Search Results (309)

To meet the need for global coverage, space–air–ground integrated networks (SAGINs) are crucial, but the openness of wireless links makes communications vulnerable to eavesdropping. This paper investigates the physical layer security (PLS) of uplink transmissions in a cooperative dual-hop SAGIN. The system comprises a ground source with a directional antenna, an unmanned aerial vehicle (UAV) relay cluster, and a low Earth orbit (LEO) satellite. Utilizing stochastic geometry, we model the spatial randomness of terrestrial eavesdroppers and the multi-layered dual-orbital LEO destination. To combat mixed radio-frequency (RF) and free-space optical (FSO) fading, multiple relay selection and maximum ratio combining (MRC) are integrated into the UAV cluster. We analytically derive the piecewise probability density function for the FSO link distance, obtaining exact closed-form expressions for the end-to-end secrecy outage probability (SOP). Monte Carlo simulations strictly validate the derivations. The results demonstrate that while increasing available relays and antennas enhances PLS via spatial diversity, a security bottleneck restricts the RF-FSO architecture under high-transmit power regimes, generating asymptotic secrecy floors. These findings provide explicit theoretical guidelines for the secure design and parameter optimization of future SAGINs. Full article

To meet the energy-saving requirements of user equipment (UE) operating in Radio Resource Control idle/inactive states (RRC_IDLE/RRC_INACTIVE) in the 3rd-Generation Partnership Project (3GPP) 5G-Advanced (5G-A) networks, the New Radio (NR) downlink paging procedure relies on periodic monitoring and frequent synchronization signal block (SSB) measurements, which wastes energy when no paging arrivals occur. Meanwhile, heterogeneous Quality of Service (QoS) constraints make it difficult for fixed-parameter Idle Discontinuous Reception and Paging Early Indication mechanisms (IDRX/PEI) to balance energy, delay, and reliability. This paper develops a UAV-assisted 5G-A paging control framework that maps services into multiple QoS classes and models QoS violation risk and system energy consumption under unified accounting, including UE monitoring/reception energy and unmanned aerial vehicle (UAV) forwarding energy. We then propose a QoS-aware risk-driven paging strategy: an offline Long Short-Term Memory (LSTM) predictor is trained to estimate the time-to-next-arrival (TTNA) of paging events and produce a bounded urgency/risk signal to initialize class-dependent thresholds, while online triggering and QoS-feedback-based threshold adaptation regulate the empirical violation rate toward target constraints under varying loads, enabling a controllable energy–delay trade-off. A simulation-based evaluation is conducted to compare the proposed method with representative baselines (Enhanced Paging Monitoring (EPM), Split Paging Occasion (SPOP), and Predicted Paging Early Indication (PPEI)) and to examine the impact of SSB overhead and UAV relaying on the energy–delay–reliability trade-offs. Full article

This paper examines the secrecy performance of a decode-and-forward (DF) relay-assisted device-to-device (D2D) communication system operating over Terahertz (THz) channels in multi-cluster two-wave (MTW) fading environments. Eavesdroppers are located near the relay and the receiver, intercepting their respective signals. Co-channel interference (CCI) affecting the relay, receiver, and eavesdroppers is also considered. To counter fading, both the relay and the receiver employ Maximal Ratio Combining (MRC). The analysis uses a characteristic function (CF)-based approach to derive key secrecy metrics, such as secrecy outage probability, secrecy success probability, the probability of strictly positive secrecy capacity, and intercept probability. The derived expressions are dependent on the characteristics of the THz, MTW fading, and CCI parameters. Finally, the system’s performance is then evaluated numerically for a range of channel and interference parameters. Full article

