Communication Outage Research Articles

Investigating war crimes in de-occupied territories: the role of the National Police of Ukraine

The purpose of this article is to examine the specific activities of the National Police of Ukraine in the investigation of war crimes in de-occupied territories, developing a clear algorithm of action and taking into account possible power, heating, and communication outages. The study argues for the creation of a Coordination Headquarters to ensure proper interaction between the bodies and departments involved in recording and investigating war crimes. The article proves that the activities of the National Police of Ukraine bodies and units during the investigation of war crimes in the de-occupied territories are aimed at their prompt, complete, and impartial investigation, so that any perpetrator of such acts is held accountable according to their guilt, and includes several algorithmic actions. The research methodology includes dialectical-materialistic, formal-logical, general scientific, and special methods. The results of the study are significant as they provide a practical guide for the National Police of Ukraine in the investigation of war crimes in de-occupied territories. The proposed algorithm and practical considerations can help ensure prompt, complete, and impartial investigations, ultimately contributing to the rule of law and justice in times of conflict.

Enhancing the driving experience of smart city users based on content delivery framework for intelligent transportation systems

Integration of several communication technologies that facilitate user access contributes to the rapid development of the smart city notion. Intelligent transportation systems (ITS) are introduced as part of smart city development to provide drivers with enhanced communication and information-sharing capabilities. The article introduces a novel ITS content delivery framework (CDF) that addresses communication outage issues. CDF-ITS uses End-to-end decision-making system modelling to examine factors such as communication, content distribution, and vehicle features. A suitable communication slot for vehicular users is determined by processing these characteristics based on outage time and variables. By allocating time-aware communication slots according to the classification of the propagation factor, outage problems may be reduced. End-to-end decision-making is used for classification and vehicle attribute balance, allowing immediate responses to user requests. The experimental outcomes show that the latency of 0.297 s, outage time of 0.0837, distributed messages of 276, and computing complexity of 11.87 are used to assess the proposed framework's efficiency across vehicle density and velocities.

Joint Collaborative Big Spectrum Data Sensing and Reinforcement Learning Based Dynamic Spectrum Access for Cognitive Internet of Vehicles

Cognitive Internet of Vehicles (CIoV) is an intelligent vehicle network envisioned to opportunistically access spectrum licensed to primary users (PUs) on the premise of not interrupting their normal communications. Dynamic spectrum access enables the CIoV to choose the best possible spectrum for communications based on the outcomes of spectrum data sensing, which can improve the spectrum access performance effectively. In this paper, we enable the CIoV to adapt to various spectrum states through: a) a collaborative big spectrum data sensing scheme to sense a massive amount of spectrum data; and b) a reinforcement learning (RL) based dynamic spectrum access scheme to optimize spectrum selection strategies. Q-learning, which is a popular RL approach, is proposed for underlay, overlay, and collaborative spectrum access modes to allocate spectrum resources to the CIoV intelligently. The Q-learning models, which include the spectrum state vector, the action vector of CIoV, and the spectrum access reward received in different spectrum situations, are defined for the spectrum access modes. A Q-learning based spectrum access algorithm is proposed to improve the communication performance of the CIoV in different spectrum access modes. Simulation results indicate that the collaborative spectrum access mode can achieve higher average throughput, lower interference power and lower communication outage compared with the underlay and overlay spectrum access modes.

Mixed-Reality-Based Teleoperation Grasping Control

Abstract Traditionally, teleoperation means that the system sends a series of signal commands from the master while the slave manipulator receives and realizes the desired control operations. For the purpose of implementing more dexterous and complex tasks, we propose a novel framework with dual-hand master teleoperation systems under time-varied delays. In this paper, we emphasize studying the bilateral grasping teleoperation control, as the time delay causes a communication outage. Combining a wave-variable structure with a four-channel framework, an event-trigger-based bilateral sliding mode teleoperation control and an adaptive neural network are designed to effectively achieve master-slave trajectory tracking. In the virtual 3D environment, we created a mixed-reality interface based on dual-hand master teleoperation control that effectively responded to the two Omni manipulators' position transformation of the virtual manipulator. The time delay between the real slave force feedback and the virtual interface is addressed by designed event-trigger-based control in order to efficiently reduce the impact of time communication outage. The system's stability is analyzed and robot experiments are performed. From the experimental results, the telepresence platform innovatively applied virtual force feedback to reveal the soft target grasping and to accurately estimate the interactive force, enabling sensorless force feedback control.

