A thin broadband dual-layer radar absorber based on periodic Frequency Selective Surfaces (FSS) to tackle Electromagnetic Interference (EMI) in radomes is presented in this article. The proposed structure consists of periodically arranged metallic patterns printed on two dielectric substrates separated by an optimized air gap. Under normal incidence, the proposed structure exhibits at least 89.7% of absorption in the whole band of 4.8 GHz to 11.1 GHz for both Transverse Electric (TE) and Magnetic (TM) polarizations. For oblique incidences, a very slight decrease in the bandwidth is observed in the upper frequency band until 30° and the absorption remains very interesting for higher incidences. The structure is λ/7.2 (λ is the wavelength in free space) thin compared to the center frequency (8.2 GHz). In addition, parametric studies have demonstrated that at least 90% of absorption can be produced with our structure by adjusting the thicknesses of the dielectric substrates. Another issue that is presented and discussed in this paper is a new approach for evaluating the performance of absorbers. In fact, studies show that the absorber can compete with other recent broadband absorbers. After fabricating the structure, the measurements were found to be in good agreement with the simulation results.

Current artificial magnetic conductor (AMC) designs use metallic patterns on rigid substrates and focus on shapes and sizes of AMC structures, rather than on material performance, which has hindered operation bandwidth and design flexibility. Here, we introduce printed graphene AMC-based broadband and flexible microwave radar absorbers, which not only redirect but also absorb the incident wave so to broaden the operation bandwidth. Contrasting to other reported works, the phase characteristics of the AMCs are realized through the control of the surface resistance provided by printed graphene laminates. We produced a variety of AMC structures, composed of printed graphene circular ring arrays with exactly the same shape and size, but different sheet resistances. By carefully designing the sheet resistance of printed graphene laminates, the optimized anti-phase reflection cancellation between AMCs can be achieved. With printed graphene AMCs and flexible dielectric substrate, the absorber presented in this work has a broadband effective absorption (above 90% absorptivity) from 7.58 GHz to 18, is polarization insensitive under normal incident, and can work at relatively wide incident angles. Furthermore, this absorber is capable of bending easily with notable performance, which makes it ideal for applications with irregular and uneven shapes.

We report the simulation, fabrication, and experimental characterization of a single-layer broadband, polarization-insensitive and wide-angle near perfect metamaterial absorber (MA) in the microwave regime. The topology of the resonators is chosen in such a way that is capable of supporting simultaneously multiple plasmon resonances at adjacent frequencies, which lead to a broadband operation of the MA. Absorption larger than 80% at normal incidence covering a broad frequency range (between 7.4 GHz and 10.4 GHz) is demonstrated experimentally and through numerical simulations. Furthermore, the performance of the metamaterial absorber is kept constant up to an incident angle of 30°, for both TE and TM-polarizations. In addition, a hybrid model of the MA is proposed and implemented numerically in order to dynamically tune the absorption window. The hybrid MA is controlled by incorporating vanadium dioxide (VO₂) temperature-driven metal-insulator phase transition material, which enables the transition from broadband (80% absorption and 3 GHz bandwidth) to narrowband (80% absorption and 0.7 GHz bandwidth) absorption window. Our proposed single-layer MA offers substantial advantages due to its low-cost and simplicity of fabrication. The results are very promising, suggesting a potential use of the MA in wide variety of applications including solar energy harvesting, biosensing, imaging, and stealth technology.

In this article, a single layer co-polarization broadband radar absorber is presented. Under normal incidence, it achieves at least 90% of absorption from 5.6 GHz to 9.1 GHz for both Transverse Electric (TE) and Transverse Magnetic (TM) polarizations. Our contribution and the challenge of this work is to achieve broadband absorption using a very thin single layer dielectric and it is achieved by rotating the resonating element by 45°. An original optimized Underlined U shape has been developed for the resonating element which provides a broadband co-polarization absorption. The structure is 12.7 times thinner than the wavelength at the center frequency. To understand the absorption mechanism, the transmission line model of an absorber and the three near unity absorption peaks at 5.87 GHz, 7.16 GHz and 8.82 GHz have been used to study the electric and magnetic fields. The physical insight of how the three near unity absorption peaks are achieved has also been discussed. After fabricating the structure, the measurements were found to be in good agreement with the simulation results. Furthermore, with the proposed original UUSR resonating element, the operational bandwidth to thickness ratio of 6.43 is obtained making the proposed UUSR very competitive.

In today’s world, the significance of reducing energy consumption globally is increasing, making it imperative to prioritize energy efficiency in 5th-generation (5G) networks. However, it is crucial to ensure that these energy-saving measures do not compromise the Key Performance Indicators (KPIs), such as user experience, quality of service (QoS), or other important aspects of the network. Advanced wireless technologies have been integrated into 5G network designs at multiple network layers to address this difficulty. The integration of emerging technology trends, such as machine learning (ML), which is a subset of artificial intelligence (AI), and AI’s rapid improvements have made the integration of these trends into 5G networks a significant topic of research. The primary objective of this survey is to analyze AI’s integration into 5G networks for enhanced energy efficiency. By exploring this intersection between AI and 5G, we aim to identify potential strategies and techniques for optimizing energy consumption while maintaining the desired network performance and user experience.