured global gain of 2.98 dB and 2.53 dB, respectively, on a 2.2 mm thick cardboard material. The rectifying element consists of a voltage-doubler configuration connected through a T-matching network to the antenna. At low RF input power (−10 dBm), the maximum available DC output power is experimentally evaluated at 1.73 μW, 7.5 μW, and 8.5 μW for HSMS-2860, HSMS-2850, and SMS7306-079L diodes, respectively. The respective rectifiers with diodes SMS7306-079L, HSMS-2850, and HSMS-2860 exhibit optimal load values of 2 kΩ, 2.6 kΩ, and 8 kΩ. The rectifier designed using the SMS7306-079L diode experimentally reaches a maximum power conversion efficiency (PCE) of 14.2% at −5 dBm input power when the optimal load value is 1.5 kΩ. [ABSTRACT FROM AUTHOR]

The compact model plays a pivotal role as a critical link between device fabrication and circuit design. While conventional compact model theories and techniques are generally mature, the intricate physical mechanisms of gallium nitride (GaN) high‐electron mobility transistors (HEMTs) pose challenges due to their strong non‐linearity in high‐power radio frequency (RF) applications. This complexity hinders achieving the required precision for applications using traditional modeling methods. Therefore, the development of physics‐based compact modeling techniques becomes crucial for a deeper understanding of the intricate features of GaN HEMTs. This paper explores the advancements and the current state‐of‐the‐art in physics‐based compact models. The comprehensive review covers both intrinsic core models and real‐device effects models. Core models are presented with a focus on fundamental concepts, development overviews, and applications. Additionally, the real‐device effects models are introduced, encompassing advanced characterization techniques and modeling methodologies. Furthermore, the paper outlines future trends in physics‐based compact modeling, providing valuable insights for individuals engaged in transistor compact modeling work. [ABSTRACT FROM AUTHOR]

In this paper, a sandwich structure metamaterial was designed, in which the substrate is radio frequency (RF) F4B, and the metal pattern of copper is prepared by the substrate on both sides. Analyzed the transmission of the structure, and the quad-band and reciprocal electromagnetically induced transparency (EIT)-like phenomena of the structure were obtained. The physical mechanism of the EIT-like phenomenon was explained by the electric field distribution. Discussing the size of the structure, the influence of structure parameters on EIT-like phenomena was further illustrated. By comparing the measured results with the calculated results in a microwave anechoic chamber, the results are in good agreement. This structure has potential applications in multi-band filtering, sensing, and other fields. [ABSTRACT FROM AUTHOR]

This paper investigates the effect of volume traps intentionally introduced into a silicon-on-insulator (SOI) substrate by inserting a layer of polysilicon beneath buried oxide. In radio frequency applications, this type of substrate, referred to as trap-rich, is known to considerably reduce the generation of harmonics resulting from the parasitic non-linear charge dynamics introduced by the substrate handler under the buried oxide. This analysis focuses on a test vehicle in the form of an integrated coplanar waveguide on two types of substrates, namely, high-resistivity SOI substrates with and without a trap-rich layer. From a modeling point of view, a simulation methodology is implemented in order to convert the 3D simulation of the coplanar waveguide into a 2D treatment that takes into account the wave propagation effect associated with the distributed nature of the transmission line. As a first step, this modeling strategy is implemented to reproduce the effect of increasing substrate resistivity on 2nd and 3rd harmonic reductions, leading to an excellent agreement with experimental data. Building on this validation of the simulation method, we have opted to simulate the non-linear response of the transmission line on the SOI trap-rich substrate by simplifying the trap distribution model. To avoid the adoption of unverified and strongly process-dependent trap distributions across the bandgap, a midgap monovalent trap density has been introduced, either acceptor or donor density. A monovalent density of acceptor traps with a concentration of 1016 cm−3 and a carrier lifetime of 0.1 ns has been shown to reproduce the experimental data very accurately with a substantial reduction in 2nd and 3rd harmonics. A detailed analysis of the displacement current waveforms explains the beneficial role of acceptor traps compared with donor traps. [ABSTRACT FROM AUTHOR]

Radio Frequency Fingerprinting (RFF) refers to the technique for identifying and classifying wireless devices on the basis of their physical characteristics, which appear in the digital signal transmitted in space. Small differences in the radio frequency front-end of the wireless devices are generated across the same wireless device model during the implementation and manufacturing process. These differences create small variations in the transmitted signal, even if the wireless device is still compliant with the wireless standard. By using data analysis and machine-learning algorithms, it is possible to classify different electronic devices on the basis of these variations. This technique has been well proven in the literature, but research is continuing to improve the classification performance, robustness to noise, and computing efficiency. Recently, Deep Learning (DL) has been applied to RFF with considerable success. In particular, the combination of time-frequency representations and Convolutional Neural Networks (CNN) has been particularly effective, but this comes at a great computational cost because of the size of the time-frequency representation and the computing time of CNN. This problem is particularly challenging for wireless standards, where the data to be analyzed is extensive (e.g., long preambles) as in the case of the LoRa (Long Range) wireless standard. This paper proposes a novel approach where two pre-processing steps are adopted to (1) improve the classification performance and (2) to decrease the computing time. The steps are based on the application of Variational Mode Decomposition (VMD) where (in opposition to the known literature) the residual of the VMD application is used instead of the extracted modes. The concept is to remove the modes, which are common among the LoRa devices, and keep with the residuals the unique intrinsic features, which are related to the fingerprints. Then, the spectrogram is applied to the residual component. Even after this step, the computing complexity of applying CNN to the spectrogram is high. This paper proposes a novel step where only segments of the spectrogram are used as input to CNN. The segments are selected using a machine-learning approach applied to the features extracted from the spectrogram using the Local Binary Pattern (LBP). The approach is applied to a recent LoRa radio frequency fingerprinting public data set, where it is shown to significantly outperform the baseline approach based on the full use of the spectrogram of the original signal in terms of both classification performance and computing complexity. [ABSTRACT FROM AUTHOR]

