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This study presents the design and optimization of a microstrip monopole antenna for 5G sub‐6 GHz applications, employing a deep learning‐based surrogate model combined with honeybee mating optimization (HBMO). The studied antenna structure employs air via arrays, intended to enhance antenna performance, including improved impedance matching and increased bandwidth. It is important to note that, unlike conventional antennas, the proposed design does not include a fully enclosed metallic cavity similar to a substrate integrated waveguide (SIW) antenna designs. A sensitivity analysis was conducted to assess the impact of these parameters, emphasizing the need for optimal tuning. To generate training and test datasets efficiently, Latin hypercube sampling (LHS) was used. A convolutional neural network (CNN) surrogate model was trained, outperforming other machine learning (ML) algorithms in predictive accuracy and generalization. The proposed CNN‐HBMO framework reduced computational costs by minimizing the need for expensive electromagnetic (EM) simulations, enabling rapid design space exploration. The optimized antenna was fabricated and validated through experimental measurements, achieving 2–3 dBi gain and 11 < −10 dB across the 2.7–5.2 GHz band. Compared to existing designs, the proposed antenna offers a compact size (34 × 34 mm) with competitive performance, making it suitable for multi‐band 5G applications.

This paper presents an overview of the different methods used for sensitivity (i.e., responsivity and noise equivalent power) determination of state-of-the-art field-effect transistor-based THz detectors/sensors. We point out that the reported result may depend very much on the method used to determine the effective area of the sensor, often leading to discrepancies of up to orders of magnitude. The challenges that arise when selecting a proper method for characterisation are demonstrated using the example of a 2×7 detector array. This array utilises field-effect transistors and monolithically integrated patch antennas at 620 GHz. The directivities of the individual antennas were simulated and determined from the measured angle dependence of the rectified voltage, as a function of tilting in the E- and H-planes. Furthermore, this study shows that the experimentally determined directivity and simulations imply that the part of radiation might still propagate in the substrate, resulting in modification of the sensor effective area. Our work summarises the methods for determining sensitivity which are paving the way towards the unified scientific metrology of FET-based THz sensors, which is important for both researchers competing for records, potential users, and system designers.

Focused microwave breast hyperthermia (FMBH) employs a phased antenna array to perform beamforming that can focus microwave energy at targeted breast tumors. Selective heating of the tumor endows the hyperthermia treatment with high accuracy and low side effects. The effect of FMBH is highly dependent on the applied phased antenna array. This work investigates the effect of polarizations of antenna elements on the microwave-focusing results by simulations. We explore two kinds of antenna arrays with the same number of elements using different digital realistic human breast phantoms. The first array has all the elements’ polarization in the vertical plane of the breast, while the second array has half of the elements’ polarization in the vertical plane and the other half in the transverse plane, i.e., cross polarization. In total, 96 sets of different simulations are performed, and the results show that the second array leads to a better focusing effect in dense breasts than the first array. This work is very meaningful for the potential improvement of the antenna array for FMBH, which is of great significance for the future clinical applications of FMBH. The antenna array with cross polarization can also be applied in microwave imaging and sensing for biomedical applications.

In this paper, a high-isolation multiple-input/multiple-output (MIMO) microstrip monopole antenna array is investigated. To reduce the mutual coupling between antenna elements, a novel composite parasitic element constituted by a T-shaped ground branch and an isolated branch was designed and analyzed. The proposed composite parasitic element is capable of generating a unique three-dimensional weak electric field, which can effectively suppress the mutual coupling between the antenna elements. To give an intuitive illustration about the design principle and decoupling strategy of the proposed antenna, the antenna design procedure was ingeniously divided into four steps, and three types of decoupling structures during the antenna evolution were meticulously analyzed at both the theoretical and the physical level. To validate the proposed decoupling concept, the antenna prototype was fabricated, measured, and evaluated. The reflection coefficient, transmission coefficient, radiation pattern, and antenna gain were studied, and remarkable consistency between the measured and simulated results was observed. The simulations showed that the antenna has a peak gain of 3.5 dBi, a low envelope correlation coefficient (ECC < 0.001), and a high radiation efficiency (radiation efficiency > 0.9). Parameters of the proposed MIMO antenna including electrical dimension, highest isolation level, and 20 dB isolation bandwidth were evaluated. Compared with the previous similar designs, the proposed antenna exhibits attractive features including compressed dimension (0.55λ0 × 0.46λ0), extremely high isolation level (approximately 43 dB), fabulous 20 dB isolation bandwidth (3.11–3.78 GHz, 19.4%), a high diversity gain (DG > 9.99 dB), an appropriate mean effective gain (−3.5 dB < MEG < −3 dB), and low design complexity.

