An Ultrawideband (UWB) octagonal ring-shaped parasitic resonator-based patch antenna for microwave imaging applications is presented in this study, which is constructed with a diamond-shaped radiating patch, three octagonal, rectangular slotted ring-shaped parasitic resonator elements, and partial slotting ground plane. The main goals of uses of parasitic ring-shaped elements are improving antenna performance. In the prototype, various kinds of slots on the ground plane were investigated, and especially rectangular slots and irregular zigzag slots are applied to enhance bandwidth, gain, efficiency, and radiation directivity. The optimized size of the antenna is 29 × 24 × 1.5 mm3 by using the FR-4 substrate. The overall results illustrate that the antenna has a bandwidth of 8.7 GHz (2.80 ̶ 11.50 GHz) for the reflection coefficient S11 < -10 dB with directional radiation pattern. The maximum gain of the proposed prototype is more than 5.7 dBi, and the average efficiency over the radiating bandwidth is 75%. Different design modifications are performed to attain the most favorable outcome of the proposed antenna. However, the prototype of the proposed antenna is designed and simulated in the 3D simulator CST Microwave Studio 2018 and then effectively fabricated and measured. The investigation throughout the study of the numerical as well as experimental data explicit that the proposed antenna is appropriate for the Ultrawideband-based microwave-imaging fields.
The investigation into new sources of energy with the highest efficiency which are derived from existing energy sources is a significant research area and is attracting a great deal of interest. Radio frequency (RF) energy harvesting is a promising alternative for obtaining energy for wireless devices directly from RF energy sources in the environment. An overview of the energy harvesting concept will be discussed in detail in this paper. Energy harvesting is a very promising method for the development of self-powered electronics. Many applications, such as the Internet of Things (IoT), smart environments, the military or agricultural monitoring depend on the use of sensor networks which require a large variety of small and scattered devices. The low-power operation of such distributed devices requires wireless energy to be obtained from their surroundings in order to achieve safe, self-sufficient and maintenance-free systems. The energy harvesting circuit is known to be an interface between piezoelectric and electro-strictive loads. A modern view of circuitry for energy harvesting is based on power conditioning principles that also involve AC-to-DC conversion and voltage regulation. Throughout the field of energy conversion, energy harvesting circuits often impose electric boundaries for devices, which are important for maximizing the energy that is harvested. The power conversion efficiency (PCE) is described as the ratio between the rectifier's output DC power and the antenna-based RF-input power (before its passage through the corresponding network).
In this article, we propose SNG (single negative) metamaterial fabricated on Mg-Zn ferrite-based flexible microwave composites. Firstly, the flexible composites are synthesized by the sol-gel method having four different molecular compositions of MgxZn(1-x)Fe2O4, which are denoted as Mg20, Mg40, Mg60, and Mg80. The structural, morphological, and microwave properties of the synthesized flexible composites are analyzed using X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), and conventional dielectric assessment kit (DAK) to justify their possible application as dielectric substrate at microwave frequency regime. Thus the average grain size is found from 20 to 24 nm, and the dielectric constants are 6.01, 5.10, 4.19, and 3.28, as well as loss tangents, are 0.002, 0.004, 0.006, and 0.008 for the prepared Mg-Zn ferrites, i.e., Mg20, Mg40, Mg60, and Mg80 respectively. Besides, the prepared low-cost Mg-Zn ferrite composites exhibit high flexibility and lightweight, which makes them a potential candidate as a metamaterial substrate. Furthermore, a single negative (SNG) metamaterial unit cell is fabricated on the prepared, flexible microwave composites, and their essential electromagnetic behaviors are observed. Very good effective medium ratios (EMR) vales are obtained from 14.65 to 18.47, which ensure the compactness of the fabricated prototypes with a physical dimension of 8 × 6.5 mm2. Also, the proposed materials have shown better performances comparing with conventional FR4 and RO4533 materials, and they have covered S-, C-, X-, Ku-, and K-band of microwave frequency region. Thus, the prepared, flexible SNG metamaterials on MgxZn(1-x)Fe2O4 composites are suitable for microwave and flexible technologies.
This work focused on the novel and compact 1-bit symmetrical coding-based metamaterial for radar cross section reduction in terahertz frequencies. A couple of coding particles were constructed to impersonate the elements '0' and '1', which have phase differences of 180°. All the analytical simulations were performed by adopting Computer Simulation Technology Microwave Studio 2019 software. Moreover, the transmission coefficient of the element '1' was examined as well by adopting similar software and validated by a high-frequency structure simulator. Meanwhile, the frequency range from 0 to 3 THz was set in this work. The phase response properties of each element were examined before constructing various coding metamaterial designs in smaller and bigger lattices. The proposed unit cells exhibit phase responses at 0.84 THz and 1.54 THz, respectively. Meanwhile, the analysis of various coding sequences was carried out and they manifest interesting monostatic and bistatic radar cross section (RCS) reduction performances. The Coding Sequence 2 manifests the best bistatic RCS reduction values in smaller lattices, which reduced from -69.8 dBm2 to -65.5 dBm2 at 1.54 THz. On the other hand, the monostatic RCS values for all lattices have an inclined line until they reach a frequency of 1.0 THz from more than -60 dBm2. However, from the 1.0 THz to 3.0 THz frequency range the RCS values have moderate discrepancies among the horizontal line for each lattice. Furthermore, two parametric studies were performed to examine the RCS reduction behaviour, for instance, multi-layer structures and as well tilt positioning of the proposed coding metamaterial. Overall it indicates that the integration of coding-based metamaterial successfully reduced the RCS values.
