Search Results (1,396)

The proliferation of low-cost, small radar cross-section UAVs (unmanned aerial vehicles) necessitates innovative solutions for countering them. Since these UAVs typically operate with a radio control link, a promising defense technique involves passive scanning of the radio frequency (RF) spectrum to detect UAV control signals. This approach is enhanced when integrated with machine-learning (ML) and deep-learning (DL) methods. Currently, this field is actively researched, with various studies proposing different ML/DL architectures competing for optimal accuracy. However, there is a notable gap regarding robustness, which refers to a UAV detector’s ability to maintain high accuracy across diverse scenarios, rather than excelling in just one specific test scenario and failing in others. This aspect is critical, as inaccuracies in UAV detection could lead to severe consequences. In this work, we introduce a new dataset specifically designed to test for robustness. Instead of the existing approach of extracting the test data from the same pool as the training data, we allowed for multiple categories of test data based on channel conditions. Utilizing existing UAV detectors, we found that although coefficient classifiers have outperformed CNNs in previous works, our findings indicate that image classifiers exhibit approximately 40% greater robustness than coefficient classifiers under low signal-to-noise ratio (SNR) conditions. Specifically, the CNN classifier demonstrated sustained accuracy in various RF channel conditions not included in the training set, whereas the coefficient classifier exhibited partial or complete failure depending on channel characteristics. Full article

Mobile communication is ubiquitous in everyday life. The fifth generation of mobile networks (5G) introduced 5G New Radio as a radio access technology that meets current bandwidth, quality, and application requirements. Network steganographic channels that hide secret message transfers in an innocent carrier communication are a particular threat in mobile communications as these channels are often used for malware, ransomware, and data leakage. We systematically analyze the protocol stack of the 5G–air interface for its susceptibility to network steganography, addressing both storage and timing channels. To ensure large coverage, we apply hiding patterns that collect the essential ideas used to create steganographic channels. Based on the results of this analysis, we design and implement a network covert storage channel, exploiting reserved bits in the header of the Packet Data Convergence Protocol (PDCP). the covert sender and receiver are located in a 5G base station and mobile device, respectively. Furthermore, we sketch a timing channel based on a recent overshadowing attack. We evaluate our steganographic storage channel both in simulation and real-world experiments with respect to steganographic bandwidth, robustness, and stealthiness. Moreover, we discuss countermeasures. Our implementation demonstrates the feasibility of a covert channel in 5G New Radio and the possibility of achieving large steganographic bandwidth for broadband transmissions. We also demonstrate that the detection of the channel by a network analyzer is possible, limiting its scope to application scenarios where operators are unaware or ignorant of this threat. Full article

Drones integrated with 5G New Radio (NR) base stations have emerged as a promising solution for efficient victim search and localization in emergency zones where cellular networks are disrupted by natural disasters. Traditional approaches relying solely on uplink Sounding Reference Signal (SRS) for localization face limitations due to User Equipment (UE) power constraints. To overcome this, our paper introduces BWSAR, a novel three-stage Search-and-Rescue (SAR) methodology leveraging 5G-NR beam sweeping technologies. BWSAR utilizes downlink Synchronization Signal Block (SSB) for coarse-grained direction estimation, guiding the drone towards potential victim locations. Subsequently, finer-grained beam sweeping with Positioning Reference Signal (PRS) is employed within the identified direction, enabling precise three-dimensional UE coordinate estimation. Furthermore, we propose a trajectory optimization algorithm to expedite the drone’s navigation to emergency areas. Simulation results underscore BWSAR’s efficacy in reducing positioning errors and completing SAR missions swiftly, within minutes. Full article

