Search Results (24)

Limited terrestrial network coverage in rural and remote areas constitutes a significant barrier to the digital transformation of the agricultural sector. Smart and precision farming applications, ranging from conventional environmental monitoring systems to advanced Digital Twin solutions, rely on the reliable transmission of sensor data, images, and video streams from geographically isolated farms. Such data-intensive services cannot be effectively supported without a robust communication infrastructure. Non-Terrestrial Networks (NTNs), particularly satellite systems, offer both narrowband and broadband connectivity, enabling the transmission of low-rate sensor measurements, as well as high-throughput multimedia data from the field. This paper presents an experimental performance evaluation of two satellite backhauling solutions: a Geostationary Earth Orbit (GEO) system provided by SES and a Low Earth Orbit (LEO) system from Starlink. The networks were first deployed and tested in a laboratory environment and subsequently validated in an operational agricultural field setting. Their performance is benchmarked against a terrestrial cellular network to assess their suitability for supporting advanced agricultural applications. The performance assessment results indicate that both satellite backhauling solutions are reliable and capable of meeting the bandwidth and latency requirements of delay-tolerant agricultural applications. In addition to the technical evaluation, this work presents a cost–benefit analysis that further underscores the advantages of NTN-based solutions. Despite higher initial expenditures, they provide extended coverage in remote areas and enable cost sharing across multiple users, improving overall economic viability. Full article

The rapid development of the Internet of Vehicles (IoV) has significantly increased data transmission demands, frequently causing backhaul congestion and service delays in traditional static cellular networks. To address these challenges, this paper proposes a joint position deployment and hierarchical caching optimization solution for unmanned aerial vehicle (UAV)-assisted vehicle-to-vehicle (V2V) caching networks towards dynamic vehicle distribution. Firstly, a hierarchical caching architecture is proposed, where the file library is classified into core, supplementary, and infrequent layers based on file popularity, applying deterministic caching, probabilistic caching, and no-caching strategies, respectively, to achieve efficient utilization of caching resources. Secondly, the mathematical expressions for the caching hit rate and service delay are derived, and a joint optimization problem is formulated to minimize service delay, addressing the dual challenges of hierarchical caching and UAV deployment. To address this problem, a decoupled iterative method is designed, decomposing the original problem into hierarchical caching and UAV deployment subproblems. Based on this, a grid search–tail distribution function fitting-based approach and a K-means clustering-based approach are proposed to optimize these subproblems, respectively. Finally, simulation results demonstrate that, compared to existing strategies, the proposed strategy effectively reduces service latency under multi-vehicle distribution while maintaining high cache file coverage. Under typical conditions, the proposed strategy reduced average service latency by 10% to 20%, thereby validating its effectiveness and superiority. Full article

Monitoring the curing process of concrete remains a challenging and critical aspect of modern construction, often hindered by labour-intensive, invasive, and inflexible methods. The primary aim of this study is to develop an integrated IoT-enabled platform for automated, real-time monitoring of concrete curing, using a combination of LoRa-based sensor networks and an LTE-M backhaul. The resulting ConMonity system employs embedded multi-sensor nodes—capable of measuring strain, temperature, and humidity–connected via an energy-efficient, TDMA-based LoRa wireless protocol to an LTE-M gateway with cloud-based management and analytics. By employing a robust architecture with battery-powered embedded nodes and adaptive firmware, ConMonity enables multi-modal, multi-site assessments and demonstrates stable, autonomous operation over multi-modal, multi-site assessment and demonstrates stable, autonomous operation over multi-month field deployments. Measured data are transmitted in a compact binary MQTT format, optimising cellular bandwidth and allowing secure, remote access via a dedicated mobile application. Operation in laboratory construction environments indicates that ConMonity outperforms conventional and earlier wireless monitoring systems in scalability and automation, delivering actionable real-time data and proactive alerts. The platform establishes a foundation for intelligent, scalable, and cost-effective monitoring of concrete curing, with future work focused on extending sensor modalities and enhancing resilience under diverse site conditions. Full article