Wideband radio frequency (RF) channelization is essential for the reception and detection of cross-band RF signals in various applications, including communications, radar, and spectrum sensing. However, digital channelizers are inefficient at performing RF channelization over a working bandwidth above 10 GHz. Meanwhile, current photonic RF channelizers face challenges in simultaneously considering a wideband, multi-channel, and a high crosstalk suppression ratio. In this work, we proposed and demonstrated a wideband image-reject RF channelization scheme based on integrated dual-soliton microcombs. The dual-soliton microcombs are used for RF spectral copies and heterodyne detection, respectively. Supported by image-reject mixers, the RF channelization is verified with an 8–37 GHz working bandwidth, a 1.2 GHz channel bandwidth, and 25 channels. The image suppression ratio is higher than 34 dB for single-tone signals and 20 dB for wideband signals. Our approach provides an innovative architecture of integrated photonic RF channelizers with high performance, which can benefit a wide range of RF applications by miniaturizing the systems. [ABSTRACT FROM AUTHOR]

Chirality (mirror asymmetry) of the unit cell ensures the phenomenon of polarization conversion in a metamaterial/metasurface. In this paper, we control the polarization conversion and asymmetric transmission properties of a metasurface by controlling the chirality of its unit cells. Radio Frequency PIN diode switches are used to control the chirality. When the switches are turned OFF, the unit cells are chiral, and the metasurface successfully exhibits polarization conversion as well as asymmetric transmission for linearly polarized incident waves. When the switches are turned ON, the unit cells become achiral and lose both the above properties. The polarization conversion switching phenomenon is also observed for circularly polarized incident waves. A simple ultrathin metasurface is designed and fabricated to demonstrate these properties. [ABSTRACT FROM AUTHOR]

With the development of communication technology, the interference from passive intermodulation to the communication system has become increasingly severe. Locating the source of passive intermodulation and then repairing or replacing the device experiencing passive intermodulation is a reliable method. Therefore, this paper proposes a dual-frequency signal localization method based on the principle of phase ranging to accurately locate the passive intermodulation sources in RF cables. This method switches the test signal frequency to obtain the phase of passive intermodulation signals at different frequencies to localize the passive intermodulation source. This paper analyzes the principle of the passive intermodulation localization method based on dual-frequency signals, establishes a localization system for experiments, and finally, analyzes the experimental error to propose an optimization strategy. Through experimental verification, this method can stabilize the positioning error of a passive intermodulation source in a transmission line less than 0.06 m. Meanwhile, this method has high positioning accuracy and the advantages of slight computational complexity, fast positioning speed, and only a small number of requirements on hardware resources. It can work in communication scenarios like satellite and base stations, providing a new technical solution for localizing passive intermodulation interference sources in 5G and 6G communication systems. [ABSTRACT FROM AUTHOR]

The noninvasive measurement and sensing of vital bio signs, such as respiration and cardiopulmonary parameters, has become an essential part of the evaluation of a patient's physiological condition. The demand for new technologies that facilitate remote and noninvasive techniques for such measurements continues to grow. While previous research has made strides in the continuous monitoring of vital bio signs using lasers, this paper introduces a novel technique for remote noncontact measurements based on radio frequencies. Unlike laser-based methods, this innovative approach offers the advantage of penetrating through walls and tissues, enabling the measurement of respiration and heart rate. Our method, diverging from traditional radar systems, introduces a unique sensing concept that enables the detection of micro-movements in all directions, including those parallel to the antenna surface. The main goal of this work is to present a novel, simple, and cost-effective measurement tool capable of indicating changes in a subject's condition. By leveraging the unique properties of radio frequencies, this technique allows for the noninvasive monitoring of vital bio signs without the need for physical contact or invasive procedures. Moreover, the ability to penetrate barriers such as walls and tissues opens new possibilities for remote monitoring in various settings, including home healthcare, hospital environments, and even search and rescue operations. In order to validate the effectiveness of this technique, a series of experiments were conducted using a prototype device. The results demonstrated the feasibility of accurately measuring respiration patterns and heart rate remotely, showcasing the potential for real-time monitoring of a patient's physiological parameters. Furthermore, the simplicity and low-cost nature of the proposed measurement tool make it accessible to a wide range of users, including healthcare professionals, caregivers, and individuals seeking to monitor their own health. [ABSTRACT FROM AUTHOR]

The rapid evolution of drone technology has introduced unprecedented challenges in security, particularly concerning the threat of unconventional drone and swarm attacks. In order to deal with threats, drones need to be classified by intercepting their Radio Frequency (RF) signals. With the arrival of Sixth Generation (6G) networks, it is required to develop sophisticated methods to properly categorize drone signals in order to achieve optimal resource sharing, high-security levels, and mobility management. However, deep ensemble learning has not been investigated properly in the case of 6G. It is anticipated that it will incorporate drone-based BTS and cellular networks that, in one way or another, may be subjected to jamming, intentional interferences, or other dangers from unauthorized UAVs. Thus, this study is conducted based on Radio Frequency Fingerprinting (RFF) of drones identified to detect unauthorized ones so that proper actions can be taken to protect the network's security and integrity. This paper proposes a novel method—a Composite Ensemble Learning (CEL)-based neural network—for drone signal classification. The proposed method integrates wavelet-based denoising and combines automatic and manual feature extraction techniques to foster feature diversity, robustness, and performance enhancement. Through extensive experiments conducted on open-source benchmark datasets of drones, our approach demonstrates superior classification accuracies compared to recent benchmark deep learning techniques across various Signal-to-Noise Ratios (SNRs). This novel approach holds promise for enhancing communication efficiency, security, and safety in 6G networks amidst the proliferation of drone-based applications. [ABSTRACT FROM AUTHOR]

The radio frequency (RF) data generated from a single-chip millimeter-wave (mmWave) ground-based multi-input multi-output (GB-MIMO) radar can provide a highly robust, precise measurement for deformation in harsh environments, overcoming challenges such as different lighting and weather conditions. Monitoring deformation is significant for safety factors in different applications, such as detecting and monitoring the ground stability of underground mines. However, radar images can experience different types of clutter and artifacts besides the spreading effects caused by the side lobes, resulting in the foremost challenge of suppressing clutter and monitoring deformation.In the state of the art, the introduced frameworks usually include many filters proposed for different types of noise, with commercial systems typically using an amplitude threshold. This paper proposes a framework for monitoring the deformation, where the essential process is to apply a data-driven threshold to the amplitude heatmap, detect the deformation, and eliminate noise. The proposed threshold is an iterative approach based on radar imagery statistics, and it performs well for the collected dataset. The principal advantage of our proposed framework is simplicity, reducing the burden of using different filters. We can consider the dynamic threshold based on data statistics as a data-driven machine learning tool. The results show promising performance for our method in monitoring the deformation and removing clutter compared to the benchmark method. [ABSTRACT FROM AUTHOR]