This paper presents the design and experimental validation of a hardware-enforced charging profile selection framework for low-voltage electric all-terrain vehicles (ATVs), implemented on a programmable Delta battery charger operating within a voltage range of 0–120 V and a current range of 0–30 A. Unlike conventional programmable chargers that rely primarily on software-defined configuration or battery management system (BMS)-negotiated parameter setting, the proposed system enforces predefined constant-current–constant-voltage (CC–CV) charging profiles at the hardware execution layer. Vehicle identification is performed using CANopen-based identifiers, while relay-based selection, controlled via Modbus RTU, physically routes the charger output to fixed CC–CV control paths, thereby structurally reducing the risk of misconfiguration and unintended parameter changes. The system integrates layered control using embedded ESP32 nodes, a redPLC supervisory controller, and NodeRED-based orchestration, combined with real-time measurement, logging, and visualization using a time-series database and Grafana dashboards. Experimental validation is conducted using lithium-ion battery packs configured at four nominal voltage levels (24 V, 48 V, 60 V, and 72 V). The results confirm correct automatic profile selection, deterministic relay-based routing, and stable CC–CV charging behavior across repeated charging sessions. Rather than proposing a new charging algorithm, this work contributes a safety-by-design execution-layer charging architecture that complements higher-level smart charging and management protocols and is particularly suited for closed, heterogeneous fleet environments where deterministic behavior, robustness against configuration errors, and transparent verification of charging processes are critical. Full article

In this paper, the performance of a conventional distance protection relay employing a single ground compensation factor (k₀) per protection zone is investigated for non-uniform transmission lines consisting of mixed overhead line and underground cable sections. In such composite lines, the use of a single k₀ value may lead to inaccurate apparent impedance calculation during phase-to-ground faults due to significant differences in zero- and positive-sequence parameters among line sections. To address this limitation, a novel ground distance protection algorithm is proposed, which applies separate ground compensation factors corresponding to individual line sections within the same distance protection zone. The proposed algorithm dynamically identifies the faulted line section based on the measured reactance and selects the appropriate compensation factor accordingly. A three-section composite transmission line model is developed in the ATP–EMTP environment, including overhead and cable segments with different electrical characteristics. Phase-to-ground faults are simulated at various locations along each line section, and the apparent impedances calculated using the proposed algorithm are quantitatively compared with those obtained from the classical ground distance protection algorithm. Simulation results demonstrate that, under resistive fault conditions (Rarc = 1 Ω), the proposed method reduces impedance magnitude estimation errors from over 23% to below 7%, while maintaining comparable or improved angle estimation accuracy across the protected zone. Although the proposed algorithm introduces an additional computational step due to the selection of appropriate ground compensation factors for individual line sections, this aspect has not been evaluated under real-time conditions and is left for future implementation-oriented studies. Overall, the proposed approach offers a practical and effective solution for improving ground distance protection performance in non-uniform transmission lines. Full article

In this paper, the performance of dual-hop relay transmission in modern wireless communication systems is analyzed by considering two fundamental relaying techniques, namely, Amplify-and-Forward (AF) and Decode-and-Forward (DF). The propagation conditions on the source–relay (S-R) and relay–destination (R-D) links are modeled using the κ-μ statistical distribution, which effectively captures the fading characteristics in both line-of-sight (LoS) and non-line-of-sight (NLoS) environments. The analysis focuses on key performance metrics, including the outage probability (P_out) and average bit error probability (P_e), for Binary Phase Shift Keying (BPSK) and Quadrature Phase Shift Keying (QPSK) modulation schemes, assuming transmission via a single relay without a direct S–D link. Closed-form expressions for the considered metrics are derived based on the κ-μ model and verified by numerical evaluation. In addition to classical analytical modeling, a Generative Artificial Intelligence (GenAI)-enabled workflow is incorporated as a supportive tool in order to aid in automated analysis, the interpretation of the results in the context of network management under varying channel and system parameters based on the P_out and P_e calculations with the aim to tackle the underlying complexity and cognitive load of infrastructure adaptation and re-configuration operations. The combined analytical and GenAI-assisted approach provides valuable insights for the optimization, design, and continuous evolution of robust relay-based architectures in next-generation wireless networks. Full article

