Abstract This paper presents a comparative review of high‐performance super‐wideband multiple‐input multiple‐output (MIMO) antenna architectures for next‐generation wireless communication systems. Rather than conducting an extensive survey of all possible architectures, this study takes a case‐study approach, specifically addressing two unique and contrasting MIMO antenna architectures: the Hexa‐Barrier Super‐Wideband (HBSWB) MIMO antenna and the Phase Helix Fractal Array (PHFA) MIMO antenna. The reason for the selection of these architectures is because they represent two different approaches toward the design of super wideband MIMO antennas. In specific, the HBSWB MIMO antenna is an interference mitigation technique in the frequency domain which makes use of multi‐notch filters, electromagnetic band gap structures, and LC networks to achieve high isolation and coexistence in interference‐rich environments. On the other hand, the PHFA antenna is a paradigm based on spatial multiplexing principles that use fractals, artificial magnetic conductor ground planes, and orbital angular momentum modes to increase spectral efficiency and system capacity. This review presents a comparative analysis of these architectures in terms of bandwidth, isolation, gain, and efficiency to identify the most important design limitations and challenges that future wireless communication systems must address. Choosing these two antennas will enable a comparative analysis of two design philosophies proposed to address key challenges in future wireless communication systems.
Abstract This paper presents a compact and efficient monopole antenna tailored for underground soil moisture sensing in wireless underground sensor networks (WUSNs). The antenna integrates a T‐shaped coupling structure and an inductive shorting strip on an FR4 substrate, achieving a compact form factor of at 920 MHz. The antenna bandwidth covers the frequency ranges used by LoRa‐based systems in the U.S. and Vietnam. Comprehensive evaluations, including simulated and measured , gain, radiation patterns, and 3D far‐field characteristics, confirm the antenna's robust performance under soil burial conditions. Field experiments conducted in loamy soil at 15 cm depth demonstrate that the proposed antenna exhibits a 2–5 dB higher signal‐to‐noise ratio (SNR) and lower packet error rate (PER) compared with the commercial counterpart under the tested conditions. At the link level, the proposed antenna achieves up to 11 dB SNR improvement compared with a commercial antenna under identical underground measurement conditions, which is attributed to improved RF radiation efficiency and underground electromagnetic coupling. This improvement reflects increased received signal power enabled by improved radiation efficiency and underground coupling, while the receiver noise floor remains unchanged, rather than any signal–noise discrimination at the antenna level. These results indicate that the proposed structure provides stable communication performance under controlled underground conditions.
Abstract The increasing integration of renewable energy resources, power‐electronic converters, and ultra‐high‐voltage (UHV) transmission networks has introduced new challenges in evaluating the short‐circuit withstand capability of high‐voltage disconnectors. This review presents a critical assessment of state‐of‐the‐art methodologies for short‐circuit withstand evaluation, focusing primarily on disconnectors while considering transformers, switchgear, and cables only for comparative analysis. A structured PRISMA‐based review methodology and comprehensive evaluation framework are employed to analyze analytical, numerical, and experimental approaches. The review critically compares short‐circuit current estimation, electrodynamic force formulation, thermal analysis, finite element electromagnetic modeling, coupled multiphysics simulation, electromagnetic transient analysis, and standardized experimental validation with respect to accuracy, computational complexity, industrial applicability, and research maturity. The analysis reveals that conventional analytical models remain suitable for preliminary design, whereas high‐fidelity numerical simulations and experimental investigations significantly improve prediction accuracy but require substantial computational resources and validation efforts. Current limitations include inadequate multiphysics integration, limited scalability for converter‐dominated grids, insufficient field‐level validation, and incomplete standardization. Finally, the review identifies emerging research directions involving digital twins, artificial intelligence, physics‐informed modeling, and harmonized testing standards to enable reliable, scalable, and real‐time short‐circuit withstand assessment for next‐generation high‐voltage power systems.
Abstract The bottomside morphological parameters of the ionospheric F2 layer, the thickness parameter B 0 and the shape parameter B 1, are crucial for describing electron density profiles and monitoring space weather. However, existing climatological models and indirect ionosonde approaches have limitations in real‐time applicability and direct analytical fitting, struggling to meet the high‐precision, continuous representation needs of three‐dimensional ionospheric modeling. We propose a direct joint inversion framework based on ionosonde electron density data, combining robust nonlinear least‐squares (NLS) initialization with modern gradient optimization algorithms, including gradient descent, Adam, AdaGrad, and limited‐memory BFGS (L‐BFGS). The convergence performance of these algorithms was systematically compared using global ionosonde observations from 2014 (high solar activity) and 2020 (low solar activity). Results demonstrated that the NLS‐initialized L‐BFGS approach performs best overall in inversion accuracy, convergence stability, and computational efficiency across various conditions. These optimized parameters were then used to quantitatively evaluate the ABT‐2009 empirical model, revealing pronounced spatiotemporal variability in its performance. During high solar activity, the model exhibits systematic biases at low and high latitudes. Conversely, during low solar activity, prediction dispersion increases in summer mid‐latitudes. Persistent error concentration in low‐latitude and polar regions highlights the deficiencies of empirical models in capturing regional variability and dynamic physical processes. This high‐precision framework accurately retrieves ionospheric parameters, effectively diagnosing existing model deficiencies and laying a solid data foundation for future three‐dimensional ionospheric modeling.
Abstract This study introduces an innovative multi‐functional reconfigurable intelligent surface (MF‐RIS) designed to achieve a comprehensive spatial coverage and improved system performance. To maximize both the achievable sum rate and energy efficiency (EE), a non‐convex optimization framework is formulated, focusing on the adjustment of MF‐RIS coefficients while incorporating constraints related to the available power budget and energy conservation requirements. We offer a thorough examination of EE performance in MF‐RIS‐assisted systems and we provide a comparison to traditional RIS architectures by integrating realistic power consumption estimates for active parts and control circuits. This study offers a significant advancement to the field by providing perspectives on the sustainability of MF‐RIS in the upcoming 6G networks.
