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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]

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]

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]

This paper introduces a novel compact ultralightweight multiband RF energy harvester fabricated on a paper substrate. The proposed rectenna is designed to operate in all recently released LTE bands (range 0.79–0.96 GHz; 1.71–2.17 GHz; and 2.5–2.69 GHz). High compactness and ease of integration between antenna and rectifier are achieved by using a topology of nested annular slots. The proposed rectifier features an RF-to-dc conversion efficiency in the range of 5%–16% for an available input power of −20 dBm in all bands of interest, which increases up to 11%–30% at −15 dBm. The rectenna has been finally tested both in laboratory and in realistic scenarios featuring a superior performance to other state-of-the-art RF harvesters on flexible substrates. [ABSTRACT FROM PUBLISHER]

This paper presents a radio frequency plasma equipment designed to be used for the conservation procedures, such as decontamination, cleaning, and consolidation of cellulose-based materials. Decontamination and cleaning are carried out by the low-temperature nitrogen plasma generated between two electrodes, connected to a 1.5-MHz generator. The paper consolidation is performed by coating with compatible polymers in view of long term protection. Surface analyses (color analysis and electron microscopy) were undertaken to assess the uniform display of the polymer on the paper surface. The microbiological tests made on representative samples collected from historical books attested the complete inhibition of bacteria and fungi after, at most, 7-min treatment duration, depending on the initial infestation degree. [ABSTRACT FROM AUTHOR]

Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers. [ABSTRACT FROM AUTHOR]

The joint radar‐communication (JRC) system is envisioned as an emerging sixth generation (6G) technology to tackle spectral congestion and hardware limitations by jointly implementing the communication and radar sensing on the same hardware platform and using the common radio frequency (RF) resources. Joint radar‐communication systems with a multi‐antenna setup leads to higher degrees of freedom, and hybrid beamforming can be exploited to achieve lower hardware complexity than conventional fully digital systems. This paper aims to design a spectral efficiency maximisation approach for a 6G inclined JRC system with hybrid beamforming and multi‐antenna setup while considering the interference between communication and radar operations and hardware impairments in the system. The rate expressions for communication and radar operations are defined, and the joint spectral efficiency is maximised via optimising the number of RF chains using an efficient selection algorithm taking into account the interference of one operation to the other and system hardware distortion. The simulation results are shown to support the effectiveness of the proposed approach, and they are compared with that of existing fully digital and hybrid beamforming based baseline methods with fixed number of RF chains. The proposed approach also exhibits a desirable communication‐radar trade‐off in terms of spectral efficiency gains. [ABSTRACT FROM AUTHOR]

The choice of gate metal technology for junctionless transistors needs to have diverse characteristics as metals have distinct work functions and hence, they show incompatibility while tailoring threshold of the device. In such a scenario, bimetallic stacked gate can be a promising candidate to present wide range of tunable work functions required for nanoregime junctionless transistors. This paper explores the electronic phenomena occurring at metal-metal interface and the impact of Platinum (Pt)/Titanium (Ti) bimetallic stacked gate-based work function tunability on the RF and thermal performances of p-type window-based Silicon on Insulator Junctionless Transistor (SOI JLT) using numerical simulator SILVACO ATLAS. The parameters considered for performance evaluation are ON-state current (ION), OFF-state current (IOFF ), ION/IOFF ratio, transconductance (gm), cutoff frequency (fT ), Transconductance Frequency Product (TFP), Intrinsic Gate Delay (IGD), intrinsic gain (AV ), and Global Device Temperature (GDT). The gm, fT, TFP, AV and GDT improve for modified over conventional in the ON state at higher work function, while IGD improves at lower work function. The improvements of 11.7 % and 2.21 % are obtained in maximum gm and fT, respectively, for modified transistor over conventional. The findings suggest that bimetallic stacked gate modified SOIJLT is a better option than conventional for low-power RF application. [ABSTRACT FROM AUTHOR]