(Vehicle’s YB)-based LPB prediction model and anti-LPB (communication link)-reconstruction strategy in the (VLC/RF)-V2X network

The hybrid vehicle-to-everything (V2X) network based on visible light communication (VLC) and radio frequency (RF) ((VLC/RF)-V2X Network) can provide a stable communication network to vehicles. It has great development forward. However, light path blocking (LPB) is a major problem for vehicular visible light communication (V-VLC). It can cause serious communication outage because the visible light signal cannot penetrate opaque obstacles. In view of this, a (vehicle’s yielding behavior (YB))-based LPB prediction model and an anti-LPB (communication link)-reconstruction strategy in the hybrid network are firstly proposed. At first, based on vehicles’ yielding behavior, a LPB prediction model is constructed. By this model, LPB can be predicted before the VLC link is blocked. Next, based on the prediction result of the model, a strategy of restructuring communication links is present. By this strategy, communication links can be self-adaptive changed or supplemented. Then, based on the proposed model and strategy, the anti-LPB scheme is finished. By the scheme, LPB can be avoided timely, communication outages and redundant handovers can be reduced effectively. Finally, by simulations, the model’s validity and the scheme’s effectiveness have been demonstrated. Through LPB prediction and link reconstruction, the proposed scheme avoids LPB caused by user-behavior blockage at source for the first time in multiple road regions. And it has the comparative advantages of faster response time and lower handover number. Compared with other methods, the average advance time of handovers is improved by 66.94% and the average handover number of the network is reduced by 68.48%. What’s more, the path loss (PL) caused by LPBs is reduced by 92% on average.

Polar Cap Patches Scaling Properties: Insights from Swarm Data

Among the effects of space weather, the degradation of air traffic communications and satellite-based navigation systems are the most notable. For this reason, it is of uttermost importance to understand the nature and origin of ionospheric irregularities that are at the base of the observed communication outages. Here we focus on polar cap patches (PCPs) that constitute a special class of ionospheric irregularities observed at very high latitudes in the F region. To this purpose we use the so-called PCP flag, a Swarm Level 2 product, that allows for identifying PCPs. We relate the presence of PCPs to the values of the first- and second-order scaling exponents and intermittency estimated from Swarm A electron density fluctuations and to the values of the Rate Of change of electron Density Index (RODI) for two different levels of geomagnetic activity, over a time span of approximately 3.5 years starting on 16 July 2014. Our findings show that values of RODI, first- and second-order scaling exponents and intermittency corresponding to measurements taken inside PCPs differ from those corresponding to measurements taken outside PCPs. Additionally, the values of the first- and second-order scaling exponents and of intermittency indicate that PCPs are in a turbulent state. Investigation of the coincidence of loss of lock (LoL) events with PCPs displayed that approximately 57.4% of LoLs in the Northern hemisphere and 45.7% in the Southern hemisphere occur in coincidence of PCPs when disturbed geomagnetic activity is considered. During quiet geomagnetic conditions these percentages decrease to 51.4% in the Northern hemisphere and to 20.1% in the Southern hemisphere.

Covert Wireless Communication Against Jamming-Assisted Proactive Detection

In this paper, we consider the covert wireless communication (CWC) against a jamming-assisted proactive detector in two scenarios corresponding to whether Alice utilizes the jamming to hide the communication signals. Specifically, for the both scenarios, we first obtain Alice’s communication strategy by exploiting the statistic channel state information (CSI) of the detecting link. Then, we propose the covertness outage probability (COP) as a new covert communication measure proposed in this letter and derive its closed-form expression which indicates that the lower tolerance value or the longer channel uses are likely to cause communication outage. Numerical results indicate that, against a jamming-assisted proactive detector, hiding the communication signals in the noise is more favorable than exploiting the detector’s jamming for achieving covertness, since the latter raises the transmit power at Alice and thus leads to larger COP.

Application of Wireless Magnetic Sensors in the Urban Environment and Their Accuracy Verification.

In a smart city, sensors are essential elements-the source of up-to-date traffic information. This article deals with magnetic sensors connected to wireless sensor networks (WSNs). They have a low investment cost, a long lifetime, and easy installation. However, it is still necessary to disturb the road surface locally during their installation. All road lanes to and from the city center of Žilina have sensors that send data at five-minute intervals. They send up-to-date information about the traffic flow's intensity, speed, and composition. The LoRa network ensures the data transmission, but in the event of failure, the 4G/LTE modem realizes the backup transmission. The disadvantage of this application of sensors is their accuracy. The research task was to compare the outputs from the WSN with a traffic survey. The appropriate method for the traffic survey on the selected road profile is a video recording and speed measurement using the Sierzega radar. The results show distorted values, mainly for short intervals. The most accurate output from magnetic sensors is the number of vehicles. On the other hand, traffic flow composition and speed measurement are relatively inaccurate because it is not easy to identify vehicles based on dynamic length. Another problem with sensors is frequent communication outages, which cause an accumulation of values after the outage ends. The secondary objective of the paper is to describe the traffic sensor network and its publicly accessible database. In the end, there are several proposals for data usage.

