Reliable Communication Research Articles

Nominal GSM-R Radio Network Design for Signalling and Train Control Systems: Case Study Dar-Moro Electrified SGR Line in Tanzania

The recent development of High-Speed Trains (HST) operations requires real-time information transfer, high network capacity, and reliable communication for train signalling and control purposes. Rail operators face challenges as the high-speed railroad traffic grows. In a high-speed driving profile, the communication must be able to overcome fast handover, large Doppler shift, high penetration losses, limited visibility in tunnels, and the harsh electromagnetic environment. Global System for Mobile Communications for Railway (GSM-R) is still a standard-bearer for railway signalling communications. The link capacity and coverage prediction of the predefined Base Transceiver Station (BTS) locations are simulated using the Radio Planner RF planning tool and Matlab®. The terrain map and the signal levels along the railway corridor are observed. The analysis of the GSM-R for a fast-moving train is performed. Signal level coverage prediction, Doppler-shift effect and the received carrier frequencies due to Doppler shift along Dar–Pugu stations have been presented. The critical sites (locations) with weak signals of the first three BTSs have been identified. It is also observed that the Doppler effect may limit the proposed speed.

RIS-Assisted D2D Communication over Nakagami-m Fading with RSMA.

In this study, we investigated reconfigurable intelligent surface (RIS)-assisted device-to-device (D2D) communication systems over Nakagami-m fading channels. To enhance the reliability of RIS-assisted D2D communications, we utilized the rate-splitting multiple access (RSMA) technique to maximize the achievable ergodic rate for our considered systems. Specifically, both devices decoded the common symbol by treating private symbols as interference, and then each private symbol was decoded by treating the other as interference. In order to maximize the achievable ergodic rate at the destination, we analyzed the achievable ergodic rate of the RIS link and the D2D link, and the destination jointly decoded both symbols transmitted from the source and device by involving the maximum ratio combination (MRC). We obtained a closed-form expression for the achievable ergodic rate of the proposed RIS-assisted D2D communication system. Finally, we investigated the influence of power allocation factors and the number of reflective elements on the achievable ergodic rate. As seen by the numerical results, there was a good match between the analysis and simulation results, as well as significant superiority compared with existing works.

A deep learning framework for blockage mitigation and duration prediction in mmWave wireless networks

Millimeter-Wave (mmWave) communication can be highly affected by blockages, which can drastically decrease the signal strength at the receiver side. To overcome the impact of blockages, predicting the optimal mitigation technique and accurately estimating the duration of the blockage events are crucial for maintaining reliable and high-performance mmWave communication systems. Prior works on mitigating blockages have proposed a variety of model and protocol-based blockage mitigation solutions that concentrate on a singular technique at a time, like switching the current beam to an alternative beam at the current base station or client. In this paper, we tackle the overarching question: what blockage mitigation technique should be employed? and what is the optimal sub-selection within that technique? We also address the blockage duration estimation problem. We solve these problems by developing a Gated Recurrent Unit (GRU) model, trained on data from periodic message exchanges in mmWave systems. We tested our neural network models by utilizing a mmWave simulator that is commercially available and widely used in wireless communication to compile a large amount of dataset for this purpose. Our findings reveal that our proposed method introduces no extra communication overhead, while achieving remarkable accuracy, exceeding 91%, in predicting the optimal blockage mitigation technique. Moreover, the blockage duration estimation model achieves a very high accuracy with a residual mean error of less than 0.04 s. Finally, we demonstrate that our proposed blockage mitigation method substantially boosts the volume of data transferred in comparison to various other blockage mitigation strategies.

