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Given the critical role of media in times of crisis, particularly for relaying scientific knowledge and political decisions, we evaluated to what extent the first COVID-19 pandemic wave affected the treatment by traditional media of important societal topics. We searched a database of 650 French-speaking Swiss media outlets using specific keywords and reported the number of publications per month containing these items, associated or not with SARS-CoV-2. The number of publications related to viruses increased 12-fold during the first semester 2020, while the media coverage of topics about bacteria, parasites, and fungi remained stable. During the first pandemic wave, media generated a larger number of publications treating of political and medical subjects than before the pandemic, whereas the coverage of other topics was unchanged. All topics were viewed through the prism of the pandemic, up to 82% of the publications being associated with COVID-19. The media largely covered all medical aspects related to SARS-CoV-2 infection and offered scientists multiple opportunities to communicate with the public. However, their influence was strongly challenged by the capacity of social networks to disseminate rumors and misinformation. We also assessed the articles published in traditional media during the five subsequent epidemic waves, showing that the largest media peaks occurred during the first infection wave studied extensively in the present work, and during the huge fifth infection wave due to Omicron variant BA1. Undoubtedly, the COVID-19 pandemic highlighted how important it is for science communication to harness the tremendous power of social media. Full article

At present, the cross-region end-to-end communication of a power distribution network relies on heterogeneous networks such as carrier networks and power fiber networks to support the specialization of relay nodes, and the corresponding state volatility increases abruptly. Furthermore, the corresponding state information is often difficult to obtain in full in real-time, which leads to difficulty in predicting the channel state, and it is not possible to reasonably guide the joint deployment of sensing, communication, and computing resources. Therefore, this study proposes a cross-region data transmission channel state prediction method based on the thermal characteristics of the service traffic. Firstly, this study establishes a cross-region end-to-end data transmission system model for a new type of power distribution system, then refers to the relevant theory of thermodynamics, proposes an evaluation method of the thermal characteristics of the service traffic adapted to the multi-timescale, and finally designs the channel anomaly state evaluation function. Then, based on the thermal characteristics of the historical service traffic, the future state of the specified channel based on the LSTM (Long Short-Term Memory) neural network is predicted. Finally, the channel anomalous state assessment function is designed to accurately predict the future channel state under the specified time scale based on the thermal characteristics of the historical service traffic and based on the LSTM neural network. Simulation analysis shows that the proposed service traffic characteristic model can reasonably quantitatively characterize the change of channel state and accurately predict the state of inter-regional data transmission. Full article

Standards describing the test procedures recommended to investigate the shielding effectiveness of enclosures have two major issues: they generally prescribe the assessment of the electromagnetic field of empty cavities, and they do not deal with very small enclosures. However, the dimensions of some very common shielded apparatus are smaller than those considered in the standards and the electromagnetic field distribution inside the shielded structure is strongly affected by the enclosure content. In this paper, both issues have been investigated for two components commonly used in medium voltage/low voltage (MV/LV) substations: a mini personal computer used to store, process, and transmit relevant data on the status of the electric network, with these aspects being essential in smart grids, and an electronic relay which is ubiquitous in MV/LV substations. Both components are partially contained in a metallic enclosure which provides a certain amount of electromagnetic shielding against external interferences. It is observed that an electrostatic discharge may cause a failure and/or a loss of data, requiring an improvement of shielding characteristics or a wise choice of the positions where the most sensitive devices are installed inside the enclosure. Since the dimensions of very small enclosures, fully occupied by their internal components, do not allow for the insertion of sensors inside the protected volume, numerical analysis is considered as the only way for the appraisal of the effects induced by a typical source of interference, such as an electrostatic discharge. Full article

Power line communication (PLC) technology is investigated in this research. A PLC system model combining Orthogonal Frequency Division Multiplexing (OFDM) and Non-Orthogonal Multiple Access (NOMA) technologies is proposed to enhance spectral efficiency, extend transmission distance, and improve signal quality. We construct detailed models for the system, signal, and noise. Future Channel State Information (CSI) is predicted using a Long Short-Term Memory (LSTM) network, and an improved simulated annealing algorithm is employed to optimize power allocation and relay positioning in the system. Experiments validate the effectiveness of the LSTM model in predicting CSI data in a NOMA communication system, demonstrating generally good performance despite some prediction errors. Simulation results show that this approach significantly enhances system performance, reduces power consumption, and meets constraints on system capacity, bit error rate (BER), and signal-to-interference-plus-noise ratio (SINR) in complex PLC environments. Future research should focus on optimizing model parameters, expanding datasets, exploring alternative optimization algorithms, and testing the model in real-world scenarios to improve generalizability and practicality. In conclusion, the proposed multi-user PLC system provides an effective technical solution for future smart grid and Internet of Things (IoT) applications. Full article

