Robust Communication System Research Articles

HF skywave communication for air-to-ground networks: A cooperative transmission framework

High-Frequency (HF) communication is widely used for long-distance transmission in remote and disaster areas. However, the dynamic nature of the ionosphere and multipath propagation in the HF channel pose significant challenges to designing efficient and robust communication systems. In this paper, we propose a Fixed Station (FS) and frequency matching method, as well as a power allocation method, to improve the sum-rate of air-to-ground HF communication networks. We derive optimal power allocation among users that share the same frequency, based on which a modified water-filling algorithm is used to solve the power allocation problem in multi-user scenarios, while a low-complexity algorithm is proposed to solve the integer optimization problem of frequency-FS matching. Simulation results demonstrate that the proposed algorithm outperforms the naive algorithm, indicating its effectiveness.

A Review of the Applications of Through-the-Earth (TTE) Communication Systems for Underground Mines

AbstractUnderground mining accidents have the potential of leaving miners trapped in unknown and life-threatening locations for an extended period of time. The lives of the trapped and unaccounted-for miners are at risk and require emergency rescue. But, the primary tracking systems are highly susceptible to damage during accidents and are most likely to be defunct and inoperable post-accident. This prompted the need for a robust and reliable post-accident communication and locator system. Subsequently, the through-the-earth (TTE) communication systems were developed and tested in underground mines. Under ideal conditions, these systems are capable of post-accident full-duplex two-way voice, text, and data communication and fingerprint detection of the geolocations of the trapped miners. This is achieved through a wireless link established by the transmission of electromagnetic and seismic waves between surface and underground, even in challenged underground environments. Unlike the primary tracking systems, the TTE communication systems do not require extensive shaft-to-workplace backbone infrastructure. This has made the TTE systems to be less susceptible to damage and therefore suitable for post-accident communication. Instead, the Earth’s crust acts as the signal transmission medium which forms an uplink and downlink communication path. This is achieved by injecting an electric current into the ground using electrodes, by transmitting magnetic fields from a radiating loop antenna, or by inducing fingerprint geolocations using seismic waves. Range and data rates are the critical requirements for the effectiveness of these systems and are dependent on factors such as the antenna design, frequency, and rock properties. This study provides a review of the applications of the different types of TTE communication systems, their evolution, factors that affect them, and techniques for improving their efficiencies and capabilities. These systems present the mining industry with an opportunity to improve safety by providing post-accident communication and locating trapped miners as quickly as possible. This will improve their survival chances and ultimately reduce fatality rates in the mining industry.

Road to Efficiency: V2V Enabled Intelligent Transportation System

Intelligent Transportation Systems (ITSs) have grown rapidly to accommodate the increasing need for safer, more efficient, and environmentally friendly transportation options. These systems cover a wide range of applications, from transportation control and management to self-driving vehicles to improve mobility while tackling urbanization concerns. This research looks closely at the important infrastructure parts of vehicle-to-vehicle (V2V) communication systems. It focuses on the different types of communication architectures that are out there, including decentralized mesh networks, cloud-integrated hubs, edge computing-based architectures, blockchain-enabled networks, hybrid cellular networks, ad-hoc networks, and AI-driven dynamic networks. This review aims to critically analyze and compare the key components of these architectures with their contributions and limitations. Finally, it outlines open research challenges and future technological advancements, encouraging the development of robust and interconnected V2V communication systems in ITSs.

Behind the Door: Practical Parameterization of Propagation Parameters for IEEE 802.11ad Use Cases

The integration of the 60 GHz band into the IEEE 802.11 standard has revolutionized indoor wireless services. However, this band presents unique challenges to indoor wireless communication infrastructure, originally designed to handle data traffic in residential and office environments. Estimating 60 GHz signal propagation in indoor settings is particularly complicated due to dynamic contextual factors, making it essential to ensure adequate coverage for all connected devices. Consequently, empirical channel modeling plays a pivotal role in understanding real-world behavior, which is characterized by a complex interplay of stationary and mobile elements. Given the highly directional nature of 60 GHz propagation, this study addresses a seemingly simple but important question: what is the impact of employing highly directive antennas when deviating from the line of sight? To address this question, we conducted an empirical measurement campaign of wireless channels within an office environment. Our assessment focused on power losses and distribution within an angular range while an indoor base station served indoor users, simulating the operation of an IEEE 802.11ad high-speed WLAN at 60 GHz. Additionally, we explored scenarios with and without pedestrian movement in the vicinity of wireless terminals. Our observations reveal the presence of significant antenna lobes even in obstructed links, indicating potential opportunities to use angular combiners or beamformers to enhance link availability and the data rate. This empirical study provides valuable information and channel parameters to simulate 60 GHz millimeter wave (mm-wave) links in indoor environments, paving the way for more efficient and robust wireless communication systems.

