Current Issue : October-December Volume : 2026 Issue Number : 4 Articles : 5 Articles
The growing penetration of renewables and prosumagers in the 2030s will require deeper monitoring and control in medium- and low-voltage grids. Wireless technologies, particularly 5G, offer possibilities for cost-effective, flexible, and scalable connectivity in grid automation. Power system communication is highly heterogeneous, involving diverse traffic types with varying latency and reliability requirements. Prior research on 5G technology enablers, such as carrier aggregation, dual connectivity, and network slicing (NS), has focused on other verticals and relied mainly on simulations, leaving a gap in experimental validation for grid protection and automation under realistic conditions. This paper maps 5G technology enablers to IEC 61850 traffic types and evaluates their performance in commercial 5G networks for line differential protection and virtualised fault passage indication. Results show that NS improves reliability compared to traffic prioritisation, but does not yet meet ultra-low latency requirements for line differential protection. Minimum latency for mission-critical protection traffic reaches approximately 11 ms, and roundtrip times are 32% lower than prior works. These findings provide the first end-to-end empirical evidence of 5G technology enabler deployment for smart grid applications and offer practical guidance for future implementations....
Classifying encrypted sensor traffic is critical for the security and management of Internet of Things networks, particularly in Mobile Edge Computing (MEC) environments. Existing methods often require extensive task-specific labeled data to adapt to emerging traffic categories and may also fail to distinguish intrinsic traffic behaviors from patterns introduced by shared communication libraries, which can degrade classification accuracy under distribution shifts. To address these issues, we propose CDTF, a contrastive dual-task framework for transferable and few-shot traffic representation learning. CDTF adopts a hybrid pre-training strategy that jointly optimizes supervised triplet pretraining (STP) and self-supervised dynamic burst masking (DBM). STP uses base-class labels as structural anchors to explicitly constrain distance relationships by aligning intra-class samples and separating inter-class samples, thereby mitigating interference from shared network components. DBM models global semantic structures and enhances the robustness of traffic representations against network noise and distribution shifts. By learning discriminative and contextual representations in a shared embedding space via these two tasks, CDTF can rapidly adapt to novel categories through lightweight fine-tuning, thereby substantially reducing the reliance on large-scale fine-grained supervision in downstream tasks. Experimental results across seven public and two custom datasets, across diverse environments, show that the proposed framework outperforms state-of-the-art methods. Under the few-shot setting, CDTF improves Precision by 4.61 percentage points over the strongest baseline, with statistical significance confirmed by a paired t-test (p < 0.05)....
Direct-to- cell (D2C) connectivity enables future non-terrestrial networks to provide service directly to standard terrestrial user equipment (UE) when terrestrial networks (TN) are unavailable. In this work, the satellite system is considered as a secondary network that supplements existing TN coverage while minimizing interference to the primary terrestrial infrastructure. To achieve this goal, we propose a dynamic cell-division framework in which satellite cells are adaptively formed to balance coverage and interference constraints. For UEs located near TN cells, a projected gradient descent algorithm is developed to place satellite cells as far as possible from the TN while maintaining user coverage. For UEs located far from the TN, a minimum covering cell (MCC) algorithm is employed to efficiently serve remote users while limiting the increase in the total number of cells. Simulation results demonstrate that the proposed method significantly reduces interference to the terrestrial network compared with conventional hexagonal cell layouts and the conventional MCC algorithm. In other words, the proposed method enables higher throughput without increasing the interference level compared to conventional approaches....
Advancement of next-generation information technologies is driving the increasing integration of millimeter-wave and terahertz (THz) communication, detection, and artificial intelligence technologies, thereby creating a demand for multifunctional absorbing materials to address complex electromagnetic interference. In this study, a flexible WPU-MXene@FC composite fabric with ultrabroadband absorption, superhydrophobicity, and excellent durability is developed. The base fabric (FC) is modified via surface plasma treatment to introduce positively charged active sites on fibers. Driven by electrostatic interaction, negatively charged MXene is self-assembled with modified FC. The electrostatic interactions process induces a “nest-like” structure on fibers, building construct MXene multiple loss paths. Waterborne polyurethane (WPU) is finally coated to endow the FC with MXene oxidation protection, superhydrophobicity, and stability. Results show that a 1.8 mm-thick WPU-MXene@FC achieves an effective absorption bandwidth spanning 25.3–1200 GHz. Within 0.2–1.0 THz, the reflection loss ( RL ) value is below − 30 dB, reaching a minimum of − 45.2 dB. After 500 bending cycles, its RL remains below − 30 dB. The WPU-MXene@FC exhibits superhydrophobicity (contact angle 151.3◦, sliding angle 1.2◦), excellent air permeability, and flexibility. This multifunctional FC has important applications in wearable devices, communications, and provides strong support for the development of lightweight stealth structures and flexible electromagnetic camouflage....
Future networks should provide access to cloud-based content to subscribers in mountainous region. This research proposes a network architecture incorporating mountain data centers that provide content access via caching in a capital-constrained context. It also discusses the aspects of the power system supporting the network architecture. The use of content caching reduces content access latency. The research recognizes that mountains can host computing platforms while ensuring low to moderate operational costs. Using the proposed approach also reduces the number of network hops and associated power consumption by (26–37)% and (17–25)% on average, respectively....
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