This paper presents how the concept of opportunistic integrated sensing and communication (ISAC), focusing on weather sensing, is incorporated into wireless smart cities’ networks. The concept, first introduced in 2006, utilized standard signal level measurements from wireless backhaul cellular networks for rain monitoring. Since then, it has expanded to include technologies like satellite communication and smart cities’ networks. Opportunistic ISAC (OISAC) for weather involves transforming communication networks into virtual sensors by interpreting the signal attenuation caused by environmental factors, such as rain. These virtual sensors form the sensing layer of an IoT system, with built-in connectivity. In this paper, we present the recent advancements in the field, emphasizing the potential of current and future smart cities’ wireless networks for accurate rainfall monitoring. We also demonstrate a test case in the city of Rehovot in Israel, where high spatiotemporal resolution rain maps produced via the OISAC paradigm significantly outperform the spatial resolution achieved by modern weather radars. We also discuss the challenges and opportunities in applying this concept. Full article

A novel tracking and monitoring system for ISO 668 dry containers was realized by the ESA-funded “5G SENSOR@SEA” project, integrating 5G cellular technologies for massive Internet of Things with a GEO satellite-optimized backhauling link. The scope is the development of monitoring and tracking new services for multimodal container shipping. With the cooperation of four industrial partners and a telecommunication research center, the so-called “5GT System” was designed, developed, tested and validated up to field trials. Several modules of the system were designed, built and finally installed on the ship and in the teleport: the container tracking devices placed on the containers, the NB-IoT cellular network with optimized satellite backhauling, the Ku-band satellite terminals and the maritime service platform based on the OneM2M standard. The field trial conducted during the intercontinental liner voyage of a container ship showed primary technical achievements, including fair switching between terrestrial and satellite networks, reduction in packet loss in the open sea scenario and seamless integration of the BLE mesh network over the container tracking devices as NB-IoT/BLE LE Mesh gateways. Full article

Recently, hyperdense small cells have been proposed to meet the challenge of the tremendous increment in cellular data service requirements. To reduce the deployment cost, as well as operated cost, these small cells are usually connected to limited backhauls, in which case the backhaul capacity may become a bottleneck in busy hours. In this paper, we propose an optimal scheme for the small cells to utilize the macrocell links as its wireless backhaul. Based on stochastic geometry, the analytical expressions of network capacity with in-band and out-band wireless backhaul are derived and validated using simulation results. The optimized results show that our proposed scheme can significantly improve the network performance in scenarios with a high traffic load. Full article

This paper presents the spectral gap-based topology control algorithm (SGTC) for wireless backhaul networks, a novel approach that employs the Laplacian Spectral Gap (LSG) to find expander-like graphs that optimize the topology of the network in terms of robustness, diameter, energy cost, and network entropy. The latter measures the network’s ability to promote seamless traffic offloading from the Macro Base Stations to smaller cells by providing a high diversity of shortest paths connecting all the stations. Given the practical constraints imposed by cellular technologies, the proposed algorithm uses simulated annealing to search for feasible network topologies with a large LSG. Then, it computes the Pareto front of the set of feasible solutions found during the annealing process when considering robustness, diameter, and entropy as objective functions. The algorithm’s result is the Pareto efficient solution that minimizes energy cost. A set of experimental results shows that by optimizing the LSG, the proposed algorithm simultaneously optimizes the set of desirable topological properties mentioned above. The results also revealed that generating networks with good spectral expansion is possible even under the restrictions imposed by current wireless technologies. This is a desirable feature because these networks have strong connectivity properties even if they do not have a large number of links. Full article

