This study presents the design and analysis of a compact 28 GHz MIMO antenna for 5G wireless networks, incorporating simulations, measurements, and machine learning (ML) techniques to optimize its performance. With dimensions of 3.19 λ₀ × 3.19 λ₀, the antenna offers a bandwidth of 5.1 GHz, a peak gain of 9.43 dBi, high isolation of 31.37 dB, and an efficiency of 99.6%. Simulations conducted in CST Studio were validated through prototype measurements, showing strong agreement between the measured and simulated results. To further validate the design, an equivalent RLC circuit model was developed and analyzed using ADS, with the reflection coefficient results closely matching those from CST. Additionally, supervised ML techniques were employed to predict the antenna’s gain, evaluating nine models using metrics such as R-squared, variance score, mean absolute error, and root mean squared error. Among the models, Random Forest Regression achieved the highest accuracy, delivering approximately 99% reliability in gain prediction. This integration of machine learning with antenna design underscores its potential to optimize performance and enhance design efficiency. With its compact size, high isolation, and exceptional efficiency, the proposed antenna is a promising candidate for 28 GHz 5G applications, offering innovative solutions for next-generation wireless communication.

The performance of wireless 5 G communication networks can be enhanced by combining multiple-input multiple-output (MIMO) antennas with machine learning (ML). The suggested antenna, which is constructed on a Rogers 5880 substrate, is well-suited for usage in the high bands of 5 G applications due to its 27 dB isolation and bandwidth of 35.181-39.689 (4.508) GHz within a-10 dB range. Besides being compact (measuring 37 mm x 24 mm), it boasts an impressive maximum gain of 8.09 dB and an efficiency level of 98.2 %. The methods explored in this research are the RLC equivalent circuit model and simulations with validated measurements. An advanced design system (ADS) is utilized to compare the return loss because of CST to create a model like the suggested MPA. The next step is extensive data sampling using CST MWS simulation, followed by applying supervised regression ML techniques. Lasso regression yields excellent results in terms of accuracy and achieves the lowest degree of error when testing the bandwidth prediction. Considering everything, the antenna stands out as a top choice for the 5 G communication system's high band. Designing a small MIMO antenna for 38 GHz mm-wave 5 G applications presents challenges because it requires balancing high performance while minimizing mutual coupling between closely spaced elements and dealing with high-frequency complexities.

A multipurpose antenna system that can handle a broad area of frequencies is crucial in the effort to build up widespread 5G Internet-of-Things (IoT) networks. For fifth-generation Internet-of-things applications, this research introduces a new multi-band antenna that can operate in the sub-6 GHz band (2-7 GHz), Ku-band (13-17.5 GHz), and millimeter wave band (25-39 GHz). The antenna achieves a remarkable three-band operational bandwidth through cleverly integrated slots and parasitic components. Maximum realized gain of 4.3 dBi in the sub-6 GHz band, 5.5 dBi in the Ku-band, and 9.9 dBi in the millimeter wave (mm-wave) band for 3D MIMO setup is ensured. In addition, the machine learning prediction is used to verify the single element realized gain, and the results demonstrate that it performs admirably with an accuracy of more than 89% using the random forest regression model throughout the entire frequency spectrum. A 6-port, one-of-a-kind MIMO design with strong diversity performance is built from the single-element configuration. This 6-port MIMO system uses a new codesign technique to achieve 360-degree coverage in the elevation and azimuth planes, exceptional isolation (21 dB at sub-6 GHz band, 25 dB at the Ku-band, and 30 dB at mm-wave band), and pattern diversity. This MIMO antenna module is a shining example of the future, with the potential to completely alter the state of affairs in terms of 5G IoT connectivity in settings such as smart homes, offices, cities, vehicle-to-everything communications, and broadcast satellite service (BSS).