This paper proposes the development of an IEC 61850-compliant platform that is readily programmable and deployable for future digital twin applications. Given the compatibility between IEC-61850 and digital twin concepts, a focused case study was conducted involving the robust development of a Raspberry Pi platform with protection relay functionality using the open-source libIEC61850 library. Leveraging IEC-61850’s object-oriented data modelling, the relay can be represented by fully consistent virtual and physical models, providing an essential foundation for accurate digital twin instantiation. The relay implementation supports high-speed Sampled Value (SV) subscription, real-time RMS calculations, IEC Standard Inverse overcurrent trip behaviour according to IEC-60255, and Generic Object-Oriented Substation Event (GOOSE) publishing. Further integration includes setting group functionality for dynamic parameter switching, report control blocks for MMS client–server monitoring, and GOOSE subscription to simulate backup relay protection behaviour with peer trip messages. A staged development methodology was used to iteratively develop features from simple to complex. At the end of each stage, the functionality of the added features was verified before proceeding to the next stage. The integration of the Raspberry Pi into Curtin’s IEC = 61,850 digital substation was undertaken to verify interoperability between IEDs, a key outcome relevant to large-scale digital twin systems. The experimental results confirm GOOSE transmission times below 4 ms, tight adherence to trip-time curves, and performance under higher network traffic. Such measured RMS and trip-time errors fall well within industry and IEC limits, confirming the reliability of the relay logic. The takeaways from this case study establish a high-performing, standardised foundation for a digital twin system that requires fast, bidirectional communication between a virtual and a physical system. Full article

Ground-based full-physical experiments for space rendezvous and docking serve as a critical step in verifying the reliability of docking technology. The high-precision active attitude setting of spacecraft simulators represents a key technology for ground-based full-physical experiments. In order to satisfy the requirement for high-precision attitude control in these experiments, this paper proposes an enhanced method based on auto disturbance rejection control (ADRC). This paper addresses the limitations of traditional deadband–hysteresis relay controllers, which exhibit low steady-state accuracy and insufficient disturbance rejection capability. This approach employs a nonlinear extended state observer (NESO) to estimate and compensate for total system disturbances in real time. Concurrently, it incorporates an adaptive mechanism for deadband and hysteresis parameters, dynamically adjusting controller parameters based on disturbance estimates and attitude errors. This overcomes the trade-off between accuracy and power consumption that is inherent in fixed-parameter controllers. Furthermore, the method incorporates a nonlinear tracking differentiator (NTD) to schedule transitions, enabling rapid attitude settling without overshoot. The stability analysis demonstrates that the proposed controller achieves local asymptotic stability and global uniformly bounded convergence. The simulation results demonstrate that under three typical operating conditions (conventional attitude setting, pre-separation connector stabilisation, and docking initial condition establishment), the steady-state attitude error remains within ±0.01°, with convergence times under 3 s and no overshoot. These results closely match ground test data. This approach has been demonstrated to enhance the engineering applicability of the control system while ensuring high precision and robust performance. Full article

The broadcast nature of wireless channels introduces significant security vulnerabilities in information transmission, particularly when the eavesdropper is close to the legitimate destination. In such scenarios, the eavesdropping channel often exhibits high spatial correlation with, or even superior quality to, the legitimate channel. This makes it challenging for traditional power optimization methods to effectively suppress the eavesdropping rate. To address this challenge, this paper proposes an optimization method for the secrecy capacity of unmanned aerial vehicle (UAV) relaying based on the dynamic adjustment of the power allocation factor. By injecting artificial noise (AN) during signal forwarding and combining it with real-time channel state information, the power allocation factor can be dynamically adjusted to achieve precise jamming of the eavesdropping link. We consider a four-node communication model consisting of a source, a UAV, a legitimate destination, and a passive eavesdropper, and formulate a joint optimization problem to maximize the secrecy rate. Due to the non-convexity of the original problem, we introduce relaxation variables and apply successive convex approximation (SCA) to reformulate it into an equivalent convex optimization problem. An analytical solution for the power allocation factor is derived using the water-filling (WF) algorithm. Furthermore, an alternating iterative optimization algorithm with AN assistance is proposed to achieve global optimization of the system parameters. Simulation results demonstrate that, compared to traditional power optimization schemes, the proposed algorithm substantially suppresses the eavesdropping channel capacity while enhancing transmission efficiency, thereby significantly improving both secrecy performance and overall communication reliability. Full article