In order to perform complex manipulation and grasp tasks, robotic hands require sensors that can handle increasingly demanding functionality and degrees of freedom. This research paper proposes a radiofrequency sensor that uses a wireless connection between a probe and a tag. A compact and low-profile antenna is mounted on the hand and functions as a probe to read a printed passive resonator on the plastic object being targeted, operating within a pre-touch sensing range. The grasping strategy consists of four stages that involve planar alignment in up-to-down and left-to-right directions between the probe and tag, the search for an appropriate distance from the object, and rotational (angular) alignment. The real and imaginary components of the probe-input impedance are analyzed for different orientation strategies and positioning between the resonator on the object and the probe. These data are used to deduce the orientation of the hand relative to the target object and to determine the optimal position for grasping. [ABSTRACT FROM AUTHOR]

Maintaining optimal Indoor Environmental Quality (IEQ) requires continuous measurement of certain variables. To this end, ASHRAE and BPIE recommend that at least the following areas of interest be considered when measuring IEQ: thermal comfort, illuminance, indoor air quality, and noise. At this time, it is not common to find an IoT device that is suitable for dense deployments in schools, university campuses, hospitals, and office buildings, among others, that measures variables in all of the above areas of interest. This paper presents a solution to the problem previously outlined by proposing an IoT device that measures variables across all of the aforementioned areas of interest. Moreover, in a radio frequency network with a tree-like structure of IoT devices, this device is able to assume the roles of sensor and hub node, sensor and router node, and only sensor node. The experimental results are satisfactory, and the detailed system design ensures the replicability of the device. Furthermore, the theoretical analysis paves the way for high scalability. [ABSTRACT FROM AUTHOR]

This paper presents a wideband low-profile dual-polarized patch antenna with helical-shaped L-probe feeding (HLF) for mmWave 5G mobile device applications. Parametric studies on the HLF structure are performed to identify the optimal specifications. As a result, the optimized antenna achieves a wide bandwidth of 5.4 GHz (24.2–29.6 GHz), good isolation > 18 dB between ports, and 5.1 dBi of good peak realized gain, which is experimentally verified with a 10× upscaled antenna. In addition, various one × four phased arrays with different port configurations and beamform capabilities are designed and simulated for the peak realized gain. The designed antenna array shows a high peak realized gain of 10 dBi, high isolation of 15 dB between the ports, and a small substrate thickness of 0.048λ0 (λ0 is the wavelength of 24.25 GHz). Compared to the state-of-the-art antennas, the designed dual-polarized antenna can operate in the frequency ranges of 24.25–29.6 GHz, including n257, n258, and n261 of the 5G new radio frequency range 2. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of coordinated resource allocation for multiple unmanned aerial vehicles (UAVs) to address the scarcity of communication resources in disaster-affected areas. UAVs carrying modules of free space optical (FSO) and radio frequency (RF) serve as relay nodes and edge offloading nodes, presenting an FSO/RF dual-hop framework. Considering the varying urgency levels of tasks, we assign task priorities and transform the proposed problem into distributed collaborative optimization problem. Based on the K-means algorithm and the multi-agent deep deterministic policy gradient (MADDPG) algorithm, we propose a UAV-coordinated K-means MADDPG (KMADDPG) to maximize the number of completed tasks while prioritizing high-priority tasks. Simulation results show that KMADDPG is 5% to 10% better than the benchmark DRL methods in convergence performance. [ABSTRACT FROM AUTHOR]

The RF (Radio Frequency) signals carry both energy and information. Harvesting energy from these RF signals leads to new technology such as WEH (Wireless Energy Harvesting). In this paper, the design of a microstrip-fed spurious free slant antenna array for wireless energy harvesting applications. A prototype antenna operating at 2.45 GHz is designed and fabricated. Defected ground structure (DGS) and stubs have been used to suppress the spurious responses. The measured results show 19% 10 dB return loss bandwidth, 7.11 dBi average gain, and more than 80% radiation efficiency. Spurious radiations up to third harmonics resulting from higher-order modes are effectively suppressed. [ABSTRACT FROM AUTHOR]

LoRa enables long-range communication for Internet of Things (IoT) devices, especially those with limited resources and low power requirements. Consequently, LoRa has emerged as a popular choice for numerous IoT applications. However, the security of LoRa devices is one of the major concerns that requires attention. Existing device identification mechanisms use cryptography which has two major issues: (1) cryptography is hard on the device resources and (2) physical attacks might prevent them from being effective. Deep learning-based radio frequency fingerprinting identification (RFFI) is emerging as a key candidate for device identification using hardware-intrinsic features. In this paper, we present a comprehensive survey of the state of the art in the area of deep learning-based radio frequency fingerprinting identification for LoRa devices. We discuss various categories of radio frequency fingerprinting techniques along with hardware imperfections that can be exploited to identify an emitter. Furthermore, we describe different deep learning algorithms implemented for the task of LoRa device classification and summarize the main approaches and results. We discuss several representations of the LoRa signal used as input to deep learning models. Additionally, we provide a thorough review of all the LoRa RF signal datasets used in the literature and summarize details about the hardware used, the type of signals collected, the features provided, availability, and size. Finally, we conclude this paper by discussing the existing challenges in deep learning-based LoRa device identification and also envisage future research directions and opportunities. [ABSTRACT FROM AUTHOR]

The ANTHEM (Advanced Technologies for Human-centered Medicine) Radio-Frequency Quadrupole (RFQ) will employ eight coaxial power couplers, which will be magnetically coupled to the device through a loop antenna. The coupler design can support up to 140 kW in continuous wave operation. This paper presents the design of the cavity used for high-power testing, with the primary objectives of both optimizing the coupling between the couplers and ensuring operations at the designated operating frequency. Furthermore, the paper encompasses thermal and structural assessments conducted through numerical simulations. [ABSTRACT FROM AUTHOR]