The present study outlines the development and execution of a unique, condensed, ultrawideband microstrip patch antenna through the utilization of CST Microwave Studio software. The aforementioned antenna, with dimensions of 15 × 18.30 × 1.6 mm3, has been designed with a particular focus on its utility in the context of satellite communication applications. The substrate utilized in its construction is Rogers RT5880 material. The antenna exhibits a noteworthy characteristic of achieving a wide range of bandwidth coverage, estimated to be around 140.39

This paper presents the findings about implementing a machine learning (ML) technique to optimize the performance of 5 G mm wave applications utilizing multiple-input multiple-output (MIMO) antennas operating at the 28 GHz frequency band. This article examines various methodologies, including simulation, measurement, and the utilization of an RLC-equivalent circuit model, to evaluate the appropriateness of an antenna for its intended applications. In addition to its compact dimensions, the proposed design exhibits a maximum gain of 10.34 dBi, superior isolation exceeding 26 dB, and a broad bandwidth of 16.56 % Centered at 28 GHz and spanning from 25.905 to 30.544 GHz. Another supervised regression machine learning technique is utilized to predict the antenna's gain accurately. Machine learning (ML) models can be assessed by several measures, such as the variance score, R square, mean square error (MSE), mean absolute error (MAE), root mean square error (RMSE), and Mean Absolute Percentage Error (MAPE). Among the six machine learning models considered, it is seen that the Gaussian Process Regression (GPR) model exhibits the lowest error and achieves the highest level of accuracy in forecasting gain. The antenna under consideration has promising qualities for its intended use in high-band 5 G applications. This is evidenced by the modelling findings obtained from Computer Simulation Technology (CST) and Advanced Design System (ADS)and the measured and projected results derived using machine learning methodologies.

This paper introduces a compact tuneable metamaterial (MTM) unit cell featuring a tri-hexagon and tri-square split ring resonator (THTSSSR) structure designed for 5G communication applications. Metamaterials are employed to achieve unique electromagnetic properties not found in natural materials. The design process involves the arrangement of three square rings and three hexagon rings as metallic patches on a Rogers substrate (RT 5880), measuring 7 x 7 mm2 with a thickness of 1.575 mm. The proposed design exhibits double negative (DNG) properties, with resonances in the transmission coefficient (S21) at 3.493 GHz and a bandwidth of -10 dB covering frequencies between 3.057 and 3.711 GHz. Numerical simulations conducted using finite-integration techniques (FIT) in CST Microwave Studio validate the design's effectiveness, with confirmation through the Advanced Design System (ADS). The MTM unit cell demonstrates tuneable attributes, including negative permittivity ranging from 3.39 to 5 GHz and negative permeability from 3.39 to 3.86 GHz. These findings highlight the compactness and tunability of the proposed design, making it promising for 5G communication applications.

Yagi antennas are useful for wireless communications because of the directional gain they provide, allowing the antenna to concentrate the signal in either the transmission or reception direction. It is built on a substrate made of FR-4, this antenna has a return loss of -46.85 dB at 3.6 GHz and a bandwidth of 3.3-4.2 GHz within a -10 dB range, making it ideal for use in the n77 bands. Not only is it small, with a size of 0.642 lambda 0 x 0.583 lambda 0, but it also has a maximum gain of 7.95 dB and a maximum directivity of 8.58 dB. This study investigates several approaches to estimating the performance of an antenna. These approaches include simulation with a variety of software tools, including as CST, HFSS, and Altair Feko; curve fitting technology; and the RLC equivalent circuit model. After that, simulation with CST MWS is used to collect a large amount of data samples, and then supervised regression machine learning (ML) methods are used to determine the resonance frequency and bandwidth of the antenna. When it comes to predicting bandwidth and frequency, Random Forest Regression demonstrates an exceptional level of performance, particularly when comparing with the results produced by curve-fitting tools, neural networks, and regression machine learning models. When all of these considerations are taken into account, it is clear that the antenna is an outstanding option for the n77 band of a 5G communication system.

A rhombus shaped wearable textile patch antenna with inset-fed concept for sub-6 GHz 5G is proposed in this paper. By introducing rhombus-shape structure for the first time in the wearable antenna domain, the gain of the antenna has been enhanced significantly. The Felt substrate used has relative permittivity of 1.45 and thickness of 3 mm. The proposed antenna with a total size of 60 mm x 57 mm operated at n78 and n77 band of the sub-6 GHz with overall bandwidth of 300 MHz when placed on-body and gain value of 5.099 dBi when bent at 30 degrees in free space. Besides, the antenna was robust in operating at the desired frequency at bending and fully wet condition. The proposed antenna achieved good directional radiation patterns, low SAR value and high antenna gain at the desired frequency band. The proposed design can be a valuable candidate for body-centric wearable communications.

