Communication Links Research Articles

Maximizing energy-efficiency for RIS-UAV assisted mobile vehicles in cognitive networks

As an essential technology in the sixth generation of wireless communication, the reconfigurable intelligent surface (RIS) offers transformative solutions for the evolution of intelligent transportation. In the secondary network, RIS is equipped on an unmanned aerial vehicle (UAV) to establish a communication link between secondary base station (SBS) and secondary mobile vehicles (SMVs). At the same time, the communication within the secondary network must not interfere with the primary users (PUs) in the primary network. To achieve the optimal energy efficiency, we need to optimize the RIS passive beamforming, SMVs communication scheduling, SBS radiation power allocation and RIS-UAV trajectory. Since the original problem is difficult to solve, we use an alternating iteration framework to decompose the original problem into four subproblems and solve them with successive convex approximations (SCA). We have developed the CEEM scheme to compare it with benchmark schemes and demonstrate its superior performance, achieving up to a 43.48% improvement. In addition, RIS improves the communication quality by up to 57.53% in the simulation results, which have verified the correctness and effectiveness of the algorithm proposed in this paper.

Design and Implementation of Lightweight Certificateless Secure Communication Scheme on Industrial NFV-Based IPv6 Virtual Networks

With the fast growth of the Industrial Internet of Everything (IIoE), computing and telecommunication industries all over the world are moving rapidly towards the IPv6 address architecture, which supports virtualization architectures such as Network Function Virtualization (NFV). NFV provides networking services like routing, security, storage, etc., through software-based virtual machines. As a result, NFV reduces equipment costs. Due to the increase in applications on Industrial Internet of Things (IoT)-based networks, security threats have also increased. The communication links between people and people or from one machine to another machine are insecure. Usually, critical data are exchanged over the IoE, so authentication and confidentiality are significant concerns. Asymmetric key cryptosystems increase computation and communication overheads. This paper proposes a lightweight and certificateless end-to-end secure communication scheme to provide security services against replay attacks, man-in-the-middle (MITM) attacks, and impersonation attacks with low computation and communication overheads. The system is implemented on Linux-based Lubuntu 20.04 virtual machines using Java programming connected to NFV-based large-scale hybrid IPv4-IPv6 virtual networks. Finally, we compare the performance of our proposed security scheme with existing schemes based on the computation and communication costs. In addition, we measure and analyze the performance of our proposed secure communication scheme over NFV-based virtualized networks with regard to several parameters like end-to-end delay and packet loss. The results of our comparison with existing security schemes show that our proposed security scheme reduces the computation cost by 38.87% and the communication cost by 26.08%.

Graph Theoretical Models for Enhancing Highway Connectivity and Safety in Vehicular Networks

Vehicular networks play a crucial role in modern transportation systems, significantly impacting connectivity and safety on highways. This paper explores the application of graph theoretical models to enhance both connectivity and safety in vehicular networks. Graph theory, a branch of discrete mathematics, provides a robust framework for modeling and analyzing complex networks, including those formed by vehicles on highways. Our study begins by defining the vehicular network as a graph where nodes represent vehicles, and edges denote communication links between them. We employ various graph theoretical concepts such as connectivity, centrality, and network flow to evaluate and improve the network's performance. Key metrics, including the degree of nodes, clustering coefficients, and shortest path lengths, are utilized to quantify network connectivity and identify critical nodes and edges that influence overall network efficiency. One of the primary objectives is to ensure uninterrupted connectivity in the presence of dynamic and often unpredictable vehicular movement. To this end, we analyze the network's resilience to node failures and propose strategies to enhance robustness using redundancy and alternative routing paths. By incorporating concepts like k-connectivity and network diameter, we develop models that maintain high levels of connectivity despite the removal or failure of multiple nodes or edges. Safety is addressed through the lens of network stability and reliability. We investigate the impact of vehicular density, speed, and communication range on the network's ability to sustain reliable communication channels. Techniques such as dynamic topology management and adaptive power control are proposed to mitigate the risks associated with network fragmentation and communication delays. Furthermore, we introduce optimization algorithms that leverage graph partitioning and community detection to improve the management of vehicular clusters, facilitating efficient data dissemination and reducing the likelihood of congestion-related incidents. The proposed models are validated through simulations that mimic real-world highway conditions, demonstrating significant improvements in both connectivity and safety metrics. In conclusion, the application of graph theoretical models offers a promising approach to enhancing highway connectivity and safety in vehicular networks

