Search Results (237)

The swift advancement of fifth-generation (5G) wireless technology brings forth a range of enhancements to address the increasing demand for data, the proliferation of smart devices, and the growth of the Internet of Things (IoT). This highly interconnected communication environment necessitates using multiple-input multiple-output (MIMO) systems to achieve adequate channel capacity. In this article, a 2-port MIMO system using two flipped parallel 1 × 2 arrays and a 2-port MIMO system using two opposite 1 × 4 arrays designed and fabricated antennas for 5G wireless communication in the sub-6 GHz band, are presented, overcoming the limitations of previous designs in gain, radiation efficiency and MIMO performance. The designed and fabricated single-element antenna features a circular microstrip patch design based on ROGER 5880 (RT5880) substrate, which has a thickness of 1.57 mm, a permittivity of 2.2, and a tangential loss of 0.0009. The 2-port MIMO of two 1 × 2 arrays and the 2-port MIMO of two 1 × 4 arrays have overall dimensions of 132 × 66 × 1.57 mm³ and 140 × 132 × 1.57 mm³, respectively. The MIMO of two 1 × 2 arrays and MIMO of two 1 × 4 arrays encompass maximum gains of 8.3 dBi and 10.9 dBi, respectively, with maximum radiation efficiency reaching 95% and 97.46%. High MIMO performance outcomes are observed for both the MIMO of two 1 × 2 arrays and the MIMO of two 1 × 4 arrays, with the channel capacity loss (CCL) ˂ 0.4 bit/s/Hz and ˂0.3 bit/s/Hz, respectively, an envelope correlation coefficient (ECC) ˂ 0.006 and ˂0.003, respectively, directivity gain (DG) about 10 dB, and a total active reflection coefficient (TARC) under −10 dB, ensuring impedance matching and effective mutual coupling among neighboring parameters, which confirms their effectiveness for 5G applications. The three fabricated antennas were experimentally tested and implemented using the MIMO Application Framework version 19.5 for 5G systems, demonstrating operational effectiveness in 5G applications. Full article

Reconfigurable intelligent surfaces (RISs), recognized as one of the most promising key technologies for sixth-generation (6G) mobile communications, are characterized by their minimal energy expenditure, cost-effectiveness, and straightforward implementation. In this study, we develop a novel communication channel model that integrates RIS-enabled base stations with unmanned ground vehicles. To enhance the system’s adaptability, we implement a fluid antenna system (FAS) at the unmanned ground vehicle (UGV) terminal. This innovative model demonstrates exceptional versatility across various wireless communication scenarios through the strategic adjustment of active ports. The inherent dynamic reconfigurability of the FAS provides superior flexibility and adaptability in air-to-ground communication environments. In the paper, we derive and study key performance characteristics like the autocorrelation function (ACF), validating the model’s effectiveness. The results demonstrate that the RIS-FAS collaborative scheme significantly enhances channel reliability while effectively addressing critical challenges in 6G networks, including signal blockage and spatial constraints in mobile terminals. Full article

High-speed switching chips are key components of network core devices in the high-performance computing paradigm, and their scheduling algorithm performance directly influences the throughput, latency, and fairness within the system. However, traditional scheduling algorithms often encounter issues such as high implementation complexity and high communication overhead when dealing with bursty traffic. To addressing the issue of bottlenecks in high-speed switching chip scheduling, we propose a low-complexity and high-performance scheduling algorithm called m-RGA, where m represents a priority mechanism. First, by monitoring the historical service time and load level of the VOQs at the port, the priority of the VOQs is dynamically adjusted to enhance the efficient matching and fair allocation of port resources. Additionally, we prove that an algorithm achieving a 2× speedup under a constant traffic model can simultaneously guarantee throughput and latency, making this algorithm theoretically as excellent as any maximum matching algorithm. Through simulation, we demonstrate that m-RGA outperforms Highest Rank First (HRF) arbitration in terms of latency under non-uniform and bursty traffic patterns. Full article