Strategic Deployment of Ducklink Wireless Devices for Disaster Mitigation and Management in Nueva ECIJA University of Science and Technology Sumacab Campus

A significant challenge during disasters is the breakdown of traditional communication systems, impeding rescue operations and information dissemination. To tackle this issue, researchers conducted a study on strategically deploying DuckLink wireless devices within a small community, particularly at NEUST Sumacab Campus. Utilizing tools like Google Maps, Google Earth, and WiFi Heat Map, optimal locations for device placement were identified. Analyzing signal range and performance characteristics, the study endeavored to enhance disaster management capabilities on campus. Findings revealed DuckLink devices operate with omnidirectional polarity, ensuring reliable communication, with a clear correlation between distance and message transmission time emphasizing strategic device placement for efficient campus-wide connectivity. Recommending the installation of 112 devices across 79 buildings, with key locations designated for Papaduck receivers and Mamaduck transmitters, this research offers crucial insights into disaster management strategies, optimizing wireless communication infrastructure in educational environments, thus contributing to safer and more resilient communities.

Validation of a Cantonese Version of the Amsterdam-Nijmegen Everyday Language Test (CANELT): A functional approach.

The current study aimed to validate the Cantonese version of the Amsterdam-Nijmegen Everyday Language Test (CANELT), a functional communication assessment tool for Cantonese speakers with aphasia. A quantitative scoring method was adopted to examine the pragmatics and informativeness of the production of people with aphasia (PWA). CANELT was translated from its English version with cultural adaptations. The performance on the 20-item CANELT collected from 56 PWA and 100 neurologically healthy Cantonese-speaking controls aged 30 to 79 years was orthographically transcribed. Scoring was based on the completeness of the main concepts produced in the preamble and subsequent elaborations, defined as Opening (O) and New Information (NI). Measures examining the validity and reliability were conducted. An age effect was found in neurologically healthy controls, and therefore z scores were used for subsequent comparisons between neurologically healthy controls and PWA. The test showed strong evidence for known-group validity in both O [χ2 (2) = 95.2, p < .001] and NI [χ2 (2) = 100.4, p < .001]. A moderate to strong correlation was found between CANELT and standardized aphasia assessment tools, suggesting satisfactory concurrent validity. Reliability measures were excellent in terms of internal consistency (Cronbach's α of .95 for both 'O' and 'NI'), test-retest reliability (ICC = .96; p < .001), intra-rater reliability (ICC = 1.00; p < .001), and inter-rater reliability for O (ICC = .99; p < .001) and NI (ICC = .99; p < .001). Sensitivity and specificity for O are 97% and 76.8%, respectively, while for NI, a sensitivity of 95% and specificity of 91.1% were obtained. Measures on validity and reliability yielded promising results, suggesting CANELT as a useful and reliable functional communication assessment for PWA. Its application in managing PWA and potential areas for development are discussed.

Joint uplink-downlink user-cell association for ultra-dense NOMA networks

As wireless communication systems evolve, the transition from homogeneous structures to heterogeneous ones intensifies. The need for continuous connectivity, fairness, and spectrum efficiency, such as in massive Internet of Things (IoT) networks and ultra reliable low latency communications (uRLLC), necessitates the utilization of base stations with diverse capabilities and coverage areas. As a result, the need for advanced interference management, user-cell association, and resource allocation techniques increases. This study proposes an innovative solution for the problem of non-orthogonal multiple access (NOMA) user-cell association in multi-tier ultra-dense heterogeneous networks (UD-HetNet). The proposed network constitutes a general framework that can be applied to next generation cellular communications, massive IoT, non-terrestrial and uRLLC type communications. Differing from previous studies that ignore interference and primarily focus on the received signal powers for user-cell association, this investigation advances the subject by considering the interplay between downlink received signal/interference power and uplink inter-cell interference. Due to the non-convex integer programming nature of the problem, it is proposed to employ an innovative relaxation algorithm to obtain a sub-optimal solution for the total signal-to-interference-plus-noise ratio (SINR). As verified through simulation results, the proposed association method permits concurrent communication participation of multiple users while managing the interference, rendering it as an ideal approach for systems emphasizing fairness and continuous connectivity.