Background: Transactivation Response Element RNA-binding Protein (TRBP2) is a double-stranded RNA-binding protein widely known for its critical contribution to RNA interference (RNAi), a conserved mechanism of gene-expression regulation mediated through small non-coding RNA moieties (ncRNAs). Nevertheless, TRBP2 has also proved to be involved in other molecular pathways and biological processes, such as cell growth, organism development, spermatogenesis, and stress response. Mutations or aberrant expression of TRBP2 have been previously associated with diverse human pathologies, including Alzheimer’s disease, cardiomyopathy, and cancer, with TRBP2 playing an essential role(s) in proliferation, invasion, and metastasis of tumor cells. Methods: Hence, the present study aims to investigate, via employment of advanced flow cytometry, immunofluorescence, cell transgenesis and bioinformatics technologies, new, still elusive, functions and properties of TRBP2, particularly regarding its cell cycle-specific control during cancer cell division. Results: We have identified a novel, mitosis-dependent regulation of TRBP2 protein expression, as clearly evidenced by the lack of its immunofluorescence-facilitated detection during mitotic phases, in several human cancer cell lines of different tissue origin. Notably, the obtained TRBP2-downregulation patterns seem to derive from molecular mechanisms that act independently of oncogenic activities (e.g., malignancy grade), metastatic capacities (e.g., low versus high), and mutational signatures (e.g., p53^−/− or p53^ΔΥ126) of cancer cells. Conclusions: Taken together, we herein propose that TRBP2 serves as a novel cell cycle-dependent regulator, likely exerting mitosis-suppression functions, and, thus, its mitosis-specific downregulation can hold strong promise to be exploited for the efficient and successful prognosis, diagnosis, and (radio-/chemo-)therapy of diverse human malignancies, in the clinic. Full article

As a new, safe, and efficient method, Atmospheric-Pressure Room-Temperature Plasma (ARTP) mutagenesis has been widely applied in the field of microbial breeding and industrial applications, but it is rarely used in fish. In this study, ARTP mutagenesis technology was applied for the first time to a common carp strain, Songpu mirror carp (Cyprinus carpio L.), to increase genetic variation in this species. The appropriate experimental conditions were determined to include a radio frequency output power of 160 W and the processing of fertilized eggs for 360 s. The ARTP treatment group had a lower survival rate than the control group. The CV of morphological characters in the ARTP treatment group was significantly higher than that in the control group, and the CV of body weight was the highest (p < 0.05). In addition, the deformity rate in the ARTP treatment group was significantly higher than in the control group (p < 0.05). Individuals with high weight and no deformities were screened within the selection pressure of 1:15 of ARTP treatment group and fed in the same pool with the control group of the same age. The measurement of serum indices showed that, in the ARTP treatment group, TP, ALP, ALB, T-CHO, LDL levels were significantly higher than those in the control group (p < 0.05). Furthermore, the relative expressions of SOD, growth-related genes GH, IGF-I, protein synthesis-related genes TOR and 4EBP1 were significantly higher in the ARTP treatment group than in the control group (p < 0.05). In summary, Songpu mirror carp subjected to ARTP treatment showed a higher growth potential and antioxidant capacity. Full article

The JamSail mission is an educational CubeSat aiming to design, develop, and demonstrate two new technologies on a small satellite, tentatively scheduled for launch no earlier than 2026. When launched, JamSail will demonstrate the functionality of two new payloads in low Earth orbit. First, a flexible, low-cost GNSS interference detection payload capable of characterising and geolocating the sources of radio interference regarding the E1/L1 and E5a/L5 bands will be demonstrated on a global scale. The data produced by this payload can be used to target anti-interference actions in specific regions and aid in the design of future GNSS receivers to better mitigate specific types of interference. If successful, the flexibility of the payload will allow it to be remotely reconfigured in orbit to investigate additional uses of the technology, including a potential demonstration of GNSS reflectometry aboard a CubeSat. Second, a compact refractive solar sail will be deployed that is capable of adjusting the orbit of JamSail in the absence of an on-board propellant. This sail will be used to gradually raise the semi-major axis of JamSail over the span of the mission before being used to perform rapid passive deorbit near the end-of-life juncture. Additionally, self-stabilising optical elements within the sail will be used to demonstrate a novel method of performing attitude control. JamSail is currently in the testing phase, and the payloads will continue to be refined until the end of 2024. This paper discusses the key objectives of the JamSail mission, the design of the payloads, the expected outcomes of the mission, and future opportunities regarding the technologies as a whole. Full article