In precision cotton seeding, the toothed-disk precision seeder often experiences issues with missed seeding and multiple seeding. To promptly detect and address these abnormal seeding conditions, this study develops a modular photoelectric sensing monitoring system. Initially, the monitoring time window is divided using the capacitance sensing signal between two seed drop ports. Concurrently, a photoelectric monitoring circuit is designed to convert the time when seeds block the sensor into a level signal. Subsequently, threshold segmentation is performed on the time when seeds block the photoelectric path under different seeding states. The proposed spatiotemporal joint counting algorithm identifies, in real time, the threshold type of the photoelectric sensor’s output signal within the current monitoring time window, enabling the differentiation of seeding states and the recording of data. Additionally, an STM32 micro-controller serves as the core of the signal acquisition circuit, sending collected data to the PC terminal via serial port communication. The graphical display interface, designed with LVGL (Light and Versatile Graphics Library), updates the seeding monitoring information in real time. Compared to photoelectric monitoring algorithms that detect seed pickup at the seed metering disc, the monitoring node in this study is positioned posteriorly within the seed guide chamber. Consequently, the differentiation between single seeding and multiple seeding is achieved with greater accuracy by the spatiotemporal joint counting algorithm, thereby enhancing the monitoring precision of the system. Field test results indicate that the system’s average accuracy for single-seeding monitoring is 97.30%, for missed-seeding monitoring is 96.48%, and for multiple-seeding monitoring is 96.47%. The average probability of system misjudgment is 3.25%. These outcomes suggest that the proposed modular photoelectric sensing monitoring system can meet the monitoring requirements of precision cotton seeding at various seeding speeds. Full article

This study explores the impact of graphene integration on lithium niobate (LiNbO₃, LN) ridge waveguides and directional couplers, focusing on coupling efficiency, polarization-dependent light absorption, and temperature sensitivity. Experimental and simulation results reveal that graphene loading significantly alters the effective mode refractive index and enhances waveguide coupling, enabling precise control over light transmission and power distribution. The temperature-dependent behavior of graphene–LN structures demonstrates strong thermal sensitivity, with notable changes in output power ratios between cross and through ports under varying temperatures. These findings highlight the potential of graphene–LN hybrid devices for compact, high-performance photonic circuits and temperature sensing applications. This study provides valuable insights into the design of advanced integrated photonic systems, paving the way for innovations in optical communication, sensing, and quantum technologies. Full article

This paper presents a compact, high-performance metasurface-based leaky-wave MIMO antenna with dimensions of 40 × 30 mm², achieving a gain of 12.5 dBi and a radiation efficiency of 85%. The antenna enables precise control of electromagnetic waves, featuring a flower-like metasurface (MTS) with coffee bean-shaped arrays on substrates of varying permittivity, separated by a cavity layer to enhance coupling. Its dual-port MIMO design boosts data throughput operating in three bands (3.75–5.25 GHz, 6.4–15.4 GHz, and 22.5–30 GHz), while the leaky-wave mechanism supports frequency- or phase-dependent beamsteering without mechanical parts. Ideal for CubeSat communications, its compact size meets CubeSat constraints, and its high gain and efficiency ensure reliable long-distance communication with low power consumption, which is crucial for low Earth orbit operations. Circular polarization (CP) maintains signal integrity despite orientation changes, and MIMO capability supports high data rates for applications such as Earth observations or inter-satellite links. The beamsteering feature allows for dynamic tracking of ground stations or satellites, enhancing mission flexibility and reducing interference. This lightweight, efficient antenna addresses modern CubeSat challenges, providing a robust solution for advanced space communication systems with significant potential to enhance satellite connectivity and data transmission in complex space environments. Full article

