Search Results (1,105)

Underwater wireless networking is an emerging field for exploration and monitoring, enabling real-time data transmission and communication with both static sensors and submersibles. Current approaches mostly focus on utilizing acoustic waves. The use of optics for this purpose has been known to have several implementation challenges that have prevented it from being considered as a universal alternative. This study proposes that utilizing optics in an adaptive relay wireless network configuration can overcome its primary limitation of line-of-sight (LOS) propagation. In this paper, a network of strategically placed sensors is experimentally constructed with the ability to read and send modulated blue light, fit for extended submersion in water. This proposal represents a hypothetical aquatic drone swarm that is developed and programmed to follow adaptive relay logic. This network is able to demonstrate adaptation to obstructions in the LOS and maintain communication through configurations in which the sender and intended recipient would otherwise be unable to directly communicate. This finding allows the advantages of optical communications to be further explored for aquatic applications, primarily its higher potential data rate, which is inherently productive to a swarm. 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

The increasing variety in last-mile delivery demands requires diverse vehicle-drone collaboration models to meet various scenarios. Meanwhile, growing environmental concerns demand that we optimize not just delivery efficiency but also sustainability. This study thus proposes a unified multi-mode framework for collaborative multi-vehicle, multi-drone delivery networks to enable fair model comparisons. We introduce a hybrid metaheuristic algorithm combining NSGA-II and VND using specialized encoding and neighborhood structures to handle complex constraints, thereby comprehensively enhancing both efficiency and sustainability. Experiments on nine benchmark instances across three models reveal a nonlinear trade-off between efficiency and sustainability, with our migratory-relay model consistently outperforming others in terms of the Pareto front across multiple comparisons. Sensitivity analysis shows diminishing returns from adding more drones; while the first drone can cut emissions by up to 23.1%, additional drones bring progressively smaller reductions. These findings provide a strong framework and practical insights for designing sustainable urban logistics systems. Full article

Wireless sensor networks (WSNs) have widespread applications in vital fields, including environmental surveillance, medical care, and smart urban settings. Nevertheless, the restricted battery capacity of sensor nodes renders energy consumption an ongoing hindrance, limiting both the performance and operational lifespan of a network. To mitigate this challenge, this study proposes an enhanced clustering and routing scheme, the Black-Kite Optimization–Time Of Arrival (BKA-TOA) algorithm, which jointly optimizes cluster head selection and data transmission. The proposed BKA-TOA integrates the bio-inspired Black-Kite Optimization (BKA) with relay selection based on the Time of Arrival (TOA) technique. A multidimensional fitness function is constructed by incorporating inter-node distance, energy variance, and cluster head distribution to achieve robust clustering, balanced energy consumption, and improved scalability. Extensive simulations conducted in Matlab R2024a are used to benchmark the proposed algorithm against Particle Swarm Optimization (PSO), Improved Ant Colony–minimum spanning tree (IACO-MST), and Energy-Efficient Uneven Clustering (EEUC). The experimental results indicate that BKA-TOA significantly reduces node mortality, improves residual energy preservation, and prolongs the operational lifetime of WSNs compared with competing algorithms. 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

Verifiable Credentials (VCs) are a core component of decentralized identity systems, enabling individuals to prove claims without centralized intermediaries. However, managing VC revocation across segregated blockchain networks remains a key interoperability challenge. In this paper, we present a bidirectional blockchain bridge that enables the cross-chain verification of VCs between two Ethereum-compatible private blockchain networks: Geth and Besu. The system allows credentials issued and revoked on one chain to be validated from another without duplicating infrastructure or compromising security. Our architecture combines on-chain smart contracts with an off-chain relay, ensuring auditable, low-latency credential checks across chains. Our proposal is validated through an open-source working prototype. It is particularly relevant for domains where independent organizations must validate shared credentials across segregated blockchain infrastructures, including education, healthcare, and governmental identity services. Full article

This paper presents the design, development, and testing of a smart home automation system that integrates a Siemens LOGO! programmable logic controller (PLC) with an ESP32 microcontroller to enable dual-mode control—manual and voice-activated. The system automates essential home functions such as lighting, irrigation, gate control, and ventilation. Through the use of the fauxmoESP library, the ESP32 communicates with Amazon Alexa, converting voice commands into GPIO signals interpreted by the PLC. Manual control is retained via pushbuttons, ensuring operational redundancy in case of network or hardware failure. The system architecture includes optocouplers and relays to ensure voltage compatibility and device protection between the 3.3 V microcontroller and the 12–24 V PLC inputs. Functional tests revealed a 100% success rate in manual operations and over 95% in voice-controlled actions, with notable differences in response times. A cost breakdown and risk analysis are also included to assess feasibility and sustainability. This prototype highlights a practical, low-cost solution for residential automation, with scalability potential for broader smart home applications and educational or industrial implementations. Full article