This paper considers a decentralized and autonomous wireless network of low SWaP (size, weight, and power) fixed-wing UAVs (unmanned aerial vehicles) used for remote exploration and monitoring of targets in an inaccessible area lacking communication infrastructure. Here, the UAVs collaborate to find target(s) and use routing protocols to forward the sensed data of target(s) to an aerial base station (BS) in real-time through multihop communication, which can then transmit the data to a control center. However, the unpredictability of target locations and the highly dynamic nature of autonomous, decentralized UAV networks result in frequent route breaks or traffic disruptions. Traditional routing schemes cannot quickly adapt to dynamic UAV networks and can incur large control overhead and delays. In addition, their performance suffers from poor network connectivity in sparse networks with multiple objectives (exploration and monitoring of targets), which results in frequent route unavailability. To address these challenges, we propose two routing schemes: Pipe routing and TC-Pipe routing. Pipe routing is a mobility-, congestion-, and energy-aware scheme that discovers routes to the BS on-demand and proactively switches to alternate high-quality routes within a limited region around the routes (referred to as the “pipe”) when needed. TC-Pipe routing extends this approach by incorporating a decentralized topology control mechanism to help maintain robust connectivity in the pipe region around the routes, resulting in improved route stability and availability. The proposed schemes adopt a novel approach by integrating the topology control with routing protocol and mobility model, and rely only on local information in a distributed manner. Comprehensive evaluations under diverse network and traffic conditions—including UAV density and speed, number of targets, and fault tolerance—show that the proposed schemes improve throughput by reducing flow interruptions and packet drops caused by mobility, congestion, and node failures. At the same time, the impact on coverage performance (measured in terms of coverage and coverage fairness) is minimal, even with multiple targets. Additionally, the performance of both schemes degrades gracefully as the percentage of UAV failures in the network increases. Compared to schemes that use dedicated UAVs as relay nodes to establish a route to the BS when the UAV density is low, Pipe and TC-Pipe routing offer better coverage and connectivity trade-offs, with the TC-Pipe providing the best trade-off. Full article

With the rapid expansion of urban populations and the accelerated pace of urbanization, the concept of urban air mobility (UAM) has emerged. During flights, UAM aircraft need to transmit real-time sensing information to base stations for further processing and analysis. Large-scale real-time data require leveraging the computing capabilities of edge servers at the network edge to reduce transmission delay and energy consumption of UAM aircraft. In cases where edge servers are unable to process information, an unmanned aerial vehicle (UAV) equipped with computing capabilities and operating in low-altitude airspace can serve as a relay to assist in communication and computation. Due to the limited payloads and flight times of UAVs and UAM aircraft, delay and energy consumption within the system pose significant challenges. To tackle these challenges, two fundamental objectives have been proposed: minimizing delay and minimizing energy consumption. Furthermore, an optimization problem has been proposed to minimize the weighted sum of delay and energy consumption. Then, a UAM federated twin delayed deep deterministic policy gradient (UF-TD3) algorithm has been proposed to solve the original problems characterized by complex, non-convex, and inseparable variables. Simulation results show that the proposed UF-TD3 algorithm converges quickly and significantly outperforms four other baseline algorithms in optimizing delay and energy consumption performance. Moreover, compared to the conventional delay minimization strategy and energy minimization strategy, the proposed strategy of minimizing the weighted sum of delay and energy consumption can reduce the delay by 63.8% and reduce energy by 73.96%. Full article

Future generations of wireless networks at high-frequency spectrum suffer from limited coverage and Non-Line- of-Sight signal blockage, challenging emerging applications, such as smart industries and intelligent automation systems. Collaborative and cooperative communications with smart relays via Non-Orthogonal Multiple Access (NOMA) could be a breakthrough solution to this challenge. This paper presents a blockchain-integrated framework for NOMA wireless communication systems that incentivizes cooperation among users serving as relays. By leveraging Ethereum-based smart contracts, we introduce a Service Verification Contract featuring a Proof of Quality of Experience (PQoE) mechanism. The contract uses trust scores, weighted verifications, and dynamic validation thresholds to ensure honest behavior and deter malicious activities. The simulation results show that honest participants gradually increase their trust scores and require fewer verifications, while malicious verifiers lose influence over repeated rounds. Our findings indicate that combining trust-based incentives with a decentralized ledger can effectively promote reliable data-relaying services and streamline payment processes in collaborative and smart wireless networking systems. Full article