One of the leading candidates for the next fifth generation of (5G) and body-centric wireless communications is millimeter-wave frequencies. In this study, a wideband tunable metamaterial (MTM) consisting of T-H shaped symmetric resonator is presented for body-centric applications operating in the millimeter-wave frequency band centered at 28 GHz. The characteristics of the proposed MTM are examined through wave propagation in both Z and X directions. It has a wide operating frequency range of 5.6 GHz for waves travelling along the Z-axis, with DNG characteristics at 26.2 GHz resonance frequency. However, it represents a negative epsilon metamaterial (ENG) range during X-axis wave propagation in the 25-29.4 GHz frequency range. The metamaterial is constructed on a Rogers (RT-5880) substrate and has a compact size, with overall dimensions of 0.420 lambda o x 0.420 lambda o. A proposed Y-shaped antenna is developed with a compact size of 1.36 lambda o x 1.82 lambda o to cover the 5G at 28 GHz. The single-Y-shaped antenna consists of a radiating patch, Rogers substrate, full ground plane, air bandgap (ABG), and array of DNG MTM. Thus, the array of MTM has been applied to validate the effect in the overall antenna performance such as gain which has been increased from 5.5 dBi to 8.5 dBi. The experimental, simulated results, and equivalent circuit model using Advanced Design Software (ADS) for validation functions showed that the completed results are comparable. The proposed mm-wave metamaterial is expected to be a good candidate for modern 5G wireless communication system components, especially to enhance the antenna gain and isolation. The proposed antenna loaded with MTM is a suitable contender for the upcoming 5G mm wave mobile handheld devices.

Metasurface absorbers (MSAs) are of significant importance in a wide range of applications, such as in the field of stealth technology. Nevertheless, conventional designs demonstrate limited flexible characteristics and a lack of transparency, hence constraining their suitability for certain radar stealth applications. This study introduces a novel MSA operating in the broad microwave range, which exhibits both optical transparency and flexibility. The structure consists of a flexible substrate made of polyvinyl chloride (PVC), along with a resistive film composed of indium tin oxide (ITO). The proposed structure exhibits the ability to effectively absorb over 90% of the energy carried by incident electromagnetic (EM) waves across the frequency range of 9.85–41.76 GHz within an angular range of 0° to 60°. In addition, to assess the efficacy of the absorption performance, an examination of the radar cross-section (RCS) characteristics is conducted. The results indicate a reduction of over 10 dB across the aforementioned broad frequency spectrum, regardless of the central angle.

The paper outlines a methodology to diminish mutual coupling in 4-port dual-band MIMO textile antenna for biomedical applications. This antenna leverages MIMO technology and Wireless Body Area Network (WBAN) for operation in two distinct frequency bands at (3.5 & 2.45 GHz). The antenna is made up of four octagonal patch antennas, each having a bar and a split-ring (SR) slot with 47.2 x 31 mm2 dimensions for each patch. A hybrid mutual coupling (MC) approach was investigated with closely spaced patches (up to 0.05 lambda). Various bending setups have been selected along with flat case to examine the antennas' resilience which demonstrate such agreement between measured and simulated findings. Furthermore, the MC is only -20 dB, the envelope correlation coefficient (ECC) is 0.001, and maximum peak measured gain of 5.2 dBi is achieved with lowest peak specific absorption rate (SAR) value. Even when bent at a 60 degrees angle along with y-axis and x-axis, the antenna retains a decent gain of 1.861 dBi in the low frequency region and 5.479 dBi at high frequency band. Surprisingly, the antenna outperforms the attenuation produced by the lossy effects of the human body, indicating a favorable alignment between the modelled and observed findings.