A Generic High-Performance Architecture for VPN Gateways

Virtual private network (VPN) gateways are widely applied to provide secure end-to-end remote access and to relay reliable interconnected communication in cloud computing. As network convergence nodes, the performance of VPN gateways is limited by traditional methods of packet receiving and sending, the kernel protocol stack and the virtual network interface card. This paper proposes a generic high-performance architecture (GHPA) for VPN gateways in consideration of its generality and performance. In terms of generality, we redesign a generic VPN core framework by modeling a generic VPN communication model, formulating generic VPN core technologies and presenting corresponding core algorithms. In terms of performance, we propose a three-layer GHPA for VPN gateways by designing a VPN packet processing layer based on a data plane development kit (DPDK), implementing a user space basic protocol stack and applying our proposed generic VPN core framework. On the basis of the research work above, we implement a high-performance VPN (HP-VPN) and a traditional VPN (T-VPN) that complies with GHPA and traditional methods, respectively. Experimental results prove that the performance of HP-VPN based on GHPA is superior to T-VPN and other common VPNs in RTT, system throughput, packet forwarding rate and jitter. In addition, GHPA is extensible and applicable for other VPN gateways to improve their performance.

Unveiling New IoT Antenna Developments: Planar Multibeam Metasurface Half-Maxwell Fish-Eye Lens with Wavelength Etching

This study introduces a groundbreaking antenna system, the directive Metasurface Half-Maxwell Fish-Eye (MHMF) lens antenna, tailored specifically for Internet-of-Things (IoT) networks. Designed to operate at 60 GHz, this antenna ingeniously integrates a dipole antenna within a parallel-plate waveguide to illuminate a Half-Maxwell Fish-Eye (HMFE) lens. The HMFE lens serves as a focal point, enabling a crucial high gain for IoT operations. The integration of metasurface structures facilitates the attainment of the gradient refractive index essential for the lens surface. By employing commercial Ansys HFSS software, extensive numerical simulations were conducted to meticulously refine the design, focusing particularly on optimizing the dimensions of unit cells, notably the modified H-shaped cells within the parallel waveguides housing the beam launchers. A functional prototype of the antenna was constructed using a standard PCB manufacturing process. Rigorous testing in an anechoic chamber confirmed the functionality of these manufactured devices, with the experimental results closely aligning with the simulated findings. Far-field measurements have further confirmed the effectiveness of the antenna, establishing it as a high-gain antenna solution suitable for IoT applications. Specifically, it operates effectively within the 60 GHz range of the electromagnetic spectrum, which is crucial for ensuring reliable communication in IoT devices. The directive HMFE lens antenna represents a significant advancement in enhancing IoT connectivity and capabilities. Leveraging innovative design concepts and metasurface technology, it heralds a new era of adaptable and efficient IoT systems.

Signal points allocation for generalized enhanced spatial modulation

AbstractIn this paper, making full use of the spatial domain of transmit antennas (TAs) and keeping the characteristic of the squared minimum Euclidean distance (MED) between the transmitted spatial vectors (TSVs), generalized enhanced spatial modulation with signal points allocation (GESM‐SPA) is proposed to expand the size of signal spaces for enhancing the spectral efficiency and the reliability of communications. In the GESM‐SPA, according to the number of active TAs, signal constellation points (CPs) from the QAM or secondary QAM constellations are allocated and then modulated on the corresponding active TAs with the selected antenna index (AI) vector. Through this design, which further exploits the spatial domain with the variability of active TAs, the squared MED between the TSVs is increased in comparison with the existing traditional systems. More specifically, in view of the disadvantage of the classic ESM system, the constellation groups (CGs) with priority given to the QAM CPs are constructed to further maximize the squared MED. Then, the AI vector subsets corresponding to the obtained CGs are designed to be candidate for the specified AI vector set with the AI information. The squared MED and the average bit error probability (BEP) are analyzed. In simulation results using Monte Carlo, the GESM‐SPA outperforms the existing classic systems in terms of the bit error rate performance.