Performance Analysis of MIMO-mQAM System with Pointing Errors and Beam Spreading in Underwater Málaga Turbulence Channel

Both the long-term beam spreading caused by ocean turbulence and the pointing errors induced by the jitter of transmitters and receivers degrade the performance of underwater wireless optical communication (UWOC) links. To effectively alleviate their effects, an in-depth study was carried out over the Málaga turbulence channel with pointing errors and beam spreading in multiple-input and multiple-output (MIMO) UWOC. First, we analyzed the long-term beam spreading and the received light power for the finite receiving aperture in the presence of pointing error displacements. Based on this, the relationship between beam spreading, pointing errors, and signal power was established. Second, the approximate expressions of the average bit error rate (BER) and the communication outage probability were derived theoretically for this MIMO system using maximal-ratio combining (MRC) diversity. Third, the effects of the pointing errors on the coding and the diversity gains were explored for the MIMO links. Finally, using the observed ocean data from the Global Ocean Argo gridded dataset, we numerically verified the combined effects of ocean turbulence strength, beam spreading, and pointing errors on the average BER and outage probability of this system. These results also proved that adjusting the size of the receiving aperture or the order of the multiple quadrature amplitude modulation (mQAM) could effectively mitigate their effects.

Characterization of Transient Communication Outages Into States to Enable Autonomous Fault Tolerance in Vehicle Platooning

The benefits of platooning, e.g., fuel efficiency, road throughput enhancement, driver offload, etc., have sparked an interest in a more connected, intelligent, and sustainable transportation ecosystem. However, efficient platooning is realized through wireless communications, characterized by transient connectivity, which is caused by occasional packet losses. Being a safety-critical system of systems, a platoon must be fail-operational even during transient connectivity. Moreover, a platoon should be capable of transitioning into a fail-safe state upon encountering a hazard. To this end, we propose a strategy for classifying the transient communication outages incurred by platooning vehicles into states. Furthermore, a state machine using these states to enable safe automated platooning is proposed that also defines the transitions between the states based on the nature and levels of transient connectivity and hazards. To achieve this, a graceful degradation and upgradation method is proposed, such that the platoon can remain fail-operational by adjusting, e.g., the automated controller and/or the inter-vehicle gaps based on the current communication quality. An emergency braking strategy is also proposed to enable a fast transition into a fail-safe state, should the platoon encounter a hazard. Rigorous simulation studies show that the proposed strategies enable fault-tolerant automated platooning also during transient connectivity.

Rate-Splitting Multiple Access-Based Satellite–Vehicular Communication System: A Noncooperative Game Theoretical Approach

Rate-Splitting Multiple Access (RSMA) has recently found favor in high-mobility scenarios due to the benefits of relaxing the accuracy of Channel State Information at the Transmitter (CSIT) while maintaining high spectral efficiency. These benefits are particularly important in Satellite-Vehicular Networks (SVNs), where the mobility of the vehicles significantly affects the estimation accuracy of the CSIT. To tackle this challenge, we propose an RSMA-based satellite-vehicular communication system for reliable data transmission. Specifically, we investigate the outage probability of the RSMA-based satellite-vehicular communication system under the Shadowed-Rician model. Considering the satellite-vehicular communication outage problem, an optimization problem is formulated to maximize the Weighted Sum Rate (WSR) of the communication system. However, due to communication overhead and privacy concerns, not all vehicles are willing to participate in interference management. In this study, we exploit an incentive mechanism to efficiently solve this problem. Specifically, we formulated a non-cooperative game to motivate users to report the CSIT and participate in the power allocation. In addition, we have proved the existence and uniqueness of Nash Equilibrium (NE) in the game formulated. Our simulation results show that the proposed non-cooperative game theoretical approach achieves the effectiveness of the RSMA-based satellite-vehicular system. The game theoretical framework is shown to motivate users to participate in interference management, so as to maximize their transmission rates.