The Ulva prolifera green tide in the South Yellow Sea has erupted annually for many years, posing significant threats to coastal ecology, the economy, and society. While environmental factors are widely acknowledged as prerequisites for these outbreaks, the asynchrony and complex coupling between their variations and disaster events have challenged traditional studies that rely on instantaneous correlations to uncover the underlying dynamic mechanisms. This study focuses on the Ulva prolifera disaster in the South Yellow Sea, systematically analyzing its spatiotemporal distribution patterns, the temporal accumulation and lag effects of environmental factors, and the coupled driving mechanisms using the Floating Algae Index (FAI). The results indicate that: (1) The disaster shows significant interannual variability, with 2019 experiencing the most severe outbreak. Monthly, the disaster begins offshore of Jiangsu in May, moves northward and peaks in June, expands northward with reduced scale in July, and largely dissipates in August. Years with large-scale outbreaks exhibit higher distribution frequency and broader spatial extent. (2) Environmental factors demonstrate significant accumulation and lag effects on Ulva prolifera disasters, with a mixed temporal mode of both accumulation and lag effects being dominant. Temporal parameters vary across different factors—nutrients generally have longer lag times, while light and temperature factors show longer accumulation times. These parameters change dynamically across disaster stages and display a clear inshore–offshore gradient, with shorter effects in coastal areas and longer durations in offshore waters, revealing significant spatiotemporal heterogeneity in temporal response patterns. (3) The driving mechanism of Ulva prolifera disasters follows a “nutrient-dominated, temporally relayed” pattern. Nutrient accumulation (PO₄, NO₃, SI) from the previous autumn and winter serves as the decisive factor, explaining 86.8% of interannual variation in disaster scale and 56.1% of the variation in first outbreak timing. Light and heat conditions play a secondary modulating role. A clear temporal relay occurs through three distinct stages: the initial outbreak triggered by nutrients, the peak outbreak governed by light–temperature–nutrient synergy, and the system decline characterized by the dissipation of all driving forces. These findings provide a mechanistic basis for developing predictive models and targeted control strategies. Full article

In this paper, we propose a two-way hybrid satellite–terrestrial relay scheme employing Fountain codes (FCs). In the proposed model, a satellite and a ground user exchange data through a group of terrestrial relay stations, in the presence of an eavesdropper. In the first phase, the satellite and the ground user simultaneously transmit their encoded packets to the relay stations. The relay stations then apply a successive interference cancelation (SIC) technique to decode the received packets. To reduce the quality of the eavesdropping links, a cooperative jammer is employed to transmit jamming signals toward the eavesdropper during the first phase. Next, one of the relay stations which can successfully decode the encoded packets from both the satellite and the ground user is selected for data forwarding, by using a partial relay selection method. Then, this selected relay performs an XOR operation on the two encoded packets, and then broadcasts the XOR-ed packet to both the satellite and the user in the second phase. We derive exact closed-form expressions of outage probability (OP), system outage probability (SOP), intercept probability (IP), and system intercept probability (SIP), and realize simulations to validate these expressions. This paper also studies the trade-off between OP (SOP) and IP (SIP), as well as the impact of various system parameters on the performance of the proposed scheme. Full article