Microstrip GPS Circular Antenna for Terrestrial Transportation Systems

In this paper, the design, implementation, and evaluation of a microstrip circular antenna is presented and analyzed. This antenna has two resonant frequencies, which are used in the Global Positioning System (GPS). The antenna was built in a low-cost Printed Circuit Board (PCB) with a FR-4 substrate. The top layer of the PCB includes two slots in the main circular patch, which normally is used in a single carrier reception. The radiation pattern of the antenna shows a wide main lobe in the vertical axis, intending to obtain line-of-sight communication links with five or more GPS satellites.

Methodology for the design of a nanosatellite telecommunication system in S-Band based on Software for Digital Mission Engineering

Abstract A trend in the development of nanosatellite platforms for technology demonstration has increased in both private industry and academic projects. Communication link design plays a crucial role in the success of space missions, enabling efficient and reliable data transmission between satellites and ground stations. In this context, the use of advanced tools such as System Tool Kit (STK) has gained significant importance by enabling a comprehensive analysis of the technical and operational aspects of the communication link. In an effort to make the future design of the communications subsystem payload on a nanosatellite more efficient and accessible, this paper shows a methodology for the efficient use of STK to perform link analysis.

Experimental realization of optical communication link with intensity degenerate orbital angular momentum beams

Experimental realization of optical communication link with intensity degenerate orbital angular momentum beams

Connecting quantum cities: simulation of a satellite-based quantum network

We present and analyze an architecture for a European-scale quantum network using satellite links to connect Quantum Cities, which are metropolitan quantum networks with minimal hardware requirements for the end users. Using NetSquid, a quantum network simulation tool based on discrete events, we assess and benchmark the performance of such a network linking distant locations in Europe in terms of quantum key distribution rates, considering realistic parameters for currently available or near-term technology. Our results highlight the key parameters and the limits of current satellite quantum communication links and can be used to assist the design of future missions. We also discuss the possibility of using high-altitude balloons as an alternative to satellites.

Correction of the GN Model for Fiber Optical Communication Links with Distributed Raman Amplification

Correction of the GN Model for Fiber Optical Communication Links with Distributed Raman Amplification

Анализ территориальной структуры хозяйства «Енисейская Сибирь»

The territorial structure of the economy is the basis on which the territorial organization of the economy is built, where the existing interrelations and interdependencies in a certain area are objectively reflected. Materials and methods. The methods of statistical analysis, as well as methods of data collection and processing were used in the work. The methodological basis for the study of territorial structure is the system approach. Results. The competitive advantages of the macro-region are its unique location on the territory of the country, while its weakness is the low level of development of transportation and communication links, which leads to an insufficient level of development of innovative developments. Discussion. Yenisei Siberia is an important part of the existing and projected transportation corridors linking Asia-Pacific countries with European countries. Conclusion. Thus, the territorial structure of the economy is a dynamically structured generalized system, for which it is necessary to search for adaptive approaches with spatial and temporal variability of interrelations optimizing the structural features of the economy depending on the inertia of the economy. Resume. The diversity of the complex of constituent parts of the territorial system, allows the system to be more stable and prone to socio-economic improvement. “Yenisei Siberia” consists of three subjects of the Federation, these are two national republics and one krai (krai – Krasnoyarsk and national republics – Tyva and Khakassia). Suggestions for practical applications and directions for future research. In connection with the turn to the East, the actualization of scientific research on the development of Yenisei Siberia may become a driver of interregional interactions, especially for regions with a low level of economic development. The results of the research may be useful in future development strategies and/or master plans of the territories of the Yenisei Siberia.

