Antenna Design Research Articles

A compact multiband flexible antenna with a full ground plane for off body communication

Abstract A compact, multiband flexible antenna for off Body Communication (OBC) at 2.45 GHz and UWB low and high bands are presented as required by the IEEE 802.15.6TM standard, 2012. The antenna exhibits a directional radiation pattern and provides good gain and a low specific absorption rate (SAR). The proposed antenna has a compact footprint of 44 × 32 ×1.5 mm3. The proposed antenna is fabricated by placing a conductive fabric on a 1.5 mm thick polydimethylsiloxane (PDMS) polymer to enhance high flexibility and durability. A full ground made of conductive textile is used on the underside of the dielectric to reduce the load directed towards the antenna caused by the layers of human tissue underneath and to minimize back radiation from the human body. The proposed antenna design combines square and circular rings to achieve multi-band characteristics. Edge chamfering, slotting, and stub addition bandwidth expansion techniques are used to achieve wide bandwidth. The proposed antenna demonstrates exceptional resistance to the human body's load and physical deformation. The proposed antenna is a compact single-layer substrate flexible FGP (FGP) antenna operable in the WLAN (2.45 GHz), lower (3.2-4.6 GHz), and higher UWB (6.2-11 GHz) bands specified by IEEE. 802.15.6.

A novel elliptical MIMO antenna design for enhanced wireless connectivity in greenhouse applications

This paper presents a novel design and development of an elliptical antenna tailored for Greenhouse applications, providing support for multiple wireless services. The proposed antenna configuration is a quad-port multiple input multiple output (MIMO