This work presents a novel fully parallel decoder architecture designed for high-throughput decoding of Quasi-Cyclic Low-Density Parity-Check (QC-LDPC) codes within the context of 5G New-Radio (NR) communication. The design uses the layered Min-Sum (MS) algorithm and focuses on increasing throughput to meet the strict needs of enhanced Mobile BroadBand (eMBB) applications. We incorporated a Sub-Optimal Low-Latency (SOLL) technique to enhance the critical check node processing stage inherent to the MS algorithm. This technique efficiently computes the two minimum values, rendering the architecture well-suited for specific Ultra-Reliable Low-Latency Communication (URLLC) scenarios. We design the decoder to be reconfigurable, enabling efficient operation across all expansion factors. We rigorously validate the decoder’s effectiveness through meticulous bit-error-rate (BER) performance evaluations using Hardware Description Language (HDL) co-simulation. This co-simulation utilizes a well-established suite of tools encompassing MATLAB/Simulink for system modeling and Vivado, a prominent FPGA design suite, for hardware representation. With 380,737 Look-Up Tables (LUTs) and 32,898 registers, the decoder’s implementation on a Virtex-7 XC7VX980T FPGA platform by AMD/Xilinx shows good hardware utilization. The architecture attains a robust operating frequency of 304.5 MHz and a normalized throughput of 49.5 Gbps, marking a 36% enhancement compared to the state-of-the-art. This advancement propels decoding capabilities to meet the demands of high-speed data processing. Full article

This paper aims to propose a novel call for help traffic (SOS) and study its impact over Machine-to-Machine (M2M) and Human-to-Human (H2H) traffic in Internet of Things environments, specifically during disaster events. During such events (e.g., the spread COVID-19), SOS traffic, with its predicted exponential increase, will significantly influence all mobile networks. SOS traffic tends to cause many congestion overload problems that significantly affect the performance of M2M and H2H traffic. In our project, we developed a new Continuous-Time Markov Chain (CTMC) model to analyze and measure radio access performance in terms of massive SOS traffic that influences M2M and H2H traffic. Afterwards, we validate the proposed CTMC model through extensive Monte Carlo simulations. By analyzing the traffic during an emergency case, we can spot a huge impact over the three traffic types of M2M, H2H and SOS traffic. To solve the congestion problems while keeping the SOS traffic without any influence, we propose to grant the SOS traffic the highest priority over the M2M and H2H traffic. However, by implementing this solution in different proposed scenarios, the system becomes able to serve all SOS requests, while only 20% of M2M and H2H traffic could be served in the worst-case scenario. Consequently, we can alleviate the expected shortage of SOS requests during critical events, which might save many humans and rescue them from being isolated. Full article

This paper presents a Doherty power amplifier (DPA) integrated circuit (IC) designed to have enhanced gain, efficiency, and AM-AM characteristics through a dynamic power dividing technique, which can control the power dividing ratio according to the input power. Since this multi-purpose dynamic power dividing network also provides the phase offset and impedance matching at the interstage network needed for appropriate DPA operation, the active IC area could be reduced. To verify the proposed technique and its analysis, the DPA was implemented with a 28 nm bulk CMOS process for the fifth-generation (5G) new radio (NR) millimeter-wave frequency band of 23.5–27.5 GHz. The measured results showed a gain of 20.3–21.9 dB, saturated output power of 14.0–15.2 dBm, power added efficiency (PAE) of 22.8–26.7% at the peak power, and PAE of 14.6–17.6% at the 6 dB output power back-off (OBO). Full article