With the increase in the adoption of Internet of Things (IoT) devices, the security threat they face has become more pervasive. Recent research has demonstrated that most IoT devices are insecure and vulnerable to a range of cyber attacks. The impact of such attacks can vary significantly, from affecting the service of the device itself to putting their owners and their personal information at risk. As a response to improving their security, the focus has been on attacks, specifically on the network layer. However, the importance and impact of other vulnerabilities, such as low-level Radio Frequency (RF) attacks, have been neglected. Such attacks are challenging to detect, and they can be deployed using non-expensive equipment and can cause significant damage. This paper explores security vulnerabilities that target RF communications on popular commercial IoT devices such as Wi-Fi, Zigbee, and 433 Mz. Using software-defined radio, a range of attacks were deployed against the devices, including jamming, replay attacks, packet manipulation, protocol reverse engineering, and harmonic frequency attacks. The results demonstrated that all devices used were susceptible to jamming attacks, and in some cases, they were rendered inoperable and required a hard reset to function correctly again. This finding highlights the lack of protection against both intentional and unintentional jamming. In addition, all devices demonstrated that they were susceptible to replay attacks, which highlights the need for more hardened security measures. Finally, this paper discusses proposals for defence mechanisms for enhancing the security of IoT devices against the aforementioned attacks. [ABSTRACT FROM AUTHOR]

The miniaturization and low power consumption characteristics of RF MEMS (Radio Frequency Microelectromechanical System) switches provide new possibilities for the development of microsatellites and nanosatellites, which will play an increasingly important role in future space missions. This paper provides a comprehensive review of RF MEMS switches in satellite communication, detailing their working mechanisms, performance optimization strategies, and applications in reconfigurable antennas. It explores various driving mechanisms (electrostatic, piezoelectric, electromagnetic, thermoelectric) and contact mechanisms (capacitive, ohmic), highlighting their advantages, challenges, and advancements. The paper emphasizes strategies to enhance switch reliability and RF performance, including minimizing the impact of shocks, reducing driving voltage, improving contacts, and appropriate packaging. Finally, it discusses the enormous potential of RF MEMS switches in future satellite communications, addressing their technical advantages, challenges, and the necessity for further research to optimize design and manufacturing for broader applications and increased efficiency in space missions. The research findings of this review can serve as a reference for further design and improvement of RF MEMS switches, which are expected to play a more important role in future aerospace communication systems. [ABSTRACT FROM AUTHOR]

This study compares the performance of graph convolutional neural network (GCN) models with conventional natural language processing (NLP) models for classifying scientific literature related to radio frequency electromagnetic field (RF-EMF). Specifically, the study examines two GCN models: BertGCN and the citation-based GCN. The study concludes that the model achieves consistently good performance when the input text is long enough, based on the attention mechanism of BERT. When the input sequence is short, the composition parameter  λ , which combines output values of the two subnetworks of BertGCN, plays a crucial role in achieving high classification accuracy. As the value of  λ  increases, the classification accuracy also increases. The study also proposes and tests a simplified variant of BertGCN, revealing performance differences among the models under two different data conditions by the existence of keywords. This study has two main contributions: (1) the implementation and testing of a variant of BertGCN and citation-based GCN for document classification tasks related to radio frequency electromagnetic fields publications, and (2) the confirmation of the impact of model conditions, such as the existence of keywords and input sequence length, in the original BertGCN. Although this study focused on a specific domain, our approaches have broader implications that extend beyond scientific publications to general text classification. [ABSTRACT FROM AUTHOR]

Quality fraud seriously damages the right-to-known of customers. Therefore, it is necessary for customers to recheck the process quality level declared by suppliers, which is often measured by process capability indices (PCIs). However, there exist two practical problems when rechecking PCIs based on a quality characteristic (QC). First, QC data often do not follow normal distributions. Second, to enhance the market competitiveness, the supplier usually conducts a full inspection and eliminates the non-conforming items before selling them, which causes the QC data to be truncated. To overcome these problems, motivated by the radio-frequency (RF) power output data, this paper proposes a two-phase process capability recheck method, including data-filling and generalised p-value (GE-P) test. The novel data-filling method integrates the quantile-filling (QA) and bias-correction closed-form (BC) estimator for Gamma distributions, and simulation results show it performs better than the traditional methods on unbiasedness and consistency. Based on the filling pseudo-complete data, GE-P is adopted to complete the recheck by testing whether the process capability reaches the supplier declared level. Numerical analysis indicates it performs well on two types of errors. Finally, a real case study on the motivating example is presented to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Context. Quantifying the number density and physical characteristics of extragalactic polarized sources is important for the successful planning of future studies based on Faraday rotation measure (RM) grids of polarized sources to probe foreground Galactic and intergalactic magnetic fields. However, it is proving very hard to detect polarized signal from the population of very faint (sub-mJy) polarized sources at low radio frequencies, and their properties are mostly unknown. LOFAR can play an important role in such studies thanks to its sensitivity and angular resolution, combined with the precision on the inferred RM values that can be achieved through low-frequency broad-band polarimetry. Aims. The aim of this study is to probe the sub-mJy polarized source population with LOFAR. In this first paper, we present the method used to stack LOFAR polarization datasets, the resulting catalog of polarized sources, and the derived polarized source counts. Methods. The European Large Area ISO Survey-North 1 (ELAIS-N1) field, one of the deepest of the LOFAR Two-Metre Sky Survey (LoTSS) Deep Fields so far, was selected for a polarimetric study at 114.9–177.4 MHz. A total area of 25 deg2 was imaged at 6″-resolution in the Stokes Q and U parameters. Alignment of polarization angles was done both in frequency and in Faraday space before stacking datasets from 19 eight-hour-long epochs taken in two different LOFAR observing cycles. A search for polarized sources was carried out in the final, stacked dataset, and the properties of the detected sources were examined. The depolarization level of sources known to be polarized at 1.4 GHz was quantified. Results. A one-sigma noise level, σQU, of 19 µJy beam−1 was reached in the central part of the field after stacking. Twenty-five polarized sources were detected above 8σQU, five of which had not been detected in polarization at any other radio frequencies before. Seven additional polarized components were found by lowering the threshold to 6σQU at positions corresponding to sources known to be polarized at 1.4 GHz. In two radio galaxies, polarization was detected from both radio lobes, so the final number of associated radio continuum sources is 31. The detected sources are weakly polarized, with a median degree of polarization of 1.75% for the sample of sources detected in polarized emission. For the 10 polarized sources previously identified in a pilot LOFAR study of the ELAIS-N1 field at 20″-resolution, the RM values are consistent but the degrees of polarization are higher in the 6″-resolution data. The sources previously detected in polarization at 1.4 GHz are significantly depolarized at 150 MHz. The catalog is used to derive the polarized source counts at 150 MHz. Conclusions. This is the deepest and highest-resolution polarization study at 150 MHz to date. A full characterization of the sources and an analysis of the catalog will be presented in Paper II. [ABSTRACT FROM AUTHOR]