The integration of intelligent voice-control systems represents a critical pathway for enhancing driver comfort and reducing cognitive distraction in modern vehicles. Currently, voice assistants capable of accessing real-time vehicular data (e.g., engine parameters) or controlling actuators (e.g., door locks) remain exclusive to premium brands. While aftermarket solutions like Amazon’s Echo Auto provide multimedia functionality, they lack access to critical vehicle systems. To address this gap, we develop a novel architecture leveraging the OBD-II port to enable voice-controlled telematics and actuation in mass-production vehicles. Our system interfaces with a Toyota Hilux (2020) and Mazda CX-3 SUV (2021), utilizing an MCP2515 CAN controller for engine control unit (ECU) communication, an Arduino Nano for data processing, and an ESP01 Wi-Fi module for cloud transmission. The Blynk IoT platform orchestrates data flow and provides user interfaces, while a Voiceflow-programmed Alexa skill enables natural language commands (e.g., “unlock doors”) via Alexa Auto. Experimental validation confirms the successful real-time monitoring of engine variables (coolant temperature, air–fuel ratio, ignition timing) and secure door-lock control. This work demonstrates that high-end vehicle capabilities—previously restricted to luxury segments—can be effectively implemented in series-production automobiles through standardized OBD-II protocols and IoT integration, establishing a scalable framework for next-generation in-vehicle assistants. Full article

This paper presents a novel, four-port, rectangular microstrip, inset-feed multiple-input and multiple-output (MIMO) antenna array, enhanced with metamaterials for improved gain and isolation, specifically designed for multi-operator 5G open radio access network (ORAN)-based indoor software-defined radio (SDR) applications. ORAN is an open-source interoperable framework for radio access networks (RANs), while SDR refers to a radio communication system where functions are implemented via software on a programmable platform. A 3 × 3 metamaterial (MTM) superstrate is placed above the MIMO antenna array to improve gain and reduce the mutual coupling of MIMO. The proposed MIMO antenna operates over a 300 MHz bandwidth (3.5–3.8 GHz), enabling shared infrastructure for multiple operators. The antenna’s dimensions are 75 × 75 × 18.2 mm³. The antenna possesses a reduced mutual coupling less than −30 dB and a 3.5 dB enhancement in gain with the help of a novel 3 × 3 MTM superstrate 15 mm above the radiating MIMO elements. A performance evaluation based on simulated results and lab measurements demonstrates the promising value of key MIMO metrics such as a low envelope correlation coefficient (ECC) < 0.002, diversity gain (DG) ~10 dB, total active reflection coefficient (TARC) < −10 dB, and channel capacity loss (CCL) < 0.2 bits/sec/Hz. Real-world testing of the proposed antenna for ORAN-based sub-6 GHz indoor wireless systems demonstrates a downlink throughput of approximately 200 Mbps, uplink throughput of 80 Mbps, and transmission delays below 80 ms. Additionally, a walk test in an indoor environment with a corresponding floor plan and reference signal received power (RSRP) measurements indicates that most of the coverage area achieves RSRP values exceeding −75 dBm, confirming its suitability for indoor applications. Full article

Coastal and maritime regions and their entities face accelerated degradation due to the combined effects of environmental stressors and anthropogenic activities. Coastal degradation can be identified, visualized and estimated through periodic monitoring over a region of interest using earth observation, climate, meteorological, seasonal, waves, sea level rising, and other ocean- and maritime-related datasets. Usually, these datasets are provided through different sources, in different structures or data types; in many cases, a complete dataset can be large in size and needs some kind of preprocessing (information filtering) before use in the intended application. Recently, the term data cube introduced in the scientific community and frameworks like Google Earth Engine and Open Data Cubes have emerged as a solution to earth observation data harmonization, federation, and exchange framework; however, these sources either completely lack the ability to process climate, meteorological, waves, sea lever rising, etc., data from open sources, like CORDEX and WCRP, or preprocessing is required. This study describes and utilizes the Ocean-DC framework for modular earth observation and other data types to resolve major big data challenges. Compared to the already existing approaches, the Ocean-DC framework harmonizes several types of data and generates ready-to-use data cubes products, which can be merged together to produce high-dimensionality visualization products. To prove the efficiency of the Ocean-DC framework, a case study at Crete Island, emphasizing the Port of Heraklion, demonstrates the practical utility by revealing degradation trends via time-series analysis of several related remote sensing indices calculated using the Ocean-DC framework. The results show a significant reduction in processing time (up to 89%) compared to traditional remote sensing approaches and optimized data storage management, proving its value as a scalable solution for environmental resilience, highlighting its potential use in early warning systems and decision support systems for sustainable coastal infrastructure management. Full article