UAV-Based Delivery Systems: A Systematic Review, Current Trends, and Research Challenges

The rising popularity of drones significantly impacts package delivery services, offering both unique opportunities and challenges. This survey explores the diverse applications of drones for last-mile deliveries, highlighting their capacity to access remote areas and create new business prospects. Use cases, ranging from critical medical deliveries to addressing COVID-19 pandemic needs, underscore the transformative potential of drone technology. While recognizing drones’ eco-friendly attributes in eliminating harmful gas emissions, the survey addresses battery constraints, necessitating an investigation into physical energy models to extend flight autonomy. This becomes crucial for operational capabilities, especially in adverse weather conditions. A reliable communication infrastructure is crucial for the success of drone operations in package delivery, especially during unexpected events, as seamless connectivity plays a key role in facilitating efficient control and monitoring between ground stations and drones. This enables dynamic rerouting, enhancing overall delivery reliability. The survey explores innovative approaches, including collaborations with other vehicles like trucks, trains, and buses, optimizing the last-mile delivery process. Despite the transformative potential, concerns about privacy, security, safety, and risk management in drone delivery are acknowledged. The work also emphasizes responsible and ethical implementation, considering diverse concerns associated with widespread adoption. In contrast to existing survey articles focused on specific technical aspects, this comprehensive survey broadens its scope. It covers ethical issues, sustainability aspects, healthcare systems, physics models, innovative approaches, reliable communications, security and safety concerns, and real test-beds in drone-based delivery systems. The survey not only identifies potential applications and tackles technical challenges but also integrates broader considerations. In addition, this work extensively explores the motivations, lessons learned, and future directions in the realm of drone delivery. Analyzing existing literature, it provides valuable insights for researchers, industry professionals, policymakers, and stakeholders keen on understanding the dynamic evolution of drone technology in the package delivery domain.

Enhancing Communication Reliability: Designing Microwave Links for Bahir Dar-Woretta Connectivity

This paper explores the need for establishing a microwave link between Bahir Dar and Woretta as an alternative communication solution to the existing optical fiber infrastructure. Microwave links offer an effective way to overcome challenges posed by rugged terrains and unfavorable environmental conditions that hinder the deployment of fiber optics. As Woretta emerges as a key economic and investment hub within the Amhara Region, demand for reliable and efficient communication is expected to grow significantly. The study encompasses various aspects of planning and designing the microwave link, including site surveys, consideration of fade margins, frequency planning, link budget calculations, and assessing the feasibility and reliability of the proposed link. The paper employs LINKPlanner 5.4.1 software to simulate and validate the results. Due to terrain constraints, a direct link between Bahir Dar and Woretta is not feasible. Instead, a two-hop link is proposed, involving transmission from Bahir Dar to Zege, and then from Zege to Woretta. This alternative configuration ensures optimal connectivity while addressing the terrain limitations. By presenting a comprehensive analysis and simulation of the microwave link, this paper provides valuable insights into the planning and implementation of a robust communication infrastructure. The proposed microwave link will offer a reliable and efficient alternative to the existing optical fiber network, ensuring uninterrupted connectivity to support the region’s growth and development.

Mitigation of reentry blackout via gas injection in arc-heating facility

Communication blackouts during atmospheric reentry pose significant challenges to the safety and adaptability of spacecraft missions. This phenomenon, caused by the attenuation of electromagnetic waves by the plasma surrounding the spacecraft, disrupts communication with ground stations or orbiting satellites. Therefore, it is crucial to decrease the plasma density in the vicinity of the spacecraft to ensure an unobstructed electromagnetic wave communication path. This study proposes a methodology that involves the injection of gas from the vehicle’s wall to create an insulating layer near the surface. This thin layer maintains lower temperatures and reduced plasma density, enabling electromagnetic wave propagation without attenuation. Practical experiments were conducted in an arc-heating facility to simulate atmospheric reentry conditions. The results of the experiments provided empirical evidence of the effectiveness of the technique in mitigating communication blackout phenomena. Numerical fluid analysis within the wind tunnel chamber validated the formation of an air film layer near the experimental model owing to the injected gas. Schlieren imaging revealed distinctive jet shapes, which corroborated the findings of the numerical analysis. The wind tunnel tests that simulated atmospheric reentry environments confirmed the formation of an air film layer through gas injection, which substantiates the reduction in communication blackout. These results have the potential to improve communication reliability in space transport.