Performance analysis of hybrid combining schemes under Middleton class‐A and SαS${\rm S}\alpha{\rm S}$ impulsive noise model

AbstractImpulsive noise poses a significant challenge to single input multiple output wireless communication systems. This paper assesses the effectiveness of hybrid combining techniques, namely selection combining‐equal gain combining and selection combining‐maximal ratio combining, in mitigating impulsive noise impact caused by both man‐made and natural phenomena. The evaluation considers three different noise models: Additive white Gaussian noise, Middleton class‐A impulsive noise, and symmetric alpha stable impulsive noise, across Rayleigh and Rician fading channels. Bit error rate is employed to gauge channel performance. Our research contribution lies in the comprehensive assessment of hybrid combining techniques under diverse noise models, addressing a critical research gap in wireless communication. Findings indicate that impulsive noise has a more pronounced impact on channel performance than additive white Gaussian noise, and hybrid combining techniques prove more effective in mitigating these effects. The results hold significant implications for single input multiple output wireless communication systems, guiding the development of more robust and reliable communication systems in impulsive noise scenarios.

Harnessing the power of ML for robust SISO and MIMO FSO communication systems in fog weather

This study examines Free Space Optical (FSO) communication’s performance in different fog conditions, focusing on Single-Input Single-Output (SISO) and Multiple-Input Multiple-Output (MIMO) setups. In low fog, SISO handles signal degradation well. MIMO improves link robustness in moderate fog. High fog challenges traditional FSO, leading to ML integration to optimize communication parameters. For weather channel classification, a preprocessing scheme reduces features from 12 to 2 given that the 12 features are Bit Error Rate (BER), Quality Factor (Q-factor) and Received Optical Power (ROP) for different 4 users. A Gaussian Process Classifier (GPC) achieves an accuracy greater than 99%, surpassing SVM, Decision Tree, and Random Forest. GPC’s fit and predict functions execute in 0.15 s, outperforming NuSVM (0.2 s). This study highlights FSO, SISO, MIMO, and Machine Learning (ML) practicality in enhancing communication resilience in adverse weather, especially in fog-prone areas.

Low-Cost, Open-Source, Experimental Setup Communication Platform for Emergencies, Based on SD-WAN Technology

The rapid advancement of communication technologies underscores the urgent need for robust and adaptable emergency communication systems (ECSs), particularly crucial during crises and natural disasters. Although network-based ECSs have been extensively studied, integrating open-source technologies, such as software-defined wide area networks (SD-WAN) with private long-term evolution (LTE) base stations, is a relatively unexplored domain. This study endeavors to fill this gap by introducing an experimental ECS platform that utilizes a hybrid network, incorporating a VoIP network to enhance open-source and on-premises communications in targeted areas. Our hypothesis posits that a hybrid network architecture, combining SD-WAN and private LTE, can substantially improve the reliability and efficiency of ECSs. Our findings, supported by the open-source OMNeT++ simulator, illuminate the enhanced communication reliability of the network. Moreover, the proposed platform, characterized by autonomous wireless 4G/LTE base stations and an Asterisk VoIP server, demonstrates improved quality of service (QoS) and quality of experience (QoE), with minimal data loss. This research not only has immediate practical applications but also bears significant implications for the development of cost-effective, open-source communication networks, optimized for emergencies, critical infrastructure, and remote areas.

Steganographic Techniques for High-Capacity Covert Communication in Images and Videos

Abstract: This paper investigates advanced steganographic techniques tailored for high-capacity covert communication within images and videos. Traditional approaches are limited by low embedding capacity and susceptibility to detection. To address these challenges, cutting-edge methods including adaptive embedding algorithms, content-aware techniques, and deep learningbased approaches are explored. The research emphasizes the importance of balancing embedding capacity, security, and perceptual quality. It also discusses steganalysis implications and strategies for mitigating detection risks. By reviewing existing literature, this paper offers insights into state-of-the-art steganography for covert communication. Understanding these methods enables the development of more robust and secure communication systems to meet evolving challenges in information security and privacy.