To send and receive data simultaneously, reduce network interference, and effectively improve energy efficiency, this paper analyzes the network characteristics of Multi-Radio Multi-Channel Wireless Sensor Network and optimizes the power and channel of each radio frequency interface. Based on the novel energy efficiency model and energy consumption efficiency model, this paper establishes a distributed optimization game model using Game Theory to maximize network energy efficiency, minimize energy consumption, and ensure network connectivity. Based on the game model, an efficient distributed resource allocation game algorithm is designed, in which a joint power control and channel allocation can quickly converge to Nash Equilibrium with low complexity. At the same time, the simulation results show that the distributed resource allocation game algorithm can effectively improve the energy efficiency, reduce network interference and bit error rate to ensure the successful data transmission. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In this paper, an Improved Pelican Optimization Algorithm (IPOA) was proposed to optimize a BP neural network model to predict the dielectric loss factor of wood in the RF heating and drying process. The neural network model was trained and optimized using MATLAB 2022b software, and the prediction results of the BP neural network with POA-BP and IPOA-BP models were compared. The results show that the IPOA-optimized BP neural network model is more accurate than the traditional BP neural network model. After the BP neural network model with IPOA optimization was used to predict the dielectric loss factor of wood, the value increased by 4.3%, the MAE decreased by 68%, and the RMSE decreased by 67%. The results provided by the study using the IPOA-BP model show that the prediction of the dielectric loss factor of wood under different macroscopic conditions in radio frequency heating and drying of wood can be realized without the need for highly costly and prolonged experimental studies. [ABSTRACT FROM AUTHOR]

This paper presents the design results for a self-interference canceller (SIC) based on a symmetric delay-line radio frequency finite impulse response (RF-FIR) filter with a ladder structure. The proposed SIC effectively removes self-interference signals in the receiver caused by the low isolation of the circulator applied to the monostatic radar front end and the impedance mismatch of the antenna. Consequently, it enhances the isolation between the transmitter and receiver. The proposed filter consists of six taps with adjustable sizes and phases. The phase-delay values for each filter tap are implemented at a reference frequency of 3.1 GHz. The measurement results demonstrate that the proposed SIC achieves over 25 dB suppression of self-interference signals in the frequency range of 3.05 to 3.22 GHz. When applied to a monostatic radar transceiver with an RF circulator, it exhibits isolation strength of over 50 dB in the frequency range of 3.04 to 3.22 GHz. [ABSTRACT FROM AUTHOR]

Visible light communication (VLC) is a promising complementary technology to its radio frequency (RF) counterpart to satisfy the high quality-of-service (QoS) requirements of intelligent vehicular communications by reusing LED street lights. In this paper, a hybrid handover scheme for vehicular VLC/RF communication networks is proposed to balance QoS and handover costs by considering the vertical handover and horizontal handover together judging from the mobile state of the vehicle. A Markov decision process (MDP) is formulated to describe this hybrid handover problem, with a cost function balancing the handover consumption, delay, and reliability. A value iteration algorithm was applied to solve the optimal handover policy. The simulation results demonstrated the performance of the proposed hybrid handover scheme in comparison to other benchmark schemes. [ABSTRACT FROM AUTHOR]

This paper proposed a fine dust detection system using time-interleaved counters in which surface acoustic wave (SAW) sensors changed the resonance point characteristic. When fine dust was applied to the SAW sensor, the resonance point decreased. The SAW oscillator made of the SAW sensor and radio frequency (RF) amplifier generated an oscillation frequency that was the same as the resonance frequency. The oscillation frequency was transferred to digital data by a 20-bit asynchronous counter. This system has two channels: a sensing channel and a reference channel. Each channel has a SAW oscillator and a 20-bit asynchronous counter. The difference of the two channel counter results is the frequency difference. Through this, it is possible to know whether fine dust adheres to the SAW sensor. The proposed circuit achieved 0.95 ppm frequency resolution when it was operated at a frequency of 460 MHz. This circuit was implemented in a TSMC 130 nm CMOS process. [ABSTRACT FROM AUTHOR]

This paper presents a lumped scalable model for spiral inductors in a radio frequency (RF) gallium nitride (GaN) technology on silicon substrate. The model has been developed by exploiting electromagnetic (EM) simulations of geometrically scaled spiral inductors. To this aim, the technology substrate, i.e., the metal back-end-of-line along with dielectric and semiconductor layers of the adopted GaN process, has been validated by means of experimental data and then used to define the EM simulator set-up for the spiral inductors. The proposed model adopts a simple π-topology with only seven lumped components and predicts inductor performance in terms of inductance, quality factor (Q-factor) and self-resonance frequency (SRF) for a large range of geometrical parameters of the spiral (i.e., number of turns, metal width, inner diameter). [ABSTRACT FROM AUTHOR]