Microwave medical imaging (MMI) is experiencing a surge in research interest, with antenna performance emerging as a key area for improvement. This work addresses this need by enhancing the directivity of a compact UWB antenna using a Yagi-Uda-inspired reflector antenna. The proposed reflector-loaded antenna (RLA) exhibited significant gain and directivity improvements compared to a non-directional reference antenna. When analyzed for MMI applications, the RLA showed a maximum increase of 4 dBi in the realized gain and of 14.26 dB in the transmitted field strength within a human breast model. Moreover, it preserved the shape of time-domain input signals with a high correlation factor of 94.86%. To further validate our approach, another non-directional antenna with proven head imaging capabilities was modified with a reflector, achieving similar directivity enhancements. The combined results demonstrate the feasibility of RLAs for improved performance in MMI systems.

In this study, a microstrip patch antenna was designed to enable complete coverage of satellite communication. The antenna is capable of covering almost four bands, including S, C, Ka, and Q/V bands. The bandwidth achieved for these bands is relatively large, with the maximum bandwidth of 15.6 GHz achieved at the Q/V band and 11.4 GHz achieved at the Ka band. In the microwave range, the S and C bands have a bandwidth of 2.1 GHz, which is considerable. The antenna achieves a maximum gain of 9.1 dBi at the Q/V band. Moreover, the efficiency of the antenna is remarkably high, with almost 99

This paper introduces a low-profile multiband antenna that operates in both the microwave and millimeter-wave (mm-wave) frequency bands. The proposed antenna offers wide bandwidth coverage in the ranges of 3.2-3.7 GHz, 4.0-5.5 GHz, 5.8-6.6 GHz, 6.7-7.4 GHz, and 7.6-10 GHz. It also resonates within the 25.5-29 GHz range in the mm-wave band. The antenna achieves a radiation efficiency of 67% and a maximum gain of 1.8 dBi in the microwave band at 8.5 GHz, and a radiation efficiency of 79% with a maximum gain of 4.9 dBi in the mm-wave band at 28 GHz.

This study introduces a MIMO antenna system incorporating an epsilon negative Meta Surface (MS). The system’s architects intended for it to have a large usable frequency range, high gain, narrow inter-component spacing, and superior isolation properties with four elements of MIMO antenna that are strategically organized in an orthogonal arrangement and a compact form factor measuring 41 × 41 × 1.6 mm3, utilizing a low-loss Rogers RT5880 substrate. The architecture of the antenna is characterized by integrating a multi-slotted radiating patch, a partial ground plane, and an epsilon-negative Meta Surface. This integration is done by a 7 × 7 Metamaterial array at the back of the MIMO antenna with a dimension of 41 × 41 × 1.6 mm3, resulting in a collective enhancement of the antenna’s overall performance by affecting the phase, amplitude, electromagnetic field and reducing the backward radiation. The separation between the Meta-surface and the MIMO antenna is established at a distance of 6 mm. The antenna’s exceptional super wideband performance is increased from 2–19 GHz to 1.9–20 GHz after using the MS. Moreover, isolation increases from 20 dB to 25.5 dB, Realized gain from 4.5 dBi to 8 dBi, and radiation efficiency from 77% to 89% across the operational bandwidth. The MIMO antenna exhibits remarkable diversity characteristics, as indicated by an envelope correlation coefficient (ECC) of <0.004, a diversity gain (DG) surpassing 9.98 dB, a channel capacity loss (CCL) below 0.3, and a total active reflection coefficient (TARC) measuring 12 dB. Furthermore, a circuit analogous to a resistor–inductor–capacitor (RLC) system is constructed, and four regression methods from the field of machine learning are employed to validate the gain and efficiency achieved. Notably, the linear regression model exhibits exceptional performance, achieving an accuracy of 99%. The MIMO antenna design demonstrates significant potential for many applications in the Internet of Things (IoT), specifically focusing on Vehicle-to-Everything (V2X) communications. These highlight its appropriateness for emerging IoT sectors.