Emergency Communication System for Hills and Forest Region Using IOT

This project presents an innovative approach to establishing robust communication systems in remote areas devoid of traditional network infrastructure. By harnessing the power of IoT and LoRa technology, the project proposes a Long Distance Communication System that not only facilitates connectivity but also supports critical emergency evacuation procedures. The cornerstone of this system is the LoRa Mesh Library, which enables a decentralized network topology, ensuring seamless communication even in the most challenging environments via ad hoc network. The project further explores QoS routing and traffic scheduling within 802.11 wireless mesh networks to guarantee consistent and quality communication links over long distances. Additionally, it integrates Secure IT, a security framework utilizing Firebase, Google Map, and Node.js, to provide real-time location-based alerts, enhancing the safety of individuals in emergency situations.Thisabstractencapsulatestheproject’smultifacetedapproach to overcoming the limitations of current communication infrastructures, offering a scalable, secure, and efficient solution that has the potential to revolutionize connectivity in isolated regions worldwide.

Optimal and distributed energy management in interconnected energy hubs

Recently, multi-carrier energy systems (MCESs) have been rapidly developed as flexible multi-generation systems aiming to satisfy load demands by purchasing, converting, and storing different energy carriers. This study specifically focuses on the optimal and robust large-scale coordination of interconnected energy hubs (IEHs) in an iterative consensus-based procedure considering distribution network losses. Furthermore, a new robust-based hybrid IGDT/consensus algorithm is introduced to achieve risk-averse optimal energy management in IEHs under uncertainty. The fast convergence, needless to collect the total information from all hubs, minimal computational burden, and more robust communication system are the most important features of the proposed distributed consensus algorithm in this study. The effectiveness of the proposed consensus algorithm is verified by simulation results considering various energy trading structures in IEHs at different scales. The obtained results highlight the scalability capability of the proposed method. Regarding an IEHS of 30 energy hubs, the computation burden is lightened by 0.53 (s) and 0.1917 (s), respectively with and without uncertainty. Considering distribution network losses, the total purchasing costs can be increased by 8%. The simulation results also reveal an increase of 11% in the total power trading under the uncertainty.

Rigorous Security Analysis of RabbitMQ Broker with Concurrent Stochastic Games

Modern Internet of Things architectures encompass various computational logic and communication protocols. However, the security issues inherent in these systems pose significant risks, especially at the device edges. Addressing security threats on the deployed communication edges is imperative to ensure a robust and secure communication system. In this study, we propose an approach that utilizes the Concurrent Stochastic Game model (CSG) to specify the behavior of RabbitMQ Broker in the context of IoT systems precisely while considering potential data corruption attacks. For parametrizable evaluation, these attacks and their frequencies are learned. We implement the CSG model in PRISM games for automated analysis, leveraging reward Probabilistic Alternating Temporal Logic (rPATL) to model security requirements as game goals. Empirical validation of the work is presented via an industrial case study that shows how data corruption attacks can impact the sensed data in water dam infrastructure. This assessment gives valuable insights into the RabbitMQ deployment at the edge.

Optimizing Distribution System Resilience in Extreme Weather Using Prosumer-Centric Microgrids with Integrated Distributed Energy Resources and Battery Electric Vehicles

Electric power networks face vulnerabilities from various hazards, including extreme weather and natural disasters, resulting in prolonged outages and service disruptions. This paper proposes prosumer-centric networked electrical microgrids as a solution. EMGs integrate DERs, like SPV panels, WTs, BESSs, and BEVs, to form autonomous microgrids capable of operating independently during grid disruptions. The SMA was used to identify the appropriate allocation of DERs and BEVs to improve the resilience of the system. Prosumers, acting as both producers and consumers, play a crucial role by generating and sharing electricity within the microgrid. BEVs act as mobile energy storage units during emergencies. Load management and demand response strategies prioritize the energy needs for essential facilities, ensuring uninterrupted operation during adverse weather. Robust communication and control systems improve the emergency coordination and response. The resilience analysis focused on two case studies: moderate and severe damage, both under varying weather conditions. Simulations and experiments assessed the microgrid performance with different levels of DERs and demand. By testing on the IEEE 69-bus RDS, evaluated the EMGs’ strengths and limitations, demonstrating their potential to enhance distribution grid resilience against natural disasters.