Simulation of Massive MIMO Antennas for Improved Link Throughput

Massive MIMO technology involves deploying multiple antennas on both ends of a communication link, which boosts spatial diversity and signal-to-noise ratio. By using multi-user MIMO transmission and techniques like spatial multiplexing and beamforming, it increases capacity, spectral efficiency, and data rates. Simulations conducted with tools like Octave software help engineers to optimize designs, predict system behavior, and assess the impact of antenna quantity on downlink throughput. This study addresses the increasing demand for high downlink data rates within modern communication networks. It explores the performance of Massive MIMO systems through simulations using Octave software, focusing on the quantity of antenna elements (M), and considering both spectral efficiency (SE) and data throughput. Results show higher M enhances both spectral efficiency and data rates. Efficiency dips at M=10, surges at M=40, and slowly, but steadily grows from M=50 to 100. Similar trends in data rates indicate M's impact on transmission performance. SE values range from 5.8442 bps/Hz (M = 10) to 24.1608 bps/Hz (M = 100), while data rates range from 116.8834 Mbps (M = 10) to 483.2158 Mbps (M = 100). These insights offer practical guidance for engineers and could facilitate the optimization of wireless communication setups and addressing the imperative for improved data rates. The study advances the understanding of Massive MIMO's potential, providing a roadmap for effectively leveraging its capabilities across diverse communication network scenarios.

Comparing the Performance of Optical Communication Links using G.652 and G.655 Fiber in Python Packages

This study investigates and compares the performance of a 10 Gbps optical communication link utilizing two prevalent single-mode fibers: G.652 and G.655. The analysis employs both theoretical calculations and Python-based simulations to assess the effectiveness of each fiber type in this high-speed transmission scenario. With the ever-growing demand for bandwidth in communication networks, 10 Gbps transmission systems are becoming increasingly commonplace. Single-mode fibers like G.652 and G.655 play a vital role in these systems, offering low signal attenuation for long-distance data transmission. However, each fiber type exhibits distinct dispersion characteristics, which can impact signal integrity over extended distances. This investigation adopts a two method for performance evaluation. Firstly, link power budget calculations are performed to determine the optical signal power before and after propagating through a 50-kilometer fiber span. The received power serves as the foundation for subsequent Q-factor and Bit Error Rate (BER) analysis. These calculations establish the theoretical limitations of the system based on well-defined formulas. Secondly, Python-based simulations are conducted to corroborate the theoretical findings and provide a more comprehensive performance assessment. This approach leverages the capabilities of two prominent Python packages: Opticomlib and OpticommPy. Opticomlib excels at analyzing the behavior of individual optical pulses within the system, enabling an understanding of the signal propagation. On the other hand, OpticommPy specializes in parameter sweep analysis, allowing for the investigation of how critical parameters like received power influence the Q-factor. By combining these functionalities, the simulations provide a detailed picture of the system's performance under various conditions. The calculated BER and Q-factor values for both G.652 and G.655 fiber links surpass the industry-accepted performance standards. These results demonstrate the effectiveness of using Python-based tools for comprehensive performance analysis of optical communication systems. However, it's important to note that slight discrepancies exist between the calculated and simulated results.

An adaptive MLP-based joint optimization of resource allocation and relay selection in device-to-device communication using hybrid meta-heuristic algorithm