This paper proposes a new, compact, wideband 3D horn antenna for biomedical wireless applications such as cancer and tumor detection. In order to achieve the best penetration level, the antenna has been built and tuned to work in the low frequency range of 0.48-1.24 GHz, which can exhibit a high-resolution detection result. The proposed applicator is a double ridge horn antenna (DRHA). The layout and operation of the key needed components to assemble a wideband hyperthermia system are provided in this study. We assume a cylindrical human tissue phantom with wideband dispersive tissue properties, and simulation results are given. The resulting field maps are displayed in several planes to illustrate the energy localization process. The findings indicate that, in contrast to traditional narrowband systems, wideband operation may improve energy localization in deep tumor locations while eliminating hot spots. The suggested antenna was built and measured to verify the result.

The concept, performance, and analyses of distinctive, miniaturized metamaterial (MTM) unit cell addressing the forthcoming Sub 6 GHz 5G applications are presented in this paper. Two circular split-ring resonators (CSRR) with two parallel rectangular copper elements in front of the design and a slotted square element in the background make up the suggested metamaterial. It has a line segment with tunable features that is positioned in the center of the little ring copper structure. The suggested design offers a significant operating frequency band of 220 MHz together with a resonance of transmission coefficient S21 at 3.5 GHz. Furthermore, in two (z & x) principal axes of wave propagation, wide-range achievement, single/double-negative (S/DNG) refractive index, negative permittivity, and near-zero permeability properties were demonstrated. Through varying central slotted-strip line length, resonance frequencies can be selectively altered. Moreover, the metamaterial has overall dimensions of 9 x 9 mm2 and is composed on a Rogers 5880 RT substrate. In order to create the suggested MTM's equivalent circuit, which shows similar coefficient of transmission (S21), a proposed design's numerical simulation is carried out in the CST micro-wave studio. This simulation is after that put to comparison with manufacturing of the design.

A compact oval edge slotted Ultrawideband (UWB) monopole textile antenna with truncated ground plane for breast cancer detection is presented in this paper. A comprehensively reduced size of the proposed UWB antenna is achieved. The overall dimensions of 18 x 19 x 1.84 mm 3 , covering a super wide bandwidth of range between 7.52 and 23.43 GHz is obtained. A total impedance bandwidth (<-10 dB) of 15.91 GHz is achieved with maximum exhibited radiation efficiency of 87.77 % at 8.64 GHz and maximum realized gain of 5.98 dBi at 23.43 GHz.

This article proposes an eight-port octagonal-shaped multiple-input multiple-output (MIMO) wideband 3D antenna system for terahertz (THz) applications. The 3D configuration of the proposed THz-MIMO antenna is placed on a 55-mu m-thick polyimide substrate. A modified butterfly-shaped radiating patch and full ground plane make up the single antenna element. Every antenna element spans a wide impedance bandwidth for THz spectrums from 0.9- to 1.68-THz frequency band, a frequency operating range with the highest radiation efficiency of 98% and is printed in a compact size of 130 x 110 mu m2 (0.00004 lambda o$$ {\lambda}_o $$ x 0.00005 lambda o$$ {\lambda}_o $$, with respect to the lowest operating frequency). The THz-MIMO antenna system with eight ports is composed of both symmetric and nonsymmetric array arrangements. For configurations that are symmetric or nonsymmetric, the estimated MIMO performance parameters, envelope correlation coefficient (ECC) < 0.01 within allowable bounds, diversity gain (DG) exceeding 9.99 dB, total active reflection coefficient (TARC) < -10 dB, and channel capacity loss (CCL) below 0.2 bits/s/Hz, and the exhibited gain is above 7.5 dBi. Furthermore, another approach, such as supervised regression machine learning (ML), is used to forecast antenna gain. The variance score, mean square error (MSE), root mean square error (RMSE), R square, mean squared logarithmic error (MSLE), mean absolute error (MAE), and so forth are used to gauge how well ML models perform. The accuracy of ridge regression gain prediction is approximately 98%, with errors of less than unity, which is better than the other ML models. The suggested THz-MIMO antenna system is appropriate for the wireless communication networks operating in the sixth generation.

In this paper, a new metamaterial absorber (MMA) is presented that exhibits resonances at 3.5 GHz and 13 GHz having peak absorption of 92.7