On UAV Terrestrial Connectivity Enhancement through Smart Selective Antennas

Nowadays, Unmanned Aerial Vehicles (UAVs) are widely used in heterogeneous contexts and, thanks to a continuous technological evolution, are going to be used for several applications such as, for example, Beyond Visual Line of Sight (BVLOS) operations. Since in BVLOS flights the UAV and the ground control center may not have a direct visibility with each other, a robust communication system is needed to provide reliable connectivity. Although a cellular (4G/5G) network is the current best candidate to enable BVLOS applications, there are still some limitations to overcome, as 4G (LTE) and 5G (NR) cellular networks are natively designed for terrestrial use. In this paper, we first investigate current cellular communication limitations for UAV-based applications, in particular taking into account both results available in the literature, as well as experimental performance campaigns. Then, a viable solution for mitigating these drawbacks exploiting selective on-board antennas is proposed, whose performance is experimentally investigated with a preliminary prototypical architecture.

A mathematical analysis of teleoperator optimization using multiple sensors

As the role of remote vehicle operation gains prominence, ensuring robust wireless communication systems is crucial. Prior studies have delved into various aspects of vehicle teleoperation, including its legal framework and workforce implications. Some have even formulated models to estimate the number of remote operators for large automated vehicle fleets. These models suggest that automated vehicles overseen by remote operators could supplant a significant portion of current driving jobs in the United States. Such findings underscore the need for governmental review and policy adjustment to better accommodate the burgeoning field of teleoperation, which could substantially accelerate the advancement of vehicle automation. The present study focuses on evaluating the reliability of a bi-directional communication channel based on key variable parameters. This assessment aids in determining the optimal parameter settings, thereby enhancing the effectiveness of teleoperation systems.

Assessment of 5G Connectivity for UAV Operations in Urban Environments: An Analysis of Network Performance and UAV Communication Architecture

This article presents an in-depth analysis of the integration of 5G connectivity for unmanned aerial vehicle (UAV) operations in urban environments, focusing on network performance and the architectural framework necessary for optimal UAV communication. As UAVs become increasingly prevalent in urban applications, from surveillance to delivery services, the demand for robust and reliable communication systems has become paramount. This study explores the unique challenges posed by urban settings, such as signal obstruction and high-density network traffic, and examines how 5G technology offers solutions through advanced features like beamforming. By detailing the setup and evaluation of a UAV communication architecture that incorporates 5G modules, including the use of the NVIDIA Jetson AGX Orin Developer Kit for real-world testing, this article highlights the significant improvements in data rate, latency, and reliability achieved with 5G networks compared to traditional communication technologies. The findings underscore the transformative potential of 5G connectivity in enhancing UAV operational efficiency and reliability in complex urban landscapes. Through case studies and practical insights, the article also provides a glimpse into the future of urban UAV applications, paving the way for further research and development in this dynamic field.

Enhancing local governance in Nepal through federalism: A study of key elements

Federalism and local governance are mutually inclusive and complementary at times but they are different concepts. It involves multiple aspects such as national, political, legislative, institutional, and fiscal dimensions. Federal processes have the potential to influence and shape local governance. The purpose of this study is to investigate the elements of federalism that can improve local governance in Nepal. A descriptive and analytical research design was employed to collect data from 384 respondents via a questionnaire for analysis. While the elements of federalism for enhancing local governance were found to be satisfactory, the study highlights the inadequacies in its implementation. The findings provide valuable insights into Nepal's federalism policy and offer guidelines to policymakers for improving local governance. Additionally, the study emphasizes the need for appropriate policies, robust communication, and information systems to support the federalism process from the federal government.