In 5G cellular networks, end-to-end data transmission delay is a key metric for evaluating network performance. High-frequency signal fading and complex transmission links often lead to increased delays. Pinching-antenna optimizes signal propagation through directional transmission, enhancing signal quality and reducing delay. Therefore, this paper analyzes the end-to-end transmission delay performance of 5G cellular networks assisted by pinching-antenna. Specifically, the data transmission process is modeled as a two-hop link, where data is first transmitted from the base station to the relay station (RS) via a 5G high-frequency transmission link, and then from the RS to the user equipment via a dielectric waveguide-based pinching-antenna link. We derive the statistical characteristics of the service processes for both the 5G high-frequency transmission link and the dielectric waveguide link. Considering traffic arrivals and service capabilities, we then precisely define the network’s end-to-end delay using stochastic network calculus. Through numerical experiments, we initially evaluate the impact of various network parameters on the performance upper bound and provide system performance. The experimental results show that the pinching-antenna-assisted 5G cellular network significantly reduces end-to-end delay compared with the traditional decode and forward relay, further confirming the substantial advantage of pinching-antenna in optimizing delay performance. Full article

Heterogeneous unmanned aerial vehicle (UAV) swarms are becoming critical components of next-generation non-terrestrial networks, enabling tasks such as communication relay, spectrum monitoring, cooperative sensing, and navigation. Yet, their heterogeneity and multifunctionality bring severe challenges in task allocation and resource scheduling, where traditional multi-agent reinforcement learning methods often suffer from high algorithmic complexity, lengthy training times, and deployment difficulties on resource-constrained nodes. To address these issues, this paper proposes a low-complexity multi-agent soft actor–critic (MASAC) framework that combines parameter sharing (shared actor with device embeddings and shared-backbone twin critics), lightweight network design (fixed-width residual MLP with normalization), and robust training mechanisms (minimum-bias twin-critic updates and entropy scheduling) within the CTDE paradigm. Simulation results show that the proposed framework achieves more than 14-fold parameter compression and over a 93% reduction in training time, while maintaining or improving performance in terms of the delay–energy utility function. These advances substantially reduce computational overhead and accelerate convergence, providing a practical pathway for deploying multi-agent reinforcement learning in large-scale heterogeneous UAV clusters and supporting diverse mission scenarios under stringent resource and latency constraints. Full article

Plastic greenhouses, which account for the majority of protected horticulture facilities in East Asia, are highly susceptible to wind-induced uplift failures that can lead to severe structural and economic damage. To address this issue, this study developed a low-power and low-cost wireless monitoring system applying the concept of structural health monitoring (SHM) to greenhouse foundations. Each sensor node integrates a MEMS-based inertial measurement unit (IMU) for attitude estimation, a LoRa module for long-range alert transmission, and a microSD module for data logging, while a gateway relays anomaly alerts to users through an IP network. Uplift tests were conducted on standard steel-pipe foundations commonly used in plastic greenhouses, and the proposed sensor nodes were evaluated alongside a commercial IMU to validate attitude estimation accuracy and anomaly detection performance. Despite the approximately 30-fold cost difference, comparable attitude estimation results were achieved. The system demonstrated low power consumption, confirming its feasibility for long-term operation using batteries or small solar cells. These results demonstrate the applicability of low-cost IMUs for real-time structural monitoring of lightweight greenhouse foundations. Full article

In new wireless ecosystems, simultaneous wireless information and power transfer (SWIPT) and cooperative non-orthogonal multiple access (CNOMA) together make a potential design model. These systems enhance spectral efficiency (SE), energy efficiency (EE), and data interchange reliability by combining energy harvesting (EH), superposition coding (SC), and relay-assisted transmission. Despite this, CNOMA’s energy efficiency is still constrained by the fact that relay nodes servicing multiple users require a significant amount of power. Most previous studies look at performance as if imperfect successive interference cancellation (SIC) were possible. To solve these problems, this study presents a multiuser SWIPT-enabled cooperative wavelet NOMA (CWNOMA) framework that reduces imperfect SIC, inter-symbol interference (ISI), and inter-user interference. SWIPT-CWNOMA enhances overall energy efficiency (EE), keeps relays functional, and maintains data transmission strong for users by obtaining energy from received signals. The proposed architecture is evaluated against traditional CNOMA and orthogonal multiple access (OMA) in both perfect and imperfect scenarios with SIC. The authors derive closed-form formulas for EE, signal-to-interference-plus-noise ratio (SINR), and achievable rate to support the analysis. Residual error because of imperfect SIC for near users shows lower values in a varying range of SNR. Across 0–30 dB SNR, SWIPT-CWNOMA achieves, on average, $1.4$ times higher energy efficiency, approximately $4.7$ lower BER, and $1.9$ times higher achievable rate than OFDMA, which establishes SWIPT-CWNOMA as a promising candidate for next-generation energy-efficient wireless networks. Full article