Outage probability minimization for vehicular networks via joint clustering, UAV trajectory optimization and power allocation

In this paper, we consider the vehicular uplink communication scenario where vehicles in the same lane travel in a direction within the coverage of the base station. Due to the long communication distance and poor signal quality at the cell edge, an unmanned aerial vehicle (UAV) is used as a mobile relay to improve the communication quality. Our goal is to minimize the communication outage probability by jointing vehicle clustering with UAV trajectory optimization and power allocation of each node. Since the cluster head position, UAV position and power of each node are coupled, the primary complex problem is divided into three sub-problems namely vehicle clustering, trajectory optimization and power allocation. Firstly, the improved K-means clustering algorithm is used for vehicle clustering by addressing the minimum–maximum distance criterion. In order to adapt to the changing network topology, the cluster head vehicle is determined dynamically. Then the joint Lagrangian gradient ascent method is used to determine the UAV position and the power of each vehicle through alternate iterations. The simulation results show that the proposed joint optimization scheme (J-CTOPA) is better than the equal power scheme with fixed relay position (FR-EP) and the power allocation scheme with cruise relay trajectories (CT-PA). The results also show that faster convergence and stronger stability can be achieved while the outage probability is reduced.

Outage Performance of Multi-relay System with Energy Harvesting and Storage

<p>This paper analyzes the performance of a two-hop half-duplex multi-relay system based on energy harvesting. The relay has energy harvesting and storage functions, and adopts an adaptive AF/DF transmission strategy and PS protocol. Based on three relay selection schemes, namely Energy Optimal Selection (EOS), Channel Gain Optimal Selection (GOS), and Energy and Channel Gain Optimal Selection (EGOS), the outage performance is compared. First, the finite state Markov chain (FSMC) is used to model the energy arrival and use status of each relay, and the energy transfer steady-state matrix is obtained. Then we use the Gauss Chebyshev formula to derive the analytical expression of the communication outage probability (COP). Finally, an optimization model for minimizing the COP for three relay selection schemes is constructed. The EOS and GOS schemes optimize power allocation for energy harvesting and information transmission, and the EGOS scheme jointly optimizes power allocation and energy thresholds. We use a one-dimensional search algorithm based on the golden section and a two-dimensional search algorithm based on iteration to solve these optimization problems. The simulation results show that the EGOS is the best among the three relay selection schemes.</p> <p> </p>

Missing data imputation framework for bridge structural health monitoring based on slim generative adversarial networks

In structural health monitoring (SHM) systems, sensors are important to collect structural responses to assess the load-resistant capacity and health status of structures. However, data loss of these sensors is sometimes inevitable due to communication outages and malfunction, which will result in incorrect diagnosis of structural health status. Conventional lost data imputation methods fundamentally have low implementing efficiency owing to incompact neurons network structures. This paper proposed a slim generative adversarial imputation network (SGAIN) to recover the missing deflection data for bridge SHM systems. This framework uses slim neural networks with a generator-discriminator architecture to capture the valuable information from the non-missing parts of fault sensor and other normal sensors. Based on analysis on the long-term measured deflection data under the ambient and dynamic excitation of a highway-railway dual-purpose bridge, the proposed method shows the efficient and accurate imputation performance under the input scenarios with different correlation levels. The comparative results show the proposed SGAIN significantly outperforms the conventional GAIN model for all three scenarios with different missing rates. The execution velocity of SGAIN model also outperforms GAIN with 10–20% increment for three type scenarios. Such improvement is significantly valuable and it is believed that SGAIN could also have a good imputation capability when transferred to other valuable scenarios.

Indoor mm-Wave Coverage Enhancement: Reconfigurable Intelligent Surface Deployment Strategy Based on Human Mobility Model

Reconfigurable intelligent surface (RIS) is regarded as a promising technology to assist indoor millimeter wave (mm-Wave) communication due to its ability to manipulate electromagnetic waves directionally. Due to the complexity of indoor environment, different RIS deployment strategies significantly affect the system performance. However, the existing work investigating RIS indoor deployment ignored the influence of human mobility to indoor signal coverage, therefore a practical indoor deployment strategy remains unknown. In this letter, based on the consideration of human blockage to mm-Wave signal and probability distribution of human location, we propose an indoor RIS deployment strategy with human mobility model to minimize the outage probability, which is more applicable to the realistic indoor environment. An algorithm is presented to minimize the outage probability at a subspace scale of the room geometry and calculate the corresponding RIS location for single RIS deployment and multiple RISs cooperative deployment. Numerical results are provided to display how our deployment strategy works, which indicate that deploying RIS correctly can decrease the indoor communication outage probability significantly.