WIRELESS TRAFFIC AND ROUTING ENHANCEMENT USING EMPEROR PENGUIN OPTIMIZER GUIDED BY CONDITIONAL GENERATIVE ADVERSARIAL NETS

The escalating demand for efficient wireless communication systems has prompted researchers to explore innovative solutions to optimize traffic flow and routing. The existing wireless communication infrastructure faces challenges such as congestion, latency, and suboptimal routing, impeding the seamless transmission of data. Traditional optimization approaches fall short in adapting to dynamic network conditions, necessitating the exploration of advanced methodologies. Despite recent advancements in optimization techniques, a notable research gap exists in the integration of bio-inspired algorithms like the Emperor Penguin Optimizer with machine learning models such as Conditional Generative Adversarial Nets for the purpose of wireless traffic and routing enhancement. Bridging this gap is crucial for achieving adaptive and robust wireless communication systems. This study addresses the challenges posed by the dynamic nature of wireless networks, aiming to enhance their performance through the synergistic application of the Emperor Penguin Optimizer (EPO) and Conditional Generative Adversarial Nets (CGANs). This research leverages the inherent strengths of the EPO, inspired by the collective foraging behavior of emperor penguins, to dynamically optimize the wireless network parameters. Concurrently, CGAN are employed to intelligently learn and adapt routing strategies based on real-time network conditions. The symbiotic integration of these two methodologies creates a powerful framework for adaptive wireless traffic and routing. The results indicate a significant improvement in traffic flow, reduced latency, and optimized routing paths in comparison to conventional methods. The EPO-CGAN framework demonstrates adaptability to varying network conditions, showcasing its potential to revolutionize wireless communication systems.

Tunable all-optical microwave logic gates based on nonreciprocal topologically protected edge modes

All-optical logic gates have been studied intensively owing to their potential to enable broadband, low-loss and high-speed communications. However, poor tunability has remained a key challenge in this field. In this work, we propose a Y-shaped structure composed of Yttrium Iron Garnet (YIG) layers that can serve as tunable all-optical logic gates, including, but not limited to, OR, AND and NOT gates, by applying external magnetic fields to magnetize the YIG layers. Our findings reveal that these logic gates are founded on protected one-way edge modes, where by tuning the wavenumber k of the operating mode to a sufficiently small (or even zero) value, the gates can become nearly immune to nonlocal effects. This not only enhances their reliability but also allows for maintaining extremely high precision in their operations. Furthermore, the operating band itself of the logic gates is also shown to be tunable. We introduce a straightforward and practical method for controlling and switching these gates between "work", "skip", and "stop" modes. These findings have potentially significant implications for the design of high-performance and robust all-optical microwave communication systems.

Unveiling the Nuances of Human Interaction within Organizational Settings

Purpose: The primary purpose of this research is to explore the intricate dynamics of human interaction in organizational contexts, focusing on communication, teamwork, leadership, and organizational culture. By comprehensively examining these aspects, the study seeks to uncover how they collectively impact organizational effectiveness and individual satisfaction. Research Design and Methodology: The methodology involves a qualitative literature review, integrating data from various academic sources, including journals and books. The research utilizes systematic search strategies, rigorous inclusion and exclusion criteria, and qualitative content analysis to ensure a comprehensive synthesis. Findings and Discussion: The study reveals that effective communication is pivotal in maintaining operational efficiency and fostering a positive work environment. Leadership styles significantly influence workplace dynamics, affecting everything from decision-making processes to employee morale. Teamwork and organizational culture are identified as crucial elements that contribute to the overall health and productivity of organizations. Implications: The findings suggest practical applications for organizational leaders aiming to enhance workplace interactions and organizational policies. Recommendations include investing in leadership development, fostering a collaborative culture, and implementing robust communication systems to improve engagement and productivity. Theoretical contributions include a deeper understanding of the interplay between individual behaviors and organizational structures, offering a foundation for future research in organizational behavior.

A prefix‐based approach for joint Doppler and channel estimation in underwater communication

SummaryDeveloping a reliable and robust underwater acoustic communication system is a difficult task due to the complicated nature of the underwater channel, non‐stationary noise, and several other factors. Indeed, channel estimation or equalization presents numerous challenges in this non‐stationary, highly Doppler, multipath environment; as a result, traditional equalizers and PLL‐based methods have limited performance. Generally, communication over such time‐varying channels is accomplished via packets that contain a prefix/preamble signal for training, a payload containing the actual data, and a silent period for proper alignment. The prefix signal must be designed properly because it is used to estimate the channel and determine the start of the packet. In this paper, we propose a new prefix signal based on the hyperbolic chirp signal, which has Doppler invariance properties. These properties enable the extraction of the entire packet even under severe multipath and Doppler. Our new proposed prefix signal can accurately and efficiently characterize an underwater channel by estimating the multipath delay, amplitude, and Doppler scales. Our new method has been validated through extensive simulations using various channel models for its robustness and effectiveness under various conditions. It has also been tested on a real‐world channel.