Enhancement in both energy efficiency and spectral efficiency in cellular networks is made possible by means of an advanced technique called device-to device (D2D) communication. The enhancement of these efficiencies is done by utilizing the cellular user (CU) resources once again to make communication with nearby cellular devices in an effective manner by spectral means. As the D2D communication technology is capable of providing a direct communication link with nearby devices effectively with enhanced spectral efficacy, this approach is considered as an ideal solution for the futuristic cellular communication network. A flexible and reliable relay-assisted communication by means of D2D technology is required that acts as an intermediate relay when the attenuation between the channels across the D2D devices becomes high. The throughput of the system is increased by utilizing D2D communication technology as it uses direct data transmission within cellular devices. When the cellular user is far apart from one another, the data loss in the D2D communication system is minimized with the utilization of the relay. When the channels are good, then the relay nodes (RNs) serve the cellular user. However, it is noted that the D2D systems are affected by issues such as higher consumption of energy and spectral sharing. Also, the sum rate gets degraded as a result of mutual interference between resource-sharing cellular devices in the relay-assisted D2D communication system. The transmission of the data in a traditional relay-assisted D2D communication system is carried out between the D2D receiver (DR) and D2D transmitter (DT) only with the utilization of its own energy by the RN. The issues in relay selection and resource allocation in the conventional joint resource allocation schemes are tackled by executing a scheme for performing the task of optimal relay selection and joint resource allocation. The enhancement of the overall sum rate in the D2D communication is the main motive behind the implemented scheme. This goal is attained along with the minimization of the link rates in the cellular and D2D networks. The ideal selection of the relay and the execution of the joint resource allocation are done with the utilization of a new optimization scheme called the hybrid flow direction with the chameleon swarm algorithm (HFDCSA), in which the flow direction algorithm (FDA) is fused along with chameleon swarm algorithm. This optimal selection of the relays is assisted by considering constraints like the network’s sum rate and energy efficiency in the network to achieve high performance. The data obtained from distinct sources are given to the adaptive multi-layer perceptron (AMLP) in which optimal resource allocation and the relay selection are performed with the help of the suggested HFDCSA. The parameters in the MLP are tuned by the same HFDCSA. Finally, the performance validation is conducted in the stage to verify the working of the suggested approach.

Investigated Signal-to-Noise Ratio for Terrestrial Free Space Optical based on Libya Cities Data

Free Space Optical (FSO) communication links offer high-speed data transmission but can be affected by weather conditions like rain, haze, fog, and snow. This study investigates the impact of rain on FSO link availability in the Libyan cities of Garian, Elkhoms, and Tripoli. An empirical model based on the ITU Carb. (France) Model is proposed to predict FSO link availability for ranges up to 5 km. Rain data shows that Garian has the highest rainfall, followed by Elkhoms and Tripoli. The study examines the effects of rainfall on FSO link performance for these three cities over a 5 km link distance. The results show that signal-to-noise ratio (SNR) and received power at the FSO link are influenced by both rainfall and path length. For a 2 km link distance, the SNR ranges from 16 dB in Tripoli to 10 dB in Garian. Under the influence of rain, the SNR varies from 45 dB to 5 dB over a link distance of 1 km to 5 km.

CN+: Vehicular Dataset at Traffic Light Regulated Intersection in Bremen, Germany

Vehicular Ad-Hoc Networks (VANETs) were introduced to avoid vehicular-related accidents and to improve the safety of both vehicular passengers and other road users. In VANETs, the vehicles are expected to communicate with neighbouring vehicles to increase awareness about the surrounding by using V2V (vehicle-to-vehicle) communication links. Since the introduction of VANETs, much research has focused on developing state-of-the-art algorithms to increase safety. However, real-world testing of these developed algorithms has become challenging due to the required high cost and multiple practical reasons. Therefore, simulation-based testing is commonly used for VANETs related applications. Using real datasets inside a simulation can significantly increase the results’ accuracy and help to achieve realistic results. In this study, we present a dataset called ’CN+’, which consists of more than 25,000 vehicles collected over 32 hours at a signalized intersection in Bremen, Germany. paper

Social structure and clan group networks of Afar pastorals along the Lower Awash Valley