This paper presents a frequency-reconfigurable dual-band radio frequency (RF) crossover based on quarter-wavelength coupled lines (CLs) and open stubs. Initially, an even–odd-mode analysis was conducted for the design, and closed-form equations were found. Then an advanced design system (ADS) was utilized to support and further optimize the theoretical analysis. Afterwards, high-frequency simulation software (HFSS) was used to simulate the proposed design. The proposed device is printed on a 1.524 mm RO4003C printed-circuit board ( ε r = 3.55) . The frequency tunability is achieved by employing two varactor diodes connected to the open stubs. When the biasing voltage is altered, the capacitance of the SMV1405 varactor can change from 2.67 pF to 0.63 pF. Accordingly, the two operating frequencies can be continuously tuned from 2.06 GHz to 2.40 GHz and from 5.44 GHz to 5.84 GHz. For the low-frequency range, return loss and isolation are above 15 dB, and the insertion loss is less than 1.1 dB. As for the high-frequency range, the return loss is greater than 20 dB, the isolation is better than 15 dB, and the insertion loss is lower than 1.6 dB. The measurement results agreed well with the simulation results, and the crossover overall size is 45.5 mm × 29.4 mm. The proposed device can be utilized for various application areas, such as 5G smartphone applications and satellite communication. [ABSTRACT FROM AUTHOR]

This paper proposes a cognitive radio network (CRN)-based hybrid wideband precoding for maximizing spectral efficiency in millimeter-wave relay-assisted multi-user (MU) multiple-input multiple-output (MIMO) systems. The underlying problem is NP-hard and non-convex due to the joint optimization of hybrid processing components and the constant amplitude constraint imposed by the analog beamformer in the radio frequency (RF) domain. Furthermore, the analog beamforming solution common to all sub-carriers adds another layer of design complexity. Two hybrid beamforming architectures, i.e., mixed and fully connected ones, are taken into account to tackle this problem, considering the decode-and-forward (DF) relay node. To reduce the complexity of the original optimization problem, an attempt is made to decompose it into sub-problems. Leveraging this, each sub-problem is addressed by following a decoupled design methodology. The phase-only beamforming solution is derived to maximize the sum of spectral efficiency, while digital baseband processing components are designed to keep interference within a predefined limit. Computer simulations are conducted by changing system parameters under different accuracy levels of channel-state information (CSI), and the obtained results demonstrate the effectiveness of the proposed technique. Additionally, the mixed structure shows better energy efficiency performance compared to its counterparts and outperforms benchmarks. [ABSTRACT FROM AUTHOR]

This work raises the hypothesis that it is possible to use ferromagnetic carbon nanotubes filled with iron to hyperthermally destroy cancer cells in a radiofrequency electromagnetic field. This paper describes the synthesis process of iron-filled multi-walled carbon nanotubes (Fe-MWCNTs) and presents a study of their magnetic properties. Fe-MWCNTs were synthesized by catalytic chemical vapor deposition (CCVD). Appropriate functionalization properties of the nanoparticles for biomedical applications were used, and their magnetic properties were studied to determine the heat generation efficiency induced by exposure of the particles to an external electromagnetic field. The response of the samples was measured for 45 min of exposure. The results showed an increase in sample temperature that was proportional to concentration. The results of laboratory work were compared to the simulation using COMSOL software. [ABSTRACT FROM AUTHOR]

This paper demonstrates improved throughput and energy efficiency of wireless communications by exploiting nonorthogonal multiple access (NOMA), multiple input–multiple output (MIMO), and radio frequency energy harvesting (EH) technologies. To assess the performance of NOMA MIMO communications with EH (MMe), we consider the nonlinear characteristics of EH devices and propose explicit expressions for throughput and outage probability. Based on our results, the system performance is significantly mitigated by EH nonlinearity and is considerably improved by increasing the number of antennas. Additionally, by appropriately adjusting the system parameters, our NOMA MMe innovation can avert complete outages while optimizing system performance. Moreover, the results demonstrate the superiority of the NOMA MMe over its orthogonal multiple access MMe counterparts. [ABSTRACT FROM AUTHOR]

This paper demonstrates the analytical approach of Linearized Radio over Fiber (RoF) link based on Dual-Drive Dual Parallel Mach Zehnder Modulator (DD-DPMZM) by properly adjusting the phase shifters and biasing of the Mach Zehnder Modulator (MZM). Two input RF Source at 7 and 8 GHz applied in the used RoF link. The proposed RoF link consists of Mach Zehnder Modulator (MZM), Parallel combination of Mach Zehnder Modulators, optical fiber, and photodetector (PD). Third Order Intermodulation Distortions (IMD3) factor act as a major issue, which is responsible as performance degradation factor. Major sources of IMD3 spurious components have been investigated and suppressed in theoretical analysis before photodetection. The proposed method is designed with the help of OptSim simulation software, to confirm and validate the analytical analysis and simulation results. Analytical analysis & simulation results show that, 40 dB suppression found in IMD3 spurious components, and 30 dB.Hz2/3 enhancement found in Spurious Free Dynamic Range (SFDR), for the proposed linearized RoF link as compared to conventional MZM RoF link. The Measured SFDR is also founded as 26 dB.Hz2/3, 5 dB.Hz2/3, & 10 dB.Hz2/3 for different optical fiber impairments as 8 km, 10 km & 15 km respectively for used DD-DPMZM based RoF link. [ABSTRACT FROM AUTHOR]

With the maturation of digital radio frequency memory (DRFM) technology, various intra-pulse retransmission interference methods have emerged. These flexible and changeable retransmission interference methods pose significant challenges to radar detection tasks, particularly in modern battlefields. This paper proposes an attention-guided complex-valued transformer (AGCT) as a solution. First, the encoder maps the received signal contaminated by interference and noise into a high-dimensional space. Then, the dilated convolution block (DCB) group and attention block (AB) group in the mask estimator extract the delicate multi-scale features and large-scale features of the interference, respectively, to obtain a multidimensional space mask. Finally, the decoder restores interference to the time domain and outputs the estimated target echo using residual learning. Considering the characteristics of intra-pulse interference, we introduced the energy attention block (EAB) at the end of the DCBs and the ABs within our network. This addition ensures a heightened focus on extracting interference features. Furthermore, we implemented a curriculum learning strategy during the network training. This approach gradually acclimates the network to fit different types of retransmission interference, starting from simpler to more complex scenarios. Our extensive experiments, conducted under various conditions, have provided compelling evidence of the AGCT's superior performance. Compared to the comparative network, the AGCT's advantages are particularly pronounced under more harsh conditions, demonstrating its robustness and effectiveness. [ABSTRACT FROM AUTHOR]