This paper presents the work of the LAPLACE Electromagnetism Research Group to build an experimental setup able to measure tiny forces that may appear in microwave cavities, in the context of EMDrive investigations. It is based on a commercial balance in the range of 0.1mN sensitivity, a contactless feeding for more than 150W RF power, and self calibrating device process. It requires a double cavity system in mirror configuration and is here experimented with frustum cavities, different from the NASA one [1]. The global setup can make force measurement and calibration in less than two seconds. Investigating two different cavities and various electromagnetic modes for the biggest, no force is reported while the 0.1mN sensitivity is demonstrated. [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]

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]

The newly developed research area of inkjet-printed radio frequency (RF) electronics on cellulose-based and synthetic paper substrates is introduced in this paper. This review paper presents the electrical properties of the paper substrates, the printed silver nanoparticle-based thin films, the dielectric layers, and the catalyst-based metallization process. Numerous inkjet-printed microwave passive/ative systems on paper, such as a printed radio frequency identification (RFID) tag, an RFID-enabled sensor utilizing carbon nanotubes (CNTs), a substrate-integrated waveguide (SIW), fully printed vias, an autonomous solar-powered beacon oscillator (active antenna), and artificial magnetic conductors (AMC), are discussed. The reported technology could potentially act as the foundation for true "green" low-cost scalable wireless topologies for autonomous Internet-of-Things (IoT), bio-monitoring, and "smart skin" applications. [ABSTRACT FROM AUTHOR]

This work proposes a new compact triple-band triangular patch antenna for RF energy harvesting applications in IoT devices. It is realized on Teflon glass substrate with a thickness of 0.67 mm and a relative permittivity of 2.1. Four versions of this antenna have been designed and realized with inclinations of 0°, 30°, 60° and 90° to study the impact of the tilting on their characteristics (S11 parameter, radiation pattern, gain) and to explore the possibilities of their implementation in the architectures of electronic equipment according to the available space. The antenna is also realized on waterproof paper with a thickness of 0.1 mm and a relative permittivity of 1.4 for biomedical domain. All the antennas (vertical antenna, tilted antennas and antenna realized on waterproof paper) have a size of 39 × 9 mm2 and cover the 2.45 GHz and 5.2 GHz Wi-Fi bands and the 8.2 GHz band. A good agreement is obtained between measured and simulated results. Radiation patterns show that all the antennas are omnidirectional for 2.45 GHz and pseudo-omnidirectional for 5.2 GHz and 8.2 GHz with maximum measured gains of 2.6 dBi, 4.55 dBi and 6 dBi, respectively. The maximum measured radiation efficiencies for the three antenna configurations are, respectively, of 75%, 70% and 72%. The Specific Absorption Rate (SAR) for the antenna bound on the human body is of 1.1 W/kg, 0.71 W/kg and 0.45 W/kg, respectively, for the three frequencies 2.45 GHz, 5.2 GHz and 8.2 GHz. All these antennas are then applied to realize RF energy harvesting systems. These systems are designed, realized and tested for the frequency 2.45 GHz, −20 dBm input power and 2 kΩ resistance load. The maximum measured output DC power is of 7.68 µW with a maximum RF-to-DC conversion efficiency of 77%. [ABSTRACT FROM AUTHOR]

The development and growth of Wireless Sensor Networks (WSNs) is significantly propelled by advances in Radio Frequency (RF) and Visible Light Communication (VLC) technologies. This paper endeavors to present a comprehensive review of the state-of-the-art in cognitive hybrid RF-VLC systems for WSNs, emphasizing the critical task of seamlessly integrating Cognitive Radio Sensor Networks (CRSNs) and VLC technologies. The central challenge addressed is the intricate landscape of this integration, characterized by notable trade-offs between performance and complexity, which escalate with the addition of more devices and increased data rates. This scenario necessitates the development of advanced cognitive radio strategies, potentially facilitated by Machine Learning (ML) and Deep Learning (DL) approaches, albeit introducing new complexities such as the necessity for pre-training with extensive datasets. The review scrutinizes the fundamental aspects of CRSNs and VLC, spotlighting key areas like Energy Efficient Resource Allocation, Industrial Scenarios, and Energy Harvesting, and explores the synergistic amalgamation of these technologies as a promising pathway for enhanced spectrum utilization and network performance. By delving into the integration of cognitive radio technology with visible light, this study furnishes valuable insights into the potential for innovative applications in wireless communication, presenting a balanced overview of the current advancements and prospective avenues in the field of cognitive hybrid RF/VLC systems. [ABSTRACT FROM AUTHOR]