IoT Based Antenna Positioning System

An IOT-based antenna’s position system aimed at optimizing connectivity. Through IoT-enabled actuators, the system enables remote adjustment of antenna orientation, managed by a central control unit. Real-time monitoring ensures accurate alignment for optimal signal reception, enhancing communication reliability. Key advantages include remote accessibility, allowing users to control antennas from anywhere with internet connectivity, and scalability, facilitating seamless integration into existing infrastructure. By leveraging IoT technology, the system empowers users with enhanced control over wireless communication networks, offering efficient and reliable antenna positioning solutions across diverse applications.

Enhancement of VANETS Security against Gray Hole Attack with ANFIS-GWO and LBK

Vehicular Ad Hoc Networks (VANETs) have emerged as a critical component of intelligent transportation systems, facilitating real time communication among vehicles and infrastructure. However, the open and dynamic nature of VANETs makes them vulnerable to various security threats, among which gray hole attacks pose significant challenges. In gray hole attacks, malicious nodes manipulate or selectively drop data packets, disrupting communication and compromising network integrity. In response to these challenges, this paper proposes an innovative approach that integrates the Adaptive Neuro Fuzzy Inference System (ANFIS) with Grey Wolf Optimization (GWO). The main objective of this research is to develop a robust ANFIS GWO framework capable of identifying and mitigating gray hole attacks in real time VANET scenarios. Through extensive simulations and experiments, the performance of proposed technique in terms of average energy consumed, throughput, Packet Delivery Ratio (PDR) and packet drop is examined. The results demonstrate that the ANFIS GWO approach not only improves the resilience of VANETs against gray hole attacks but also guarantees reliable and secure communication among vehicles and infrastructure.

Communications and Data Science for the Success of Vehicle-to-Grid Technologies: Current State and Future Trends

Vehicle-to-grid (V2G) technology has emerged as a promising solution for enhancing the integration of electric vehicles (EVs) into the electric grid, offering benefits, such as distributed energy resource (DER) integration, grid stability support, and peak demand management, among others, as well as environmental advantages. This study provides a comprehensive review of V2G systems, with a specific focus on the role of the communication, as they have been identified as key enablers, as well as the challenges that V2G must face. It begins by introducing the fundamentals of V2G systems, including their architecture, operation, and a description of the benefits for different sectors. It then delves into the communication technologies and protocols in V2G systems, highlighting the key requirements in achieving reliable and efficient communication between EVs and the different agents involved. A comprehensive review of communication standards is described, as well as the main communication technologies, which are evaluated in terms of their suitability for V2G applications. Furthermore, the study discusses the challenges and environmental implications of V2G technology, emphasizing the importance of addressing strong and reliable communications to maximize its potential benefits. Finally, future research directions and potential solutions for overcoming challenges in V2G systems are outlined, offering useful insights for researchers, policymakers, and administrations as well as related industry stakeholders.

Adversarial Defense Embedded Waveform Design for Reliable Communication in the Physical Layer

Adversarial Defense Embedded Waveform Design for Reliable Communication in the Physical Layer

Lightweight, Trust-Managing, and Privacy-Preserving Collaborative Intrusion Detection for Internet of Things