The rapid evolution of mobile and optical communication technologies is driving the transition from 5G to 6G networks. This transition inevitably brings about changes in authentication scenarios, as new security demands emerge that go beyond the capabilities of existing frameworks. Therefore, it is necessary to address these evolving requirements and the associated key challenges: ensuring Perfect Forward Secrecy (PFS) to protect communications even if long-term keys are compromised and integrating Post-Quantum Cryptography (PQC) techniques to defend against the threats posed by quantum computing. These are essential for both radio and optical communications, which are foundational elements of future 6G infrastructures. The DMRN Protocol, introduced in 2022, represents a major advancement by offering both PFS and PQC while maintaining compatibility with existing 3rd Generation Partnership Project (3GPP) standards. Given the looming quantum-era challenges, it is imperative to analyze the protocol’s security architecture through formal verification. Accordingly, we formally analyze the DMRN Protocol using SVO logic and ProVerif to assess its effectiveness in mitigating attack vectors, such as malicious or compromised serving networks (SNs) and home network (HN) masquerading. Our research found that the DMRN Protocol has vulnerabilities in key areas such as mutual authentication and key exchange. In light of these findings, our study provides critical insights into the design of secure and quantum-safe authentication protocols for the transition to 6G networks. Furthermore, by identifying the vulnerabilities in and discussing countermeasures to address the DMRN Protocol, this study lays the groundwork for the future standardization of secure 6G Authentication and Key Agreement protocols. Full article

The impact of cold atmospheric plasma (CAP) treatment on the enamel of twelve primary teeth (incisors, canines, and molars) collected from six children was examined in order to evaluate the possibility of using the CAP technique in dental applications. A radio-frequency dielectric barrier discharge (DBD) plasma jet operating at a voltage of 3.25 kV using a mixture of helium and oxygen as the working gas was used for the generation of plasma as part of the electro-technological method for the treatment of biological material. The plasma exposure time for the primary teeth was 5, 10, and 20 min. The properties of tooth enamel (color, contact angles, surface roughness, surface topography, elemental composition) were examined before (control) and after the plasma treatment. As shown by the results, the plasma treatment time is a key parameter that can induce desired features, such as whitening or improved wettability. However, with prolonged plasma treatment (20 min), the enamel surface may be permanently damaged. The cold-plasma-treated samples were characterized by a higher value of the brightness L* parameter and thus a lighter color, compared to the CAP-untreated teeth. It was also evidenced that the plasma treatment increased the hydrophilicity of tooth surfaces, and the contact angles effectively decreased with the time of the CAP treatment. The tooth surface also became much more heterogeneous and rough with much greater amplitudes in heights. The surface of the primary teeth after the CAP treatment lost its homogeneity, as evidenced by the SEM micrographs. The analysis of the elemental composition revealed only minor changes after the plasma process, which may suggest that the observed morphological changes in the enamel surface are mainly physical and are not a consequence of chemical reactions between the enamel and the reactive components of the cold plasma. Plasma treatment of teeth opens up new possibilities of using this method as an alternative to whitening or pre-treatment before other dental procedures. Full article

5G New Radio (NR)-V2X, standardized by 3GPP Release 16, includes a distributed resource allocation Mode, known as Mode 2, that allows vehicles to autonomously select transmission resources using either sensing-based semi-persistent scheduling (SB-SPS) or dynamic scheduling (DS). In unmanaged 5G-NR-V2X scenarios, SB-SPS loses effectiveness with aperiodic and variable data. DS, while better for aperiodic traffic, faces challenges due to random selection, particularly in high traffic density scenarios, leading to increased collisions. To address these limitations, this study models the Cellular V2X network as a decentralized multi-agent networked Markov decision process (MDP), where each vehicle agent uses the Shared Experience Actor–Critic (SEAC) technique to optimize performance. The superiority of SEAC over SB-SPS and DS is demonstrated through simulations, showing that the SEAC with an N-step approach achieves an average improvement of approximately 18–20% in enhancing reliability, reducing collisions, and improving resource utilization under high vehicular density scenarios with aperiodic traffic patterns. Full article