The use of nonmetallic conductor materials in RF applications has recently become a highlighted issue when it comes to sustainability in the electronics industry, mainly because of the waste problems associated with heavy metals and the necessity of reducing and managing them. The replacement of metal in functional applications such as in electronics is therefore very important. Among these new materials, organic conductors are of great interest since they are, in general, biocompatible and biodegradable, allowing for the disposal of electronic devices, which reduces the negative environment impact caused by electronics waste. In this work, PEDOT:PSS and Carbon are investigated. Since these materials are available as conducting pastes or inks, the production of conducting patterns by printing techniques such as screen printing is possible, which can make the process less harmful to the environment, since it permits the use of organic substrates such as paper. In order to investigate the feasibility of these materials for RF signal transmission, screen printed PEDOT:PSS and Carbon transmission lines have been designed, fabricated and characterized. Results regarding conductivity, thickness, electric permittivity and S21 parameter are presented and will serve as a foundation for the development of further reaching applications utilizing organic materials. [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]

With the development and popularization of the Beidou-3 navigation satellite system (BDS-3), to ensure its unique short message function, it is necessary to integrate a radio frequency (RF) transmitting circuit with high performance in the BDS-3 terminal. As the key device in an RF transmitting circuit, the RF power amplifier (PA) largely determines the comprehensive performance of the circuit with its transmission power, efficiency, linearity, and integration. Therefore, in this paper, an L-band highly integrated PA chip compatible with 3 W and 5 W output power is designed in InGaP/GaAs heterojunction bipolar transistor (HBT) technology combined with temperature-insensitive adaptive bias technology, class-F harmonic suppression technology, analog pre-distortion technology, temperature-insensitive adaptive power detection technology, and land grid array (LGA) packaging technology. Additionally, three auxiliary platforms are proposed, dedicated to the simulation and optimization of the same type of PA designs. The simulation results show that at the supply voltage of 5 V and 3.5 V, the linear gain of the PA chip reaches 39.4 dB and 38.7 dB, respectively; the output power at 1 dB compression point (P1dB) reaches 37.5 dBm and 35.1 dBm, respectively; the saturated output power (Psat) reaches 38.2 dBm and 36.2 dBm, respectively; the power added efficiency (PAE) reaches 51.7% and 48.2%, respectively; and the higher harmonic suppression ratios are less than −62 dBc and −65 dBc, respectively. The size of the PA chip is only 6 × 4 × 1 mm3. The results also show that the PA chip has high gain, high efficiency, and high linearity under both output power conditions, which has obvious advantages over similar PA chip designs and can meet the short message function of the BDS-3 terminal in various application scenarios. [ABSTRACT FROM AUTHOR]

The impedance expansion method (IEM), which has been previously proposed by the authors of this paper, is a circuit modeling technique for electrically very small devices. This paper describes a circuit modeling procedure that utilizes the IEM and eigenmode analysis for a wireless power transfer system. First, a multimode circuit model that can represent the higher order resonances in a broadband frequency range is presented. Subsequently, a single-mode circuit model—consisting only of passive elements—that can represent both the radiated and conduction loss powers at approximately its operating frequency band is presented. [ABSTRACT FROM AUTHOR]