Supply Chain Risk Management Resilience & Rebalancing

Supply chain is a network and infrastructure among organizations that is required to produce and distribute a product or service. As organizations extend their operational and commercial footprints, managers are focusing on improving their ability to avoid supply chain risks and maintain a competitive advantage. Supply chain disruptions is an unplanned and unanticipated event arising due to external and internal factors and these disruptions are increasingly costly. Organizations are experiencing increased supplier risk events due to extreme weather events, unplanned communication outages, supplier financial challenges, pandemic-induced lockdowns and cyberattacks, for example. The growth in cross-border flow of goods and services and in the number of partners in an organization’s global supply chain ecosystem has also increased the complexity, making many organizations to focus on creating efficiencies and reducing costs. However, moving to leaner supply chains has made organizations fragile and more susceptible to the growing number of disruptions. As a result, organizations are restructuring or rebalancing supply chains to mitigate the risks of disruptions and to build resilience while increasing visibility and creating the need to balance new operating challenges. Failing to respond to supply chain risks by building adequate contingency plans puts organizations at a greater risk of potential failures and enhanced costs during disasters and other business interruptions.

The Limited Communication Cables for Pacific Island Countries

Abstract This paper provides up-to-date analysis of the status of the undersea communication cables for Pacific Island countries. It identifies those countries with vulnerability to outages because they have just one cable and those countries that do not have a cable connection. This contribution to the ‘Current Legal Developments’ section builds upon the worldwide interest generated by a communication outage in Tonga early in 2022 and two announcements regarding cables for Kiribati late in 2021.

Investigation of Ionospheric Effects in the Planning of the AlfaCrux UHF Satellite Communication System

Recent technological developments and new launch opportunities have allowed the development and spread of small satellite missions for commercial and educational purposes and different applications. Among this category of small satellites, CubeSats have attracted lots of attention given their low design-and-deployment costs. Such satellites usually operate in the narrow ranges of the UHF frequency band to perform the communication activities. Although it provides lower data rate, the use of narrow band can be advantageous when compared to broadband, due to its better penetration and lower attenuation in the troposphere. However, the signals in this frequency band can be significantly affected by the ionosphere. This work investigates the ionospheric effects, namely the Faraday rotation and scintillation, on the UHF satellite communication systems, taking as a case study the AlfaCrux CubeSat mission, which is an 1U CubeSat mission planned for conducting research activities in the field of satellite-mediated communication. In addition, this work presents a methodology of risk estimation for communication outage which supports the planning and decision making for satellite communication missions that have their communication services focused on the low latitude regions.

Connectivity-Aware 3D UAV Path Design With Deep Reinforcement Learning

In this paper, we study the three-dimensional (3D) path planning problem for cellular-connected unmanned aerial vehicle (UAV) taking into account the impact of 3D antenna radiation patterns. The cellular-connected UAV has a mission to travel from an initial location to a destination. In this process, there is a trade-off between the flight time and the expected communication outages duration, which requires planning a suitable route to avoid the weak coverage region. However, as the existing cellular networks are primarily designed for ground coverage, the communication coverage in the sky tends to be intermittent and irregular due to the potential for severe interference and obstructions (such by buildings), which brings great challenges to 3D path planning. To address this challenge, we first construct a 3D coverage map that stores the expected outage probability over each locations. We then propose a multi-step dueling DDQN (multi-step D3QN) based algorithm to design the local optimal UAV path by leveraging the constructed coverage map. In this algorithm, the UAV acts as the agent to learn the appropriate action to complete the flight mission. Numerical results show the effectiveness of the proposed algorithm for connectivity-aware UAV path planning and the superiority of 3D path design over its 2D counterparts.

Blockage tolerance in roadside millimeter-wave backhaul networks

With the proliferation of mobile devices with bandwidth-hungry applications, mmWave communication is considered a key enabling technology for 5G and beyond cellular networks. One very promising use of mmWave communication is in wireless backhaul, which has also been investigated by 3GPP as part of an integrated access and backhaul study. Unfortunately, the network performance is hard to predict due to the sensitivity of mmWave signals to blockages, which can result in frequent communication outages. In this paper, we consider wireless backhaul links deployed along the side of a road, which have been widely proposed both in urban environments and on highways. We first investigate the inherent robustness of an interference-free topology for roadside mmWave backhaul. Based on a novel four-type blockage model, we apply stochastic geometry to derive blockage probabilities as a function of the topology parameters and obstacle density, which yields insights that lead to a more robust topology. We then present mechanisms to tolerate any blockages that do occur through reconfiguration. Through extensive simulations, the performance of our proposed algorithms are evaluated for different road scenarios and network topologies. Results show that our algorithms not only achieve high throughputs close to the no-blockage case for mmWave backhaul, but also provide high blockage tolerance rates even in the presence of multiple obstacles along the road.