Metamaterial analysis for microwave frequencies is a common practice. However, adopting a multi-layered design is unique in the concept of miniaturisation, thus requiring extensive research for optimal performance. This study focuses on a multi-layered symmetric metamaterial design for C- and X-band applications. All simulation analyses were performed analytically using Computer Simulation Technology Studio Suite 2019. The performances of the proposed metamaterial design were analysed through several parametric studies. Based on the observation, the proposed metamaterial unit cell design manifested resonant frequencies at 7.63 GHz (C-band) and 9.56 GHz (X-band). Moreover, the analysis of effective medium parameters was also included in this study. High-Frequency Simulation 15.0 and Advanced Design System 2020 software validated the transmission coefficient results. Simultaneously, the proposed multi-layered metamaterial design with Rogers RO3006 substrate material exhibited a unique transmission coefficient using double, triple, and quadruple layers. The two resonant frequencies in the unit cell design were successfully increased to three in the double-layer structure at 6.34 GHz (C-band), 8.46 and 11.13 GHz (X-band). The proposed unit cell design was arranged in an array structure to analyse the performance changes in the transmission coefficient. Overall, the proposed metamaterial design accomplished the miniaturisation concept by arranging unit cells in a multi-layer structure and possesses unique properties such as a highly effective medium ratio and left-handed characteristics.
Modernizing power systems into smart grids has introduced numerous benefits, including enhanced efficiency, reliability, and integration of renewable energy sources. However, this advancement has also increased vulnerability to cyber threats, particularly False Data Injection Attacks (FDIAs). Traditional Intrusion Detection Systems (IDS) often fall short in identifying sophisticated FDIAs due to their reliance on predefined rules and signatures. This paper addresses this gap by proposing a novel IDS that utilizes hybrid feature selection and deep learning classifiers to detect FDIAs in smart grids. The main objective is to enhance the accuracy and robustness of IDS in smart grids. The proposed methodology combines Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO) for hybrid feature selection, ensuring the selection of the most relevant features for detecting FDIAs. Additionally, the IDS employs a hybrid deep learning classifier that integrates Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks to capture the smart grid data's spatial and temporal features. The dataset used for evaluation, the Industrial Control System (ICS) Cyber Attack Dataset (Power System Dataset) consists of various FDIA scenarios simulated in a smart grid environment. Experimental results demonstrate that the proposed IDS framework significantly outperforms traditional methods. The hybrid feature selection effectively reduces the dimensionality of the dataset, improving computational efficiency and detection performance. The hybrid deep learning classifier performs better in key metrics, including accuracy, recall, precision, and F-measure. Precisely, the proposed approach attains higher accuracy by accurately identifying true positives and minimizing false negatives, ensuring the reliable operation of smart grids. Recall is enhanced by capturing critical features relevant to all attack types, while precision is improved by reducing false positives, leading to fewer unnecessary interventions. The F-measure balances recall and precision, indicating a robust and reliable detection system. This study presents a practical dual-hybrid IDS framework for detecting FDIAs in smart grids, addressing the limitations of existing IDS techniques. Future research should focus on integrating real-world smart grid data for validation, developing adaptive learning mechanisms, exploring other bio-inspired optimization algorithms, and addressing real-time processing and scalability challenges in large-scale deployments.
A metamaterial-incorporated high-gain and broadband dipole antenna is proposed for 5G mm-wave applications. The designed high refractive index metamaterial (HRIM) properties are presented in detail with supporting results. The proposed dipole antenna achieved broadband features, and the antenna gain increased significantly by incorporating HRIM in the electromagnetic (EM) wave propagation path. Besides, the EM wave aggregation engineering of utilizing the HRIM on the dipole antenna is analyzed using the electric field, magnetic field, and power flow distributions. Both conventional and HRIM-based dipole antenna (HRIMDA) were fabricated on thin (0.254 mm) Rogers RT5880 substrate material with a low dielectric constant of 2.2, where the noticeable gain enhancement by HRIM is observed. The measured results show the operational bandwidth (BW) from 23 to 38 GHz frequency, and the highest gain of 9.5 dBi is accomplished at 35 GHz frequency. Finally, a four-element MIMO configuration is numerically and experimentally analyzed where the isolation of the two conjugated MIMO elements is 9.9 were also achieved. Hence, the proposed HRIM base dipole antenna is a potential candidate for 5G mm-wave applications.