With the advancing development of Advanced Air Mobility (AAM), there is a collaborative effort to increase safety in the airspace. AAM is an advancing field of aviation that aims to contribute to the safe transportation of goods and people using aerial vehicles. When aerial vehicles are operating in high-density locations such as urban areas, it can become crucial to incorporate collision avoidance systems. Currently, there are available pilot advisory systems such as Traffic Collision and Avoidance Systems (TCAS) providing assistance to manned aircraft, although there are currently no collision avoidance systems for autonomous flights. Standards Organizations such as the Institute of Electrical and Electronics Engineers (IEEE), Radio Technical Commission for Aeronautics (RTCA), and General Aviation Manufacturers Association (GAMA) are working to develop cooperative autonomous flights using UAS-to-UAS Communication in structured and unstructured airspaces. This paper presents a new approach for collision avoidance strategies within structured airspace known as “digital traffic lights”. The digital traffic lights are deployed over an area of land, controlling all UAVs that enter a potential collision zone and providing specific directions to mitigate a collision in the airspace. This strategy is proven through the results demonstrated through simulation in a Cesium Environment. With the deployment of the system, collision avoidance can be achieved for autonomous flights in all airspaces. Full article

Long-range networks, renowned for their long-range, low-power communication capabilities, form the backbone of many Internet of Things systems, enabling efficient and reliable data transmission. However, detecting tampered frequency signals poses a considerable challenge due to the vulnerability of LoRa devices to radio-frequency interference and signal manipulation, which can undermine both data integrity and security. This paper presents an innovative method for identifying tampered radio frequency transmissions by employing five sophisticated anomaly detection algorithms—Local Outlier Factor, Isolation Forest, Variational Autoencoder, traditional Autoencoder, and Principal Component Analysis within the framework of a LoRa-based Internet of Things network structure. The novelty of this work lies in applying image-based tampered frequency techniques with these algorithms, offering a new perspective on securing LoRa transmissions. We generated a dataset of over 26,000 images derived from real-world experiments with both normal and manipulated frequency signals by splitting video recordings of LoRa transmissions into frames to thoroughly assess the performance of each algorithm. Our results demonstrate that Local Outlier Factor achieved the highest accuracy of 97.78%, followed by Variational Autoencoder, traditional Autoencoder and Principal Component Analysis at 97.27%, and Isolation Forest at 84.49%. These findings highlight the effectiveness of these methods in detecting tampered frequencies, underscoring their potential for enhancing the reliability and security of LoRa networks. Full article

The spatial–temporal sampling errors arising from the differences in geographical locations and measurement times between co-located Global Navigation Satellite System (GNSS) radio occultation (RO) and radiosonde (RS) data represent systematic errors in the three-cornered hat (3CH) method. In this study, we propose a novel spatial–temporal sampling correction method to mitigate the sampling errors associated with both RO–RS and RS–model pairs. We analyze the 3CH processing chain with this new correction method in comparison to traditional approaches, utilizing Fengyun-3E (FY-3E) GNSS Occultation Sounder II (GNOS II) RO data, atmospheric models, and RS datasets from the Hailar and Xisha stations. Overall, the results demonstrate that the improved 3CH method performs better in terms of spatial–temporal sampling errors and the variances of atmospheric parameters, including refractivity, temperature, and specific humidity. Subsequently, we assess the error variances of the FY-3E GNOS II RO, RS and model atmospheric parameters in China, in particular the northern China and southern China regions, based on large ensemble datasets using the improved 3CH data processing chain. The results indicate that the FY-3E GNOS II BeiDou navigation satellite system (BDS) RO and Global Positioning System (GPS) RO show good consistency, with the average error variances of refractivity, temperature, and specific humidity being less than 1.12%², 0.13%², and 700%², respectively. A comparison of the datasets from northern and southern China reveals that the error variances for refractivity are smaller in northern China, while temperature and specific humidity exhibit smaller error variances in southern China, which is attributable to the differing climatic conditions. Full article