This research introduces a comprehensive collaborative intrusion detection system (CIDS) framework aimed at bolstering the security of Internet of Things (IoT) environments by synergistically integrating lightweight architecture, trust management, and privacy-preserving mechanisms. The proposed hierarchical architecture spans edge, fog, and cloud layers, ensuring efficient and scalable collaborative intrusion detection. Trustworthiness is established through the incorporation of distributed ledger technology (DLT), leveraging blockchain frameworks to enhance the reliability and transparency of communication among IoT devices. Furthermore, the research adopts federated learning (FL) techniques to address privacy concerns, allowing devices to collaboratively learn from decentralized data sources while preserving individual data privacy. Validation of the proposed approach is conducted using the CICIoT2023 dataset, demonstrating its effectiveness in enhancing the security posture of IoT ecosystems. This research contributes to the advancement of secure and resilient IoT infrastructures, addressing the imperative need for lightweight, trust-managing, and privacy-preserving solutions in the face of evolving cybersecurity challenges. According to our experiments, the proposed model achieved an average accuracy of 97.65%, precision of 97.65%, recall of 100%, and F1-score of 98.81% when detecting various attacks on IoT systems with heterogeneous devices and networks. The system is a lightweight system when compared with traditional intrusion detection that uses centralized learning in terms of network latency and memory consumption. The proposed system shows trust and can keep private data in an IoT environment.

A trust management solution for 5G-based future generation Internet of Vehicles

In recent years, 5G Internet-of-Vehicles (IoV) related standards have drawn attention in both academia and industry for supporting an efficient and reliable communication among vehicles in the network. However, notice that 5G-IoV related issues are defined as critical in both real and cyber space environments, as malfunctioning in such systems could cause traffic paralysis, serious accidents, and privacy leaks. Therefore, in order to overcome these challenges, a trusted and ideal framework is proposed using Dempster–Shafer Theory (DST), which is combined with a recommender mechanism in order to identify several DDoS threats. The major trust elements in order to identify the legitimacy of a node include frequency statistics, trust factor, residual energy, and trust policy. The proposed trusted mechanism is designed to provide an improved and efficient security solution by avoiding intruders which attempt to disrupt a 5G-IoV network. The proposed mechanism is further analyzed against several security measures, and validated using traditional security schemes in IoV environments.

Channel Knowledge Map Construction Based on a UAV-Assisted Channel Measurement System

With the fast development of unmanned aerial vehicles (UAVs), reliable UAV communication is becoming increasingly vital. The channel knowledge map (CKM) is a crucial bridge connecting the environment and the propagation channel that may visually depict channel characteristics. This paper presents a comprehensive scheme based on a UAV-assisted channel measurement system for constructing the CKM in real-world scenarios. Firstly, a three-dimensional (3D) CKM construction scheme for real-world scenarios is provided, which involves channel knowledge extraction, mapping, and completion. Secondly, an algorithm of channel knowledge extraction and completion is proposed. The sparse channel knowledge is extracted based on the sliding correlation and constant false alarm rate (CFAR) approaches. The 3D Kriging interpolation is used to complete the sparse channel knowledge. Finally, a UAV-assisted channel measurement system is developed and CKM measurement campaigns are conducted in campus and farmland scenarios. The path loss (PL) and root mean square delay spread (RMS-DS) are measured at different heights to determine CKMs. The measured and analyzed results show that the proposed construction scheme can effectively and accurately construct the CKMs in real-world scenarios.

Distributed Embedded System for Air Quality Monitoring based on Long Range (LoRa) Technology

This study addresses the persistent challenge of urban air quality deterioration through the introduction of the Distributed Embedded System (DES). In response to limitations associated with conventional air quality measurement methods, the DES system offers a cost-effective and portable alternative for real-time monitoring. The study focuses on implementing a low-cost distributed system and developing effective communication protocols between sensor nodes. Equipped with Metal Oxide Semiconductor (MOS) sensors for pollutant gases, optical sensors for particulate matter, and meteorological sensors, the system strategically deploys multiple nodes within a 4 km range of urban areas. Real-time AQI and pollution severity have been measured for various locations. Implementation of Long Range (LoRa) communication technology allows the sensor nodes to efficiently transmit data to a central base station. Observations of received signal strength and signal quality indicate reliable and effective communication. To validate accuracy and reliability, acquired DES system data undergoes comparative analysis with data from a government-established meteorological station, revealing a strong correlation. This innovative approach presents a promising solution for widespread, continuous, and cost-effective real-time air quality monitoring in urban areas. The DES system addresses key challenges associated with air pollution, offering a portable and accessible tool that could revolutionize urban air quality management.