In relay-assisted underwater wireless optical communication (UWOC) systems, the traditional time-division-multiplexed relay forwarding strategy faces high latency and low throughput with the increase of relay users. To address these issues, this paper proposes a multiple receiving antenna power allocation-based bit splicing physical layer network coding (MRA-PABS-PNC) method in a three-user asymmetric modulated relay-assisted UWOC scenario. MRA-PABS-PNC reduces the number of multiple access time slots by using multi-antenna reception techniques. At the same time, it employs a bit-splicing method to concatenate the data that would normally be transmitted over two-time slots into a longer data stream transmitted in a single time slot, thus reducing the number of broadcast time slots and ultimately improving throughput. Moreover, this paper models and determines the optimal position and angle of the relay node photodetector. Once the relay node is positioned at the optimal location and angle, the system can allocate power to each user node based on the channel state information to overcome the effect of asymmetric channels on PNC coding, thereby further improving system performance. Simulation results show that the method improves the throughput by 100% compared with the existing four-time slot PNC (FT-PNC) method. Full article

In this paper, a new communication protocol is proposed to allow direct communication between internet of things (IoT)-enabled home energy management systems (HEMSs) in a smart microgrid. The direct communication features are an important attribute for decentralised demand management and local energy trading operations in a microgrid equipped with renewable energy resources. The proposed scheme utilises the intermediate HEMSs as relay nodes that forward the sum of the received signals from nearby HEMSs to both ends of the entire network. The scheme can achieve lower latency compared to the cases when HEMSs adopt direct decode−and−forward (DF) or transmit through the central controller. For the proposed protocol, we have analytically obtained expressions for the error probability at different HEMSs, as well as the average bit error rate (BER) to indicate the overall error performance of the microgrid communication. To evaluate the proposed protocol in different channel conditions, numerical simulation is performed. The results demonstrate that the channel conditions between the HEMSs at the middle of the network have a greater impact on the system error performance. Overall, it can be observed that the proposed protocol suffers a lower degradation in error performance in comparison to direct DF when one of the users experiences worse channel conditions. Full article

Wireless Sensor Networks are formed by tiny, self-contained, battery-powered computers with radio links that can sense their surroundings for events of interest and store and process the sensed data. Sensor nodes wirelessly communicate with each other to relay information to a central base station. Energy consumption is the most critical parameter in Wireless Sensor Networks (WSNs). Network lifespan is directly influenced by the energy consumption of the sensor nodes. All sensors in the network send and receive data from the base station (BS) using different routing protocols and algorithms. These routing protocols use two main types of clustering: hierarchical clustering and flat clustering. Consequently, effective clustering within Wireless Sensor Network (WSN) protocols is essential for establishing secure connections among nodes, ensuring a stable network lifetime. This paper introduces a novel approach to improve energy efficiency, reduce the length of network connections, and increase network lifetime in heterogeneous Wireless Sensor Networks by employing the K-Nearest Neighbours (KNN) algorithm to optimise node selection and clustering mechanisms for four protocols: Low-Energy Adaptive Clustering Hierarchy (LEACH), Stable Election Protocol (SEP), Threshold-sensitive Energy Efficient sensor Network (TEEN), and Distributed Energy-efficient Clustering (DEC). Simulation results obtained using MATLAB (R2024b) demonstrate the efficacy of the proposed K-Nearest Neighbours algorithm, revealing that the modified protocols achieve shorter distances between cluster heads and nodes, reduced energy consumption, and improved network lifetime compared to the original protocols. The proposed KNN-based approach enhances the network’s operational efficiency and security, offering a robust solution for energy management in WSNs. Full article

Unmanned aerial vehicles (UAVs) significantly shape the evolution of 5G and 6G technologies in India, particularly in reconfiguring communication networks. Through their deployment as base stations or relays, these aerial vehicles substantially enhance communication performance and extend network coverage in areas characterized by high demand and challenging topographies. Accurate modelling of the UAV-to-ground channel is imperative for gaining valuable insights into UAV-assisted communication systems, particularly within India’s rapidly expanding metropolitan cities and their diverse topographical complexities. This study proposes an approach to model low-altitude channels in urban areas, offering specific scenarios and tailored solutions to facilitate radio frequency (RF) planning for Indian metropolitan cities. The proposed model leverages the International Telecommunication Union recommendation (ITU-R) for city mapping and utilizes frequency ranges from 1.8 to 6 GHz and altitudes up to 500 m to comprehensively model both line-of-sight (LoS) and non-line-of-sight (NLoS) communications. It employs the uniform theory of diffraction to calculate the additional path loss for non-line-of-sight (NLoS) communication for both vertical and horizontal polarizations. The normal distribution for additional shadowing loss is discerned from simulation results. This study outlined the approach to derive a comprehensive statistical channel model based on the elevation angle and evaluate model parameters at various frequencies and altitudes for both vertical and horizontal polarization. The model was subsequently compared with existing models for validation, showing close alignment. The ease of implementation and practical application of this proposed model render it an invaluable tool for planning and simulating mobile networks in urban areas, thus facilitating the seamless integration of advanced communication technologies in India. Full article