The integration of low Earth orbit (LEO) satellites and unmanned aerial vehicles (UAVs) into the maritime Internet of Things (MIoT) offers an effective solution to overcoming the limitations of connectivity and transmission reliability in conventional MIoT, thereby supporting marine data acquisition. However, the highly dynamic ocean environment necessitates a theoretical framework for system-level performance evaluation before practical deployment. In this article, we consider a LEO satellite and UAV-assisted MIoT (LSU-MIoT) network and develop an analytical framework to evaluate its transmission performance. Specifically, marine devices and relaying buoys are modeled as a Matérn cluster process on the sea surface, UAVs as a homogeneous Poisson point process, and LEO satellites as a spherical Poisson point process. Signal transmissions over marine, aerial, and space links are characterized by Nakagami-m, Rician, and shadowed Rician fading, respectively, with the two-ray path loss model applied to sea and air links for accurately capturing propagation characteristics. By leveraging stochastic geometry, we derive analytical expressions for transmission success probability and end-to-end delay of regular and emergency data under the time division multiple access and non-orthogonal multiple access schemes. Simulation results validate the accuracy of derived expressions and reveal the impact of key parameters on the performance of LSU-MIoT networks. Full article

Fault diagnosis of railway signal relays is crucial for the operational safety and efficiency of railway systems. With the continuous advancement of deep learning techniques in various applications, voiceprint-based fault diagnosis has emerged as a research hotspot, facilitating the transition from failure-based repair to condition-based maintenance. However, this approach still faces challenges such as the limited feature extraction capability of single voiceprint features and poor discriminability when features are highly concentrated. To address these issues, this paper proposes a voiceprint-based fault diagnosis method for railway signal relays that utilizes a Gaussian–Laplacian pyramid fusion rule and an improved Swin Transformer. The enhanced Swin Transformer integrates the original architecture with a saliency feature map as a masking strategy. Experimental results demonstrate that the proposed method, based on the Gaussian–Laplacian pyramid fusion rule and the improved Swin Transformer, reduces the number of parameters by 54.8% compared to the Vision Transformer while the accuracy is almost same. Full article

Recent space exploration roadmaps from China, the United States, and Russia highlight the establishment of Mars bases as a major objective. Future deep-space missions will span the inner solar system and extend beyond the asteroid belt, demanding network control systems that sustain reliable communication and efficient scheduling across vast distances. Current centralized or regionalized technologies, such as the Deep-Space Network and planetary relay constellations, are limited by long delays, sparse visibility, and heterogeneous onboard resources, and thus cannot meet these demands. To address these challenges, we propose a dual-center architecture, DualSynNet, anchored at Earth and Mars and enhanced by Lagrange-point relays and a minimal heliocentric constellation to provide scalable multi-mission coverage. On this basis, we develop a federated multi-agent reinforcement learning framework with graph attention (Fed-GAT-MADDPG), integrating centralized critics, decentralized actors, and interplanetary parameter synchronization for adaptive, resource-aware scheduling. A unified metric system: Reachability, Rapidity, and Availability, is introduced to evaluate connectivity, latency, and resource sustainability. Simulation results demonstrate that our method increases task completion to 52.4%, reduces deadline expiration, constrains rover low-state-of-charge exposure to approximately 0.8%, and maintains consistently high hardware reliability across rover and satellite nodes. End-to-end latency is reduced, with a shorter tail distribution due to fewer prolonged buffering or stagnation periods. Ablation studies confirm the essential role of graph attention, as removing it reduces completion and raises expiration. These results indicate that the integration of a dual-center architecture with federated graph reinforcement learning yields a robust, scalable, and resource-efficient framework suitable for next-generation interplanetary exploration. Full article

During system faults, power electronic converters in modern sustainable power systems activate low-voltage ride-through (LVRT) control strategies, which introduce second harmonic current into the power system. For transformer protection, the conventional inrush current identification method based on second harmonic current fails to adapt to the high harmonic conditions of electronic power-based sources in renewable energy systems. This paper proposes an identification scheme based on a modified MobileNetV4 (MNv4) architecture and multi-source electrical quantities. The experimental dataset is constructed through PSCAD simulation and engineering field data. The input feature combination including three-phase voltage, current and differential current is designed, which solves the defects of single feature in traditional methods. Experiments show that the MNv4 model delivers competitive performance in terms of accuracy and recall, while featuring a small number of parameters that make it suitable for resource-constrained embedded deployment. This research provides theoretical support and data paradigm for the engineering application of artificial intelligence in the field of relay protection. Full article