The flexible mobility feature of unmanned aerial vehicles (UAVs) leads to frequent handovers and serious inter-cell interference problems in UAV-assisted cellular networks. Establishing a cell-free UAV (CF-UAV) network without cell boundaries effectively alleviates frequent handovers and interference problems and has been an important topic of 6G research. However, in existing CF-UAV networks, a large amount of backhaul data increases the computational pressure on the central processing unit (CPU), which also increases system delay. Meanwhile, the mobility of UAVs also leads to time-varying channel conditions. Therefore, designing dynamic resource allocation schemes with the help of edge computing can effectively alleviate this problem. Thus, aiming at partial network breakdown in an urban-micro (UMi) environment, an urban-micro CF-UAV (UMCF-UAV) network architecture is proposed in this paper. A delay minimization problem and a dynamic task offloading (DTO) strategy that jointly optimizes access point (AP) selection and task offloading is proposed to reduce system delay in this paper. Considering the coupling of various resources and the non-convex feature of the proposed problem, a dynamic resource cooperative allocation (DRCA) algorithm based on deep reinforcement learning (DRL) to flexibly deploy AP selection and task offloading of UAVs between the edge and locally is proposed to solve the problem. Simulation results show fast convergence behavior of the proposed algorithm compared with classical reinforcement learning. Decreased system delay is obtained by the proposed algorithm compared with other baseline resource allocation schemes, with the maximize improvement being 53%. Full article

Multiservice cellular in Radio Access Network (RAN) Slicing has recently attained huge interest in enhancing isolation and flexibility. However, RAN slicing in heterogeneous networks (HetNet) architecture is not adequately explored. This study proposes a pairing-network slicing (NS) approach for Multiservice RAN that cares about quality of service (QoS), baseband resources, capacities of wireless fronthaul and backhaul links, and isolation. This intriguing approach helps address the increased need for mobile network traffic produced by a range of devices with various QoS requirements, including improved dependability, ultra-reliability low-latency communications (uRLLC), and enhanced broadband Mobile Services (eMBB). Our study displays a unique RAN slicing framework for user equipment (UE) for joint user-association. Multicell non-orthogonal multiple access (NOMA)-based resource allocation across 5G HetNet under successive interference cancelation (SIC) is seen to achieve the best performance. Joint user-slice pairing and association are optimization problems to maximize eMBB UE data rates while fulfilling uRLLC latency and reliability criteria. This is accomplished by guaranteeing the inter- and intra-isolation property of slicing to eliminate interferences between eMBB and uRLLC slices. We presented the UE-slice association (U-S. A) algorithm as a one-to-many matching game to create a stable connection between UE and one of the base stations (BSs). Next, we use the UE-slice pairing (U-S. P) algorithm to find stable uRLLC-eMBB pairs that coexist on the same spectrum. Numerical findings and performance analyses of the submitted association and pairing technique show they can all be RAN slicing criteria. We prove that the proposed algorithm optimizes system throughput while decreasing uRLLC latency by associating and pairing every uRLLC user in mini slots. Full article

Coordinated multipoint joint transmission (JT) is one of the critical downlink transmission technologies to improve network throughput. However, multiple cells in a JT group should have the same user data to transmit simultaneously, resulting in a considerable backhaul burden. Even when cells are already equipped with caches in fifth-generation networks, JT groups, without effectively utilizing the caching data, still cause unnecessary backhaul data traffic. In this article, we investigate the JT grouping problem with the consideration of caches at cells. Then, we propose a genetic approach to solve the above problem with the objective of minimizing the amount of backhaul data traffic subject to the data-rate requirement of each user. The simulation results show that our proposed generic algorithm can significantly decrease the backhaul bandwidth consumption compared to the two baselines. Full article

To deal with recent increasing mobile traffic, ultra-broadband communication with millimeter-wave (mmWave) has been regarded as a key technology for 5G cellular networks. In a previous study, a mmWave heterogeneous network was composed of several mmWave small cells overlaid on the coverage of a macro cell. However, as seen from the optical fiber penetration rate worldwide, it is difficult to say that backhaul with Gbps order is available everywhere. In the case of using mmWave access under a limited backhaul capacity, it becomes a bottleneck at the backhaul; thus, mmWave access cannot fully demonstrate its potential. On the other hand, the concept of multi-access edge computing (MEC) has been proposed to decrease the response latency compared to cloud computing by deploying storage and computation resources to the user side of mobile networks. This paper introduces MEC into mmWave heterogeneous networks and proposes a content prefetching algorithm to resolve such backhaul issues. Context information, such as the destination, mobility, and traffic tendency, is shared through the macro cell to the prefetch application and data that the users request. Prefetched data is stored in the MEC and then transmitted via mmWave without a backhaul bottleneck. The effectiveness is verified through computer simulations where we implement realistic user mobility as well as traffic and backhauling models. The results show that the proposed framework achieved 95% system capacity even under the constraint of a 1 Gbps backhaul link. Full article