The escalating component density in radio frequency (RF) systems presents a growing challenge related to the coupling of adjacent microstrip lines in high-density printed circuit boards (PCBs). As a result, to tackle this prominent issue, there is a continuous pursuit of innovative techniques to effectively minimize the coupling effects among closely spaced microstrip lines. This paper proposes a reduction in the coupling of adjacent lines by utilizing a coating (stiffener) layer, which is commonly used in rigid-flex PCB fabrication. For this purpose, a reference 50 Ohm coupled line performance was compared to three coupled lines with track widths of 1.39 mm, 1.30 mm, and 1.25 mm, respectively, all at a fixed distance between the tracks. These decreasing widths were used to achieve the same 50 Ohm impedance for the coupled lines when covered with different coating layers. Each of these three coupled lines was covered with different coating (stiffener) layers, measuring 0.1 mm, 0.3 mm, and 0.5 mm in thickness, respectively. The manufactured device under test (DUT) structures underwent time-domain reflectometry (TDR) and S-parameter measurements. The TDR measurements of the DUT structures with coating layers demonstrated excellent conformity to the 50 Ohm reference coupled line. Meanwhile, the S21 measurements indicated a significant decrease in the crosstalk. For example, for a coating layer thickness of 0.3 mm, the crosstalk decreased by approximately 5–6 dB within the frequency range up to 5 GHz. When the coating layer thickness was 0.5 mm, the crosstalk decreased by approximately 10 dB or more. [ABSTRACT FROM AUTHOR]

Memristor-based design has gained significant attention in recent years due to its potential to revolutionize various fields such as artificial intelligence, neuromorphic computing, non-volatile memory, signal processing, filtering, and radio frequency design. These emerging devices offer unique advantages such as non-volatile memory, low power consumption, and a high integration density. Their scalability and compatibility with existing fabrication processes make them an attractive option for industry adoption, paving the way for faster and more efficient architecture design. Researchers are actively exploring ways to optimize memristor technology for practical applications to harness its full potential. This includes developing novel materials and structures as well as improving the reliability and performance of memristors in various applications. This paper provides a comprehensive overview of the current advancements in memristor technology and their potential impact on the design of future electronic systems, focusing on its applications in the analog domain. By exploring the latest research and development in this field, researchers can gain valuable insights into how analog memristors can be integrated into their designs to achieve enhanced performance and efficiency. The paper delves into the fundamental principles of memristor technology, exploring its unique characteristics and advantages over traditional electronic components. It discusses the potential impact of memristors and challenges in the analog field of electronics, and highlights the progress made in their integration with existing circuitry, enabling novel functionalities and improved performance. Furthermore, it highlights ongoing research efforts to improve the performance and reliability of memristors, as well as the potential limitations and challenges that need to be addressed for widespread adoption, including variability in performance and reliability. [ABSTRACT FROM AUTHOR]

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A satellite internet provider (e.g., Starlink, OneWeb, O3b mPOWR), despite possessing the capability to provide internet services to on-ground users in a global scale, can dramatically change the way space missions are designed and operated in the foreseeable future. Assuming a scenario where space mission satellites can access the internet via a space internet system, the satellite can be connected to the network permanently (24 × 7) and act as mere terminal independently from its location. The ability to communicate with the satellite on-demand has the potential to improve aspects such as real-time tasking, outage minimization, operation cost, and dependency on the ground. This paper performs a feasibility study on the concept of connecting space missions to the network through commercial mega-constellations. This study includes a review of existing and near-future space internet systems, identification of candidate space missions for the aforementioned concept, a necessary adaptation of existing Commercial off-the-shelf (COTS) terminals to be plugged into space mission satellites, assessment of communication performance, and investigation of the legal aspects of the radio frequency (RF) spectrum usage. The paper evidences that the concept is practically possible to implement in the near future. Among the studied space internet systems (i.e., Starlink, OneWeb, O3b mPOWER), O3b mPOWER stands out as the most suitable system allowing permanent coverage of low earth orbit (LEO) space missions with data rates that can reach up to 21 Mbps per satellite. Although the concept is very promising and can be implemented in the near future, our investigations show that some regulatory aspects regarding the RF usage should be solved for future exploitation of connecting space missions through NGSO (Non-Geostationary Satellite Orbit) constellations. [ABSTRACT FROM AUTHOR]