Under the “Dual Carbon” strategy, collaborative governance of port atmospheric pollutants and carbon emissions is critical for low-carbon transformation. Focusing on Ningbo-Zhoushan Port (48% regional ship emissions), this study examines government, port enterprises, and public interactions. A tripartite evolutionary game model with numerical simulation reveals dynamic patterns and key factors. The results show the following: (1) A substitution effect exists between government incentive costs and penalty intensity—increased environmental governance budgets reduce the probability of government incentives, whereas higher public reporting rewards accelerate corporate emission reduction convergence. (2) Public supervision exhibits cyclical fluctuations due to conflicts between individual rationality and collective interests, with excessive reporting rewards potentially triggering free-rider behavior. (3) The system exhibits two stable equilibria: a low-efficiency equilibrium (0,0,0) and a high-efficiency equilibrium (1,1,1). The latter requires policy cost compensation, corporate emission reduction gains exceeding investments, and a supervision benefit–cost ratio greater than 1. Accordingly, the study proposes a three-dimensional “Incentive–Constraint–Collaboration” governance strategy, recommending floating penalty mechanisms, green financial instrument innovation, and community supervision network optimization to balance environmental benefits with fiscal sustainability. This research provides a dynamic decision-making framework for multi-agent collaborative emission reduction in ports, offering both methodological innovation and practical guidance value. Full article

This research introduces a novel, high-performance multiple-input–multiple-output (MIMO) antenna designed to operate in allocated millimeter-wave (mmWave) 5G wireless communications. Operating in the tri-band, 28, 35, and 38 GHz, the four-port MIMO antenna possesses a compact size—measuring just 50 × 50 × 0.787 mm³ (4.67λ_o × 4.67λ_o × 0.73λ_o). The antenna delivers a remarkable performance, achieving peak gains of 9.6, 7.8, and 13.7 dBi in the tri-band, respectively. The realized bandwidths are 1.1, 2.2, and 3.7 GHz, at the tri-band frequencies. The antenna’s performance was significantly improved by carefully spacing the elements and employing a decoupling technique using metamaterial cells. This minimized interference between the antenna elements, resulting in efficient MIMO operation with a low envelope correlation coefficient of 0.00015 and a high diversity gain approaching 10 dB, and high isolation of 34.5, 22, and 30 dB, in the tri-band. This proposed design is confirmed with experimental measurements and offers a promising candidate for multi-band use of mmWave communication systems. Full article

The growing demand for high-speed and high-capacity wireless communication has intensified the need for compact, wideband, and efficient MIMO antenna systems, particularly for 5G mid-band and UWB applications. This article presents a miniaturized dual and quad port MIMO antenna design optimized for 5G mid-band (n77/n78/n79/n96/n102) and Ultra-Wideband (UWB) applications without employing any decoupling structures between the radiating elements. The 2-port configuration features two closely spaced symmetric monopole elements (spacing < λ_max/2), promoting efficient use of space without degrading performance. An FR4 substrate (εr = 4.4) is used for fabrication with a compact size of 30 × 41 × 1.6 mm³. This layout is extended orthogonally and symmetrically to form a compact quad-port variant with dimensions of 60 × 41 × 1.6 mm³. Both designs offer a broad operational bandwidth from 2.6 GHz to 10.8 GHz (8.2 GHz), retaining return loss (S_XX) below −10 dB and strong isolation (S_XY < −20 dB at high frequencies, <−15 dB at low frequencies). The proposed MIMO antennas demonstrate strong performance and excellent diversity characteristics. The two-port antenna achieves an average envelope correlation coefficient (ECC) of 0.00204, diversity gain (DG) of 9.98 dB, and a mean effective gain difference (MEG_ij) of 0.3 dB, with a total active reflection coefficient (TARC) below −10 dB and signal delay variation under 0.25 ns, ensuring minimal pulse distortion. Similarly, the four-port design reports an average ECC of 0.01432, DG of 9.65 dB, MEG_ij difference below 0.3 dB, and TARC below −10 dB, confirming robust diversity and MIMO performance across both configurations. Full article