This paper analyses the parameterisation of protective relays in industrial power distribution stations, focusing on the quantitative relationship between network load and protection system response time. Laboratory simulations using a dedicated automation cabinet and varying network configurations (six streams at 80 samples/cycle and two to four streams at 256 samples/cycle) revealed a clear correlation: higher network loads lead to longer trip times. Under maximum load (four streams, 256 samples/cycle), response times reached up to 63.75 ms. These delays stemmed from network congestion rather than relay instability. The extended clearing times increased the short-circuit energy (I²t) by approximately 35% on average and over 55% in critical scenarios, requiring upsizing of PVC-insulated conductors from 16 mm² to 25 mm² to maintain short-circuit withstand capacity. The findings demonstrate the practical impact of network-induced delays on protection performance, thermal stress, and cable sizing, providing a basis for optimising relay settings and system configuration in modern digital power distribution networks. Full article

Unmanned aerial vehicles (UAVs) are a promising technology for future sixth-generation (6G) wireless networks. They are airborne vehicles that act either as as flying relays or base stations (BS) to provide the line-of-sight (LOS) transmission, enable wide-area coverage, and increase the spectral efficiency. In this work, a UAV is employed to forward information from the BS to distant users using a decode-and-forward (DF) protocol. The BS serves ground users through UAV by employing non-orthogonal multiple access (NOMA). The UAV relay will be wirelessly powered and harvests energy from the BS by applying a simultaneous wireless information and power transfer (SWIPT) technique. To further improve overall performance, the near user will act as a full-duplex (FD) relay to forward the far user’s information by applying cooperative non-orthogonal multiple access (C-NOMA). The proposed scheme considers a practical detection order using a feasible successive interference cancellation (SIC) operation. Additionally, a relay power control method is introduced for the near user to guarantee a reliable cooperative link. In the proposed scheme, a low-complexity closed-form power allocation is derived to maximize the minimum achievable rate. Numerical results demonstrate that the power allocation scheme significantly improves the far user’s rate performance, and the proposed scheme guarantees a higher target rate and outperforms the conventional NOMA, half-duplex (HD) C-NOMA, and FD C-NOMA with fixed power allocation (FPA) and fractional transmit power allocation (FTPA) schemes. Full article

In this paper, we study a cognitive relay Internet of Things (IoT) network aided by an unmanned aerial vehicle (UAV) equipped with multiple antennas. The UAV performs relaying for secondary communication under stringent interference constraints imposed by the primary network. To address the outage probability floor problem caused by strong interference channels, we propose a novel joint antenna selection and transmit power optimization scheme for Rician fading channels. By using the time-sharing condition and the Lagrangian dual method, the nonconvex mixed-integer optimization problem is efficiently solved to obtain the optimal solution. Additionally, a closed-form asymptotic lower bound on the outage probability is derived for Rayleigh fading channels, providing valuable performance insights. Numerical results demonstrate that the proposed joint optimization scheme significantly outperforms existing works. Full article

With the rapid growth of wireless devices, security has become a key research concern in beyond-5G (B5G) and sixth-generation (6G) networks. Non-orthogonal multiple access (NOMA), one of the supporting technologies, is a strong contender to enable massive connectivity, increase spectrum efficiency, and guarantee high-quality access for a sizable user base. Furthermore, the scientific community has recently paid close attention to the effects of hardware impairments (HIs). The safe transmission of NOMA in a two-user uplink relay network is examined in this paper, taking into account both hardware limitations and the existence of listening devices. Each time frame in a mobile network environment comprises two phases in which users use a relay (R) to interact with the base station ($BS$). The research focuses on scenarios where a malicious device attempts to intercept the uplink signals transmitted by users through the R. Using important performance and security metrics, such as connection outage probability (COP), secrecy outage probability (SOP), and intercept probability (IP), system behavior is evaluated. To assess the system’s security and reliability under the proposed framework, closed-form analytical expressions are derived for SOP, IP, and COP. The simulation results provide the following insights: (i) they validate the accuracy of the derived analytical expressions; (ii) the study significantly deepens the understanding of secure NOMA uplink transmission under the influence of HIs across all the network entities, paving the way for future practical implementations; and (iii) the results highlight the superior performance of secure and reliable NOMA uplink systems compared to benchmark orthogonal multiple access (OMA) counterparts when both operate under the same HI conditions. Furthermore, an extended model without a relay is considered for comparison with the proposed relay-assisted scheme. Moreover, the numerical results indicate that the proposed communication model achieves over 90% reliability (with a COP below 0.1) and provides approximately a 30% improvement in SOP compared to conventional OMA-based systems under the same HI conditions. Full article