Terahertz (THz)-band communications are a possible candidate for fast communication. Transmission power needs to be optimised in order to satisfy the requirements of such a network of nodes. Multi-hop communication can be used in THz communications to add relays when obstacles or other interference is evident. This paper investigates the domain of multi-hop THz communications, acknowledging the possibility of interference from other devices affecting the communication process and utilises interference cancellation. It formulates the Transmission Power Control (TPC) problem within a game-theoretic framework, specifically as a potential game, with the assurance of convergence to a Nash equilibrium in the majority of scenarios. Bounds of the Price of Anarchy (PoA) and the Price of Stability (PoS) are provided, given assumed factors. Also, asymptotic Lyapunov stability is shown. The findings from simulations conducted to assess the effectiveness of this approach are then discussed. In particular, the final utilities when utilising interference cancellation show an improvement compared to without-interference cancellation between 19.30 and 67.30% for five simulated players. Full article

Wireless Sensor Networks (WSNs) connected to the Internet of Things (IoT) are increasingly employed in commercial and industrial applications to accomplish various tasks at a low cost. WSNs are essential for gathering diverse types of data within physical environments. A key design objective for WSNs is to balance energy consumption and increase the network’s operating lifetime. Recent studies have shown that mobile base stations (BSs) can significantly extend the lifetime of such networks, especially when their location is optimized using specific criteria. In this study, we propose an algorithm for selecting the optimal BS location in a large network. The algorithm computes a distance metric between sensor nodes (SNs) and potential BS locations on a virtual grid within the WSN. The selection process is repeated periodically to account for dead SNs, allowing the BS to relocate to a new optimal position based on the remaining active nodes after each iteration. Additionally, the inclusion of a relay node (RN) in large networks is explored to improve scalability. The impact of path loss within WSNs is also discussed. The proposed algorithms are applied to the well-known Stable Election Protocol (SEP). Simulation results demonstrate that, compared to other algorithms in the literature, the proposed approaches significantly enhance the lifetime of WSNs. Full article

In this paper, we introduce a shipping logistics network optimization method for construction waste recycling. In our case, construction waste is transported by a relay mode integrating land transportation, shipping transportation, and land transportation. Under the influence of urban economic life, the quantity (demand) of construction waste is uncertain and stochastic. Considering the randomness of construction waste generation, a two-stage stochastic integer programming model for the design of a shipping logistics network for construction waste recycling is proposed, and an accurate algorithm based on Benders decomposition is presented. Based on an actual case in Shanghai, numerical experiments are carried out to evaluate the efficacy of the proposed model and algorithm. Based on an actual case study in Shanghai, numerical experiments demonstrate that the proposed model can help to reduce transportation costs of construction waste. Sensitivity analysis highlights that factors like the penalty for untransported waste and capacity constraints play a crucial role in network optimization decisions. The findings provide valuable theoretical support for developing more efficient and sustainable logistics networks for construction waste recycling. Full article

The complexity and uncertainty of the marine environment pose significant challenges to the stability and coverage of communication links. Due to the limited coverage range of traditional onshore base stations (BSs) in marine environments, relay technology has become an essential approach to extending communication coverage. However, the rapid variations in marine wireless channels and the complexity of hydrological conditions make it extremely difficult to obtain accurate channel state information (CSI). In particular, dynamic environmental factors such as waves, tides and wind speed cause channel parameters to fluctuate significantly over time. To address these challenges, this paper proposes a cooperative communication strategy based on ships and designs a novel channel modeling method to accurately capture the characteristics of marine wireless channels. Furthermore, a deep learning-based optimization scheme is proposed, which formulates the relay selection problem as a spatiotemporal classification task. By integrating the spatial positions of candidate relays and their communication conditions, the proposed scheme enables real-time selection of the optimal relay while evaluating link connectivity probabilities under hydrological influences. Simulation results confirm that the proposed method achieves high accuracy even in rapidly changing marine environments. Full article