Interorganizational risk management (IRM) in Canadian ports faces significant challenges due to the interconnected nature of operations and the interdependence of safety, security, environmental, organizational, and technological risks. Existing siloed risk management frameworks often fail to capture these dynamic interrelations, underscoring the need for a more integrated, systemic approach. This study introduces a Port Risk Control Structure (PRCS) designed specifically for Canadian Port Authorities (CPAs), based on the Systems-Theoretic Accident Model and Processes (STAMP). The PRCS maps control actions, feedback loops, and stakeholder roles across international, national, and local levels to better reflect the layered nature of port governance. The model aims to clarify the roles of key actors, such as the International Maritime Organization, Transport Canada, and local port stakeholders, and is designed to facilitate more structured risk identification, communication, and coordination across organizational levels. Although the model has not yet been empirically validated, its design suggests strong potential for scalability and adaptability across diverse port contexts. This research contributes to IRM literature by illustrating how STAMP principles can be operationalized within port systems. Future research will focus on integrating a taxonomy of IRM challenges to refine control structures and feedback mechanisms in response to evolving risks. Full article

This paper proposes a dual-band antenna to support 5G communication with linear polarization and the global navigation satellite system (GNSS) band with circular polarization. A single inverted T-shaped patch antenna with a defective ground was designed on the Schott Foturan II (Ceramized 560 degrees) substrate. Then, an L-shaped stub and slot were inserted into the ground to achieve the 5G and GNSS bands. The antenna was then designed as a 1 × 2 multiple-input and multiple-output (MIMO) antenna to increase the directivity. A square ring-shaped frequency selective surface (FSS) was intended on the FR-4 substrate to improve the gain of the MIMO antenna. The FSS MIMO antenna increased the 3D gain from 2.8 to 5.4 dBi for the GNSS band and from 4.9 to 6.43 dBi for the 5G n79 band. The proposed antenna can receive and transmit the frequency bands covering sub-6 GHz 5G band n79 (4400–5000 MHz) and GNSS band E6 (1260–1300 MHz), respectively. A multi-port unmanned aerial vehicle antenna was fabricated, and its performance was characterized in terms of bandwidth, axial ratio, and gain. Full article

The rapid evolution of wireless communications has introduced new possibilities for the digital transformation of maritime operations. As 5G begins to take shape in selected nearshore and port environments, the forthcoming 6G promises to unlock transformative capabilities across the entire maritime domain, integrating Terrestrial/Non-Terrestrial Networks (TN/NTN) to form a space-air-ground-sea-underwater system. This paper presents a comprehensive review of how 6G-enabling technologies can be adapted to address the unique challenges of Maritime Communication Networks (MCNs). We begin by outlining a reference architecture for heterogeneous MCNs and reviewing the limitations of existing 5G deployments at sea. We then explore the key technical advancements introduced by 6G and map them to maritime use cases such as fleet coordination, just-in-time port logistics, and low-latency emergency response. Furthermore, the critical Artificial Intelligence/Machine Learning (AI/ML) concepts and algorithms are described to highlight their potential in optimizing maritime functionalities. Finally, we propose a set of resource optimization scenarios, including dynamic spectrum allocation, energy-efficient communications and edge offloading in MCNs, and discuss how AI/ML and learning-based methods can offer scalable, adaptive solutions. By bridging the gap between emerging 6G capabilities and practical maritime requirements, this paper highlights the role of intelligent, resilient, and globally connected networks in shaping the future of maritime communications. Full article