Full‐wave electromagnetic simulators, such as HFSS and CST, are essential in antenna design and analysis, but their high computational resources and time cost often limit the amount of training data available for building surrogate models. To enhance modelling accuracy, particularly in contexts where the constraint of limited data arises, this study proposes a data augmentation (DA) framework that integrates a conditional variational autoencoder (CVAE) with deep metric learning (DML), where a contrastive loss is employed to ensure the quality of the synthetic samples. This approach is experimentally validated on the proposed wideband circularly polarized S‐shaped slot antenna (WB‐SSA), where the surrogate model is built as an inverse design, mapping multi‐objective performances, including S 11 , axial ratio (AR), and gain, to the corresponding structural parameters. Specifically, the CVAE encoder learns to map the structural parameter sets to a latent distribution, conditioned on the multi‐objective performances. A contrastive loss regularizes this latent space by separating latent vectors with divergent multi‐objective performances. The decoder, in turn, generates synthetic samples from randomly generated multi‐objective vectors, thereby producing more reliable synthetic samples for DA application. Experimental results demonstrate that the proposed method contributes to a clear improvement in the performance of the inverse model.

The rise of CubeSats has unlocked opportunities for cutting-edge space missions with reduced costs and accelerated development timelines. CubeSats necessitate a high-gain antenna that can fit within a tightly confined space. This paper is primarily concerned with designing a compact Ku-band offset cylindrical reflector antenna for a CubeSat-based Earth Observation mission, with the goal of monitoring Arctic snow and sea ice. The development of a Ku-band offset cylindrical reflector, with a compact aperture of 110 × 149 mm2 (6.3λ × 8.5λ), is described alongside a patch array feed consisting of 2 × 8 elements. The patch array feed is designed using a lightweight Rogers substrate and is utilized to test the reflector. Adopting an offset configuration helped prevent gain loss due to feed blockage. Analyzing the reflector antenna, including the feed, thorough simulations and measurements indicates that achieving a gain of 25 dBi and an aperture efficiency of 52% at 17.2 GHz is attainable. The reflector’s cylindrical shape and compact size facilitate the design of a simple mechanism for reflector deployment, enabling the antenna to be stored within 1U. The array feed and reflector antenna have been fabricated and tested, demonstrating good consistency between the simulation and measurement outcomes.

Based on the problem of electromagnetic interference in the darkroom of connected vehicle communication systems, a research method is proposed to evaluate the wireless communication quality between antennas using gain coupling. The electromagnetic compatibility of the far-field radiation pattern, radiation coupling degree, and near-field radiation pattern of the vehicle antenna and the vehicle antenna model were analyzed by establishing a 3D simulation model of the vehicle antenna and the external transmitting antenna. Based on the obtained simulation data, the arrangement scheme of the transmitting antenna in the darkroom can be determined. The performance index of the automotive OTA antenna can then be tested using the determined arrangement scheme, which can effectively reduce costs and provide reliable data.

In this work, a frequency- and pattern-reconfigurable Yagi antenna based on liquid metal (LM) switches is proposed for pressure sensing and health monitoring. The proposed antenna consists of a dipole radiator, a reflector, a director, a dielectric substrate, and four flexible LM switches. Benefitted from the switching effect of the LM switches under external pressure, the frequency and radiation pattern of the antenna can be reconfigured. When the LM switch is fully or partially turned on, the radiation directions of the antenna are bidirectionally end-shot and end-fired, respectively. The operating frequency of the antenna can be tuned from 2.28 GHz to 2.5 GHz. It is shown that a maximum gain of 6 dBi can be obtained. A sample was fabricated and measured, and the experimental results were in good agreement with the simulations. The reconfigurable antenna can be applied in wireless pressure-sensing and health-monitoring systems.

Parabolic cylindrical antennas are characterized by their structural simplicity, high radiation efficiency, and low manufacturing costs. Consequently, they are widely used in Earth observation and serve as a viable option for spaceborne Synthetic Aperture Radar (SAR) systems. However, structural errors in the phased array feed and the parabolic cylindrical reflector are inevitable during manufacturing, assembly, and operation. These errors significantly degrade the accuracy of antenna pattern models. To address this issue, this paper proposes a comprehensive radiation pattern model that accounts for structural errors in both the linear feed and the reflector. This approach enables precise pattern prediction and efficient in-orbit calibration. Specifically, the reflected far-field pattern is first calculated using the field superposition principle and the Physical Optics (PO) method. Specifically, the combined phase effects resulting from feed and reflector structural errors are superimposed to establish a direct integration pattern model for the parabolic cylindrical antenna. Given the high computational complexity of the direct integration model, a simplified model based on Fresnel approximation is proposed. This approach significantly reduces integration complexity while preserving the quadratic phase characteristics of the main lobe, thereby substantially improving computational efficiency. Simulation results verify that the simplified model maintains high accuracy in both normalized amplitude and phase. Furthermore, a partitioned calibration method is proposed to compensate for the absolute gain deviation inherent in the simplified model. By integrating weighting relationships derived from sensitivity analysis of individual errors, an empirical parameter is defined to quantify the correlation between total structural errors, antenna performance, and the prediction accuracy of the simplified model. The results indicate that reflector structural errors are the dominant factor affecting the overall performance of the antenna. In contrast, the prediction accuracy of the simplified model is found to be more sensitive to feed structural errors. The simplified model exhibits tolerance to structural errors far exceeding the wavelength, enabling it to effectively replace the direct integration model. This work provides new theoretical foundations and technical methods for tolerance design, performance assurance, in-orbit testing, and calibration of parabolic cylindrical antennas.