The study examined how Afar society’s clan structure and societal hierarchies were established. The links of customary law (maa’da) practices, traditional communication (dagu), and social networks (affehina) were found to be significant in the social structure for how members perform social interactions. A qualitative method was applied, which involved Key informant interviews, focused group discussions, and observation techniques as data-gathering tools. The data was interpreted using a thematic analysis technique. Accordingly, the study explored that the administrative and social structure of the society consisted of the sultanate, the clan, and youth social groups. Each social unit has its distinct functions. A clan is the highest and most territorially located social organization. In addition, it was identified that network ties would be more commonly used to depict member’s interactions within the clan’s network structure. However, the clan’s territory (dinto) is not changeable as the season changes. The customary law applications are identified as a system of governing and controlling the social structure, social interactions, anti-social behaviours, and clan networks, with no change and differences in contents and practices in all clan groups. Furthermore, the expansion of small cities gradual change to urban centres, economic inequalities, and recurrent drought resulted in the decline of traditional norms and mutual social trusts. As a result, the study concluded that to sustain the traditional knowledge and social structure in facilitating clan vital networks, implementing visible policies will benefit the society, the government, and stakeholders to plan out effective mechanisms to preserve the sociocultural worth of the Afar pastoral societies in particular and other social groups in the country in general.

Network Latency in Teleoperation of Connected and Autonomous Vehicles: A Review of Trends, Challenges, and Mitigation Strategies

With remarkable advancements in the development of connected and autonomous vehicles (CAVs), the integration of teleoperation has become crucial for improving safety and operational efficiency. However, teleoperation faces substantial challenges, with network latency being a critical factor influencing its performance. This survey paper explores the impact of network latency along with state-of-the-art mitigation/compensation approaches. It examines cascading effects on teleoperation communication links (i.e., uplink and downlink) and how delays in data transmission affect the real-time perception and decision-making of operators. By elucidating the challenges and available mitigation strategies, the paper offers valuable insights for researchers, engineers, and practitioners working towards the seamless integration of teleoperation in the evolving landscape of CAVs.

Mindfulness, Gut-Brain Axis, and Health-Related Quality of Life: The Paradigm of IBD Patients.

Health-related quality of life (HRQoL) is a comprehensive measure that evaluates an individual's well-being across physical, mental, and social dimensions. Enhancing HRQoL, particularly in individuals with chronic conditions like inflammatory bowel diseases (IBD), necessitates a holistic approach. Mindfulness, a scientifically supported strategy for managing anxiety, has shown promise in improving both physical and mental health. Its benefits may be partly explained through its effects on the gut-brain axis (GBA), a bidirectional communication link between the gastrointestinal system and the central nervous system. By exploring the interplay between mindfulness and the GBA, this study aims to uncover how these elements collectively influence HRQoL in both healthy individuals and those with IBD, offering insights into potential therapeutic pathways. A cross-sectional investigation involved 338 adults, including 50 IBD patients, utilizing validated Greek scales for Mindfulness (MAAS-15), Mediterranean Diet (14-MEDAS), and HRQoL (EQ-5D-5L). The questionnaire gathered demographic, anthropometric, and lifestyle data. Among healthy participants, EQ-5D-5L showed a moderate correlation with the MAAS-15 scale (r = 0.389, p < 0.05) and a low correlation with 14-MEDAS (r = 0.131, p < 0.05). IBD patients exhibited significantly lower mean EQ-5D-5L scores than healthy individuals (0.75 vs. 0.85, p < 0.05). MAAS-15 demonstrated a robust correlation (r = 0.414, p < 0.001) with EQ-5D-5L in IBD patients. Elevated mindfulness levels emerged as predictive factors for higher HRQoL in IBD patients (OR: 1.101, 95% CI: 1.008, 1.202, p < 0.05, compared to low mindfulness). In summary, factors influencing the GBA, including mindfulness and the Mediterranean diet, exhibit positive associations with HRQoL. Increased mindfulness levels predict better HRQoL in IBD patients, emphasizing the potential for clinical trials to validate these cross-sectional study findings.