The use of tag devices in marine environments has become indispensable in attaining a better understanding of marine life and contributing to conservation efforts. However, the successful deployment and operation of underwater tags both depend significantly on their hydrodynamic characteristics, particularly their resistance to motion and stability in various environmental conditions. Herein, a comprehensive study on the hydrodynamic characteristics and optimization of an underwater tag designed for monitoring blue sharks is presented. Firstly, a validation process is conducted by comparing the computational fluid dynamics (CFD) results with the experimental data from Myring's study, focusing on the resistance characteristics of the tag's body and the impact of various operational conditions. Subsequently, the validated CFD model is applied to assess the hydrodynamic performance of the tag under different flow conditions, velocities, and angles of attack. Through iterative simulations, including mesh independence studies and boundary condition adjustments, the study identifies key parameters influencing the tag's resistance and stability. Furthermore, the paper proposes and implements design modifications, including the incorporation of stabilizing fins, aimed at minimizing resistance and improving the tag's equilibrium position. The effectiveness of these design enhancements is demonstrated through a comparative analysis of resistance and pitching moments for both preliminary and optimized tag configurations. Overall, the study provides valuable insights into the hydrodynamic behavior of underwater tags and offers practical recommendations for optimizing their design to minimize interference with the movement of tagged marine animals. [ABSTRACT FROM AUTHOR]

This paper describes the principles behind the radio-frequency (RF) sensing of bacterial biofilms in pipes and heat exchangers in a dairy processing plant using an electromagnetic simulation. Biofilm formation in dairy processing plants is a common issue where the absence of timely detection and subsequent cleaning can cause serious illness. Biofilms are known for causing health issues and cleaning requires a large volume of water and harsh chemicals. In this work, milk transportation pipes are considered circular waveguides, and pasteurizers/heat exchangers are considered resonant cavities. Simulations were carried out using the CST studio suite high-frequency solver to determine the effectiveness of the real-time RF sensing. The respective dielectric constants and loss tangents were applied to milk and biofilm. In our simulation, it was observed that a 1 µm thick layer of biofilm in a milk-filled pipe shifted the reflection coefficient of a 10.16 cm diameter stainless steel circular waveguide from 0.229 GHz to 0.19 GHz. Further sensitivity analysis revealed a shift in frequency from 0.8 GHz to 1.2 GHz for a film thickness of 5 µm to 10 µm with the highest wave reflection (S11) peak of ≈−120 dB for a 6 µm thick biofilm. A dielectric patch antenna to launch the waves into the waveguide through a dielectric window was also designed and simulated. Simulation using the antenna demonstrated a similar S11 response, where a shift in reflection coefficient from 0.229 GHz to 0.19 GHz was observed for a 1 µm thick biofilm. For the case of the resonant cavity, the same antenna approach was used to excite the modes in a 0.751 m × 0.321 m × 170 m rectangular cavity with heat exchange fins and filled with milk and biofilm. The simulated resonance frequency shifted from 1.52 GHz to 1.54 GHz, for a film thickness varying from 1 µm to 10 µm. This result demonstrated the sensitivity of the microwave detection method. Overall, these results suggest that microwave sensing has promise in the rapid, non-invasive, and real-time detection of biofilm formation in dairy processing plants. [ABSTRACT FROM AUTHOR]

Radio waves are significant for operating in an underground tunnel or a cave, such as two-way radio systems or emergency communication during rescue operations. Most applications used in the tunnels require wired connections because of the high attenuation of the wireless propagation. In particular, the attenuation in caves is higher than in tunnels because of the non-uniform nature of the walls. Therefore, this paper presents a study of the radio wave propagation within a cave. The experiment covers the low-frequency (LF) to ultra-high frequency (UHF) bands that aim to analyze the attenuation and behavior of waves in caves. Study results show that the low frequency and medium frequency (MF) bands can penetrate cave walls due to the deeper skin depth. At the same time, higher frequencies perform well in line-of-sight (LOS) propagation over short distances, albeit encountering significant attenuation in non-uniform cave environments. The skin depth condition obtained in the propagation result led to the Through-the-Earth (TTE) experiment by making two hand-made transceivers in the beginning band of MF at 350 kHz for transmitting and receiving waves between the mountain surface and the cave passage directly through the rock layer. The results of the TTE experiment show that the transceivers can transmit to 571 meters with a received power of -85.0 dBm before encountering an obstacle that makes it impossible to continue. Finally, the results are significant for developing the application of radio frequency within caves or tunnels and improving the application of the TTE technique with more versatility and efficiency. [ABSTRACT FROM AUTHOR]

Recently, Internet of Drones (IoD) has garnered significant attention due to its widespread applications. However, deploying IoD for area coverage poses numerous limitations and challenges. These include interference between neighboring drones, the need for directional antennas, and altitude restrictions for drones. These challenges necessitate the development of efficient solutions. This research paper presents a cooperative decision-making approach for an efficient IoDdeployment to address these challenges effectively. The primary objective of this study is to achieve an efficient IoDdeployment strategy thatmaximizes the coverage regionwhileminimizing interference between neighboring drones. In deployment problem, the interference increases as the number of deployed drones increases, resulting in bad quality of communication. On the other hand, deploying a few drones cannot satisfy the coverage demand. To accomplish this, an enhanced version of a concise population-based meta-heuristic algorithm, namely Improved Particle SwarmOptimization (IPSO), is applied. The objective function of IPSO is defined based on the coverage probability, which is primarily influenced by the characteristics of the antennas and drone altitude. A radio frequency (RF) model is derived to evaluate the coverage quality, considering both Line of Sight (LOS) and Non-Line of Sight (NLOS) down-link coverage probabilities for ground communication. It is assumed that each drone is equipped with a directional antenna to optimize coverage in a given region. Extensive simulations are conducted to assess the effectiveness of the proposed approach. Results demonstrate that the proposed method achieves maximum coverage with minimum transmission power. Furthermore, a comparison is made against Collaborative Visual Area Coverage Approach (CVACA), and a game-based approach in terms of coverage quality and convergence speed. The simulation results reveal that our approach outperforms both CVACA and the gamebased schemes in terms of coverage and convergence speed. Comparisons validate the superiority of our approach over existing methods. To assess the robustness of the proposed RFmodel, we have considered two distinct ranges of noise: range1 spanning from-120 to-90 dBm, and range2 spanning from-90 to-70 dBmfor different numbers of UAVs. In summary, this research presents a cooperative decision-making approach for efficient IoD deployment to address the challenges associated with area coverage and achieves an optimal coverage with minimal interference. [ABSTRACT FROM AUTHOR]

Transfer learning (TL) techniques have proven useful in a wide variety of applications traditionally dominated by machine learning (ML), such as natural language processing, computer vision, and computer-aided design. Recent extrapolations of TL to the radio frequency (RF) domain are being used to increase the potential applicability of RFML algorithms, seeking to improve the portability of models for spectrum situational awareness and transmission source identification. Unlike most of the computer vision and natural language processing applications of TL, applications within the RF modality must contend with inherent hardware distortions and channel condition variations. This paper seeks to evaluate the feasibility and performance trade-offs when transferring learned behaviors from functional RFML classification algorithms, specifically those designed for automatic modulation classification (AMC) and specific emitter identification (SEI), between homogeneous radios of similar construction and quality and heterogeneous radios of different construction and quality. Results derived from both synthetic data and over-the-air experimental collection show promising performance benefits from the application of TL to the RFML algorithms of SEI and AMC. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to demonstrate a new discovery regarding the interaction between materials and very low radio frequencies. Specifically, we observed a feedback response on an inertia active sensor when specific frequencies (around 2–4 kHz) are used to irradiate targeted pharmaceutical samples like aspirin or paracetamol drugs. The characteristics of this phenomenon, such as excitation and relaxation time, the relation between deceleration and a material's quantity, and signal amplitude, are presented and analyzed. Although the underlying physics of this phenomenon is not yet known, we have shown that it has potential applications in remote identification of compounds, detection, and location sensing, as well as identifying substances that exist in plants without the need for any processing. This method is fast, accurate, low-cost, non-destructive, and non-invasive, making it a valuable area for further research that could yield spectacular results in the future. [ABSTRACT FROM AUTHOR]

This paper presents a switchable self-bias polarity on the CMOS complementary cross-coupled rectifier to improve the rectifier's power conversion efficiency (PCE) profile across a wide input power (PIN) dynamic range. This technique achieves this by adaptively switching the polarity of the bias on the n-MOS to overdrive it during low PIN to improve the sensitivity and underdrive it during high PIN to suppress the shoot-through loss and the unnecessary discharge of the coupling capacitor. The popular self-biased p-MOS is also implemented further to reduce the reverse conduction loss during high PIN. The proposed rectifier is fabricated in a 40 nm CMOS process and operates at 900 MHz with a load of 50 kΩ. The proposed rectifier achieved a peak PCE of 72.1% and maintained a 0.8xPCEPEAK across a PIN dynamic range of 11.5 dB. [ABSTRACT FROM AUTHOR]

A hybrid free-space optical (FSO) and radio frequency (RF) communication system has been considered an effective way to obtain a good trade-off between spectrum utilization efficiency and high-rate transmission. Utilizing artificial intelligence (AI) to deal with the switching and rate adaption problems between FSO/RF links, this paper investigated their modulation adapting mechanism based on a machine learning (ML) algorithm. Hybrid link budgets were estimated for different modulation types in various environments, particularly severe weather conditions. For the adaptive modulation (AM) scheme with different order PPM/PSK/QAM, a rate-compatible soft-switching model for hybrid FSO/RF links was established with a random forest algorithm based on ML. With a given target bit error rate, the model categorized a link budget threshold of the hybrid FSO/RF system over a training data set from local weather records. The switching and modulation adaption accuracy were tested over the testing weather data set especially focusing on rain and fog. Simulation results show that the proposed adaptive modulation scheme based on the random forest algorithm can have a good performance for soft-switching hybrid FSO/RF communication links. [ABSTRACT FROM AUTHOR]

In recent years, with the continuous derivative of the Internet of Things (IoT) business, the use of various types of information sensing equipment needs to continue to increase. However, power supply conditions are getting tougher. On the other hand, as the function of the devices itself increases, the power consumption also increases, and the lack of energy demand is more obvious. To solve these problems, a dual-frequency RF energy harvesting system is designed in this paper. First of all, in order to expand the effective receiving range of RF energy, this paper designed a 920 MHz hexagonal windmill circular-polarized antenna, and added an energy receiving circuit in the 2.45 GHz band on this basis, which fully alleviated the problem of insufficient energy collection for small devices in the Internet of Things while ensuring a small volume wavelength ratio. In addition, in order to improve the energy conversion efficiency, this paper also designed a dual-frequency rectifier circuit based on conjugate separation matching, using the harmonic signal of 920 MHz signal to broaden the bandwidth of 2.45 GHz. The experimental results show that the peak conversion rates of 920 MHz and 2.45 GHz channels are 72.8%@0dBm and 38.7%@-2dBm, respectively. Overall testing in a Wireless Fidelity (Wi-Fi) room with a commercial Radio Frequency Identification (RFID) reader. The experimental results show that the system can steadily output 3.29 V–3.3 V voltage within 6 m charging distance, which is 20% higher than the output voltage of the single-channel receiving system, and the receiving angle is 36.84% larger. [ABSTRACT FROM AUTHOR]

Nb3Sn is emerging as one of the focal points in superconducting radio frequency (SRF) research, owing to its excellent superconducting properties. These properties hold significant possibilities for cost reduction and the miniaturization of accelerators. In this paper, we report the recent efforts of the Shanghai Advanced Research Institute (SARI) in fabricating high-performance Nb3Sn superconducting cavities using the vapor diffusion method. This includes the construction of a Nb3Sn coating system with dual evaporators and the test results of 1.3 GHz single-cell coated cavities. The coated samples were characterized, and the growth state of the Nb3Sn films was analyzed. The first coated superconducting cavity was tested at both 4.4 K and 2 K, with different cooldown rates passing through the Nb3Sn critical temperatures. The causes of Sn droplet spot defect formation on the surface of the first cavity were analyzed, and such defects were eliminated in the coating of the second cavity by controlling the evaporation rate. This study provides a reference for the preparation of high-performance Nb3Sn-coated cavities using the vapor diffusion method, including the setup of the coating system, the comprehension of the vapor diffusion process, and the test conditions. [ABSTRACT FROM AUTHOR]