Near-surface humidity is a crucial variable in many atmospheric processes, mostly related to the development of clouds and rain. The humidity at the height of a few tens of meters above ground level is highly influenced by surface characteristics. Measuring the near-surface humidity at high resolution, where most of the humidity’s sinks and sources are found, is a challenging task using classical tools. A novel approach for measuring the humidity is based on commercial microwave links (CML), which provide a large part of the cellular networks backhaul. This study focuses on employing humidity measurements with high spatio–temporal resolution in Germany. One major goal is to assess the errors and the environmental influence by comparing the CML-derived humidity to in-situ humidity measurements at weather stations and reanalysis (COSMO-Rea6) products. The method of retrieving humidity from the CML has been improved as compared to previous studies due to the use of new data at high temporal resolution. The results show a similar correlation on average and generally good agreement between both the CML retrievals and the reanalysis, and 32 weather stations near Siegen, West Germany (CML—0.84, Rea6—0.85). Higher correlations are observed for CML-derived humidity during the daytime (0.85), especially between 9–17 LT (0.87) and a maximum at 12 LT (0.90). During the night, the correlations are lower on average (0.81), with a minimum at 3 LT (0.74). These results are discussed with attention to the diurnal boundary layer (BL) height variation which has a strong effect on the BL humidity temporal profile. Further metrics including root mean square errors, mean values and standard deviations, were also calculated. Full article

The transmission of a large amount of video and picture content brings more challenges to wireless communication networks. Unmanned aerial vehicle (UAV)-aided small cells with active content caching deployed on cellular networks are recognized as a promising way to alleviate wireless backhaul and support flexible coverage. However, a UAV cannot operate for a long time due to limited battery life, and its caching capacity is also limited. For this, a multi-UAV content-caching strategy and cooperative, complementary content transmission among UAVs are jointly studied in this paper. Firstly, a user-clustering-based caching strategy is designed, where user clustering is based on user similarity, concurrently taking into consideration similarities in content preference and location. Then, cooperative, complementary content transmission between multiple UAVs is modeled as a coalition formation game (CFG) to maximize the utility of the whole network. Finally, the effectiveness of the proposed algorithms is demonstrated through numerical simulations. Full article

With the rapid growth in the penetration rate of mobile devices and the surge in demand for mobile data services, small cells and mobile backhaul networks have become the critical focus of next-generation mobile network development. Backhaul requirements within current wireless networks are almost asymmetrical, with most traffic flowing from the core to the handset, but 5G networks will require more symmetrical backhaul capability. The deployment of small cells and the placement of transceivers for cellular phones are crucial in trading off the symmetric backhaul capability and cost-effectiveness. The deployment of small cells is related to the placement of transceivers for cellular phones. Chang, Kloks, and Lee transformed the placement problem into the maximum-clique transversal problem on graphs. From the theoretical point of view, our paper considers the parameterized complexity of variations of the maximum-clique transversal problem for split graphs, doubly chordal graphs, planar graphs, and graphs of bounded treewidth. Full article

We study the performance of water vapor monitoring using commercial millimeter-wave backhaul links from the fifth-generation cellular networks and smart cities. A 38 GHz link and an E-band link located in Gothenburg, Sweden, are used for analysis. One end of these two backhaul links is installed at the same site. The water vapor density (WVD) over a one-month period from 13 June 2017 to 13 July 2017 is calculated based on the data from these microwave links with different frequencies. The meteorological data used for analysis is from a weather station installed at the site where the microwave links are installed, as well as from a nearby weather station operated by Swedish Institute of Meteorology and Hydrology (SMHI). A pre-processing step is applied to the raw link attenuation measurement for improving the estimation accuracy. We retrieved water vapor density value from two millimeter-wave links, and it is in good agreement with the water vapor density calculated by weather stations. The source of interference, such as misalignment, humidity source below the link, location, and altitude of weather stations, can contribute to estimation errors and needs to be carefully considered when using microwave link to retrieve water vapor density. Full article