Cloud–Fog Collaborative Computing Based Task Offloading Strategy in Internet of Vehicles

Vehicle terminals in the mobile internet of vehicles are faced with difficulty in the requirements for computation-intensive and delay-sensitive tasks, and vehicle mobility also causes dynamic changes in vehicle-to-vehicle (V2V) communication links, which results in a lower task offloading quality. To solve the above problems, a new task offloading strategy based on cloud–fog collaborative computing is proposed. Firstly, the V2V-assisted task forwarding mechanism is introduced under cloud–fog collaborative computing, and a forwarding vehicles predicting algorithm based on environmental information is designed; then, considering the parallel computing relationship of tasks in each computing node, a task offloading cost model is constructed with the goal of minimizing delay and energy consumption; finally, a multi-strategy improved genetic algorithm (MSI-GA) is proposed to solve the above task offloading optimization problem, which adapts the chaotic sequence to initialize the population, comprehensively considers the influence factors to optimize the adaptive operator, and introduces Gaussian perturbation to enhance the local optimization ability of the algorithm. The simulation experiments show that compared with the existing strategies, the proposed task offloading strategy has the lower task offloading cost for a different number of tasks and fog nodes; additionally, the introduced V2V auxiliary task forwarding mechanism can reduce the forwarding load of fog nodes by cooperative vehicles to forward tasks.

RL-ANC: Reinforcement Learning-Based Adaptive Network Coding in the Ocean Mobile Internet of Things

As the demand for sensing and monitoring the marine environment increases, the Ocean Mobile Internet of Things (OM-IoT) has gradually attracted the interest of researchers. However, the unreliability of communication links represents a significant challenge to data transmission in the OM-IoT, given the complex and dynamic nature of the marine environment, the mobility of nodes, and other factors. Consequently, it is necessary to enhance the reliability of underwater data transmission. To address this issue, this paper proposes a reinforcement learning-based adaptive network coding (RL-ANC) approach. Firstly, the channel conditions are estimated based on the reception acknowledgment, and a feedback-independent decoding state estimation method is proposed. Secondly, the sliding coding window is dynamically adjusted based on the estimates of the channel erasure probability and decoding probability, and the sliding rule is adaptively determined using a reinforcement learning algorithm and an enhanced greedy strategy. Subsequently, an adaptive optimization method for coding coefficients based on reinforcement learning is proposed to enhance the reliability of the underwater data transmission and underwater network coding while reducing the redundancy in the coding. Finally, the sampling period and time slot table are updated using the enhanced simulated annealing algorithm to optimize the accuracy and timeliness of the channel estimation. Simulation experiments demonstrate that the proposed method effectively enhances the data transmission reliability in unreliable communication links, improves the performance of underwater network coding in terms of the packet delivery rate, retransmission, and redundancy transmission ratios, and accelerates the convergence speed of the decoding probability.

Atmospheric turbulence recognition with deep learning models for sinusoidal hyperbolic hollow Gaussian beams-based free-space optical communication links

The integration of artificial intelligence technology to improve the performance of free-space optical communication (FSO) systems has received increasing interest. This study aims to propose a novel approach based on deep learning techniques for detecting turbulence-induced distortion levels in FSO communication links. The deep learning-based models improved and fine-tuned in this work are trained using a dataset containing the intensity profiles of Sinusoidal hyperbolic hollow Gaussian beams (ShHGBs). The intensity profiles included in the dataset are the ones of ShHGBs propagating for 6 km under the influence of six different atmospheric turbulence strengths. This study presents deep learning-based Resnet-50, EfficientNet, MobileNetV2, DenseNet121 and Improved+MobileNetV2 approaches for turbulence-induced disturbance detection and experimental evaluation results. In order to compare the experimental results, an evaluation is made by considering the accuracy, precision, recall, and f1-score criteria. As a result of the experimental evaluation, the average values for accuracy, precision, recall and F-score with the best performance of the improved method are given; average accuracy 0.8919, average precision 0.8933, average recall 0.8955 and average F-score 0.8944. The obtained results have immense potential to address the challenges associated with the turbulence effects on the performance of FSO systems.