In recent years, considerable and valuable research progress has been made in indoor positioning technologies based on WLAN Radio Frequency (RF) fingerprinting, identifying it as one of the most promising positioning technologies with substantial potential for wider adoption. However, indoor environmental factors significantly influence the propagation of wireless RF signals, resulting in a considerable decrease in positioning accuracy as the indoor environmental conditions vary. Thus, effectively mitigating the impact of indoor environmental factors on WLAN RF fingerprinting-based positioning systems has become a crucial research problem. Currently, there is a dearth of comprehensive research on the influence of indoor climatic factors, particularly the variations in relative humidity, on the propagation of WLAN RF signals within indoor spaces and its consequential impact on positioning accuracy. To address the aforementioned issues, this paper proposes an Adaptive expansion fingerprint database (AeFd) model based on a regression learning algorithm. The AeFd, through the design of a relationship model describing the interaction between fingerprint databases under varying relative humidity, allows the fingerprint database expanded by AeFd to dynamically adapt to the changes in indoor relative humidity. Our experiments show that using the AeFd model with the KNN algorithm, a 5% performance improvement was observed over 10 days and an 8% improvement over 10 months. According to experimental test results, the fingerprint database expansion model AeFd proposed in this paper can effectively expand the fingerprint database under different relative humidity levels, thereby significantly enhancing the positioning performance of the system and improving its stability. [ABSTRACT FROM AUTHOR]

In this paper, two improved ultra-wideband (UWB) balanced power amplifiers based on the flip-chip system-in-package technique and electronic design automation (EDA) are proposed. The conventional approach to system-on-chip (SoC) involves integrating all sub-circuit designs into a single manufacturing process. However, in radio frequency circuits, adopting the SoC approach necessitates intricate matching designs, leading to an increase in development costs. In this study, two types of SiGe unit power amplifiers attempted to achieve a flat S21 response using simpler matching for input/output. The cascode architecture was adopted as the main structure for the first type of unit power amplifier (type I). Subsequently, the design of the second type unit power amplifier was built upon the foundation of the first type, with the only difference being the implementation of two parallel cascode structures (type II), and the primary goal is to enhance both gain and output power compared to the first type. In addition, for this second type unit power amplifier, in conjunction with a quadrature hybrid coupler, the optimal impedance matching value was selected to maintain the flatness of gain across the entire UWB range. Furthermore, the poor performance of S11,22 of these two types of unit power amplifiers was improved by using quadrature hybrid couplers using the WIPD process combined with EDA simulation. Therefore, using flip-chip packaging technology can effectively reduce the increased wafer fabrication costs caused by complex matching designs in active circuits. This improved system has the potential to offer a new practical application for UWB power amplifier design. [ABSTRACT FROM AUTHOR]

Near-field (NF) integrated sensing and communication (ISAC) has the potential to revolutionize future wireless networks. It enables simultaneous communication and sensing operations on the same radio frequency (RF) resources using a shared hardware platform, maximizing resource utilization. NF-ISAC systems can improve communication and sensing performance compared to traditional far-field (FF) ISAC systems by exploiting the unique propagation characteristics of NF spherical waves with an additional distance dimension. Despite its potential, NF-ISAC research is still in its early stages, and a comprehensive survey of the technology is lacking. This paper systematically explores NF-ISAC technology, providing an in-depth analysis of both NF and FF systems, their applicability in various scenarios, and different channel models. It highlights the advantages and philosophies of ISAC, examining both narrow-band and wide-band NF-ISAC systems. Case studies and simulations offer deeper insights into NF-ISAC design philosophies. Additionally, the paper reviews the existing NF-ISAC literature, methodologies, potentials, and conclusions, and discusses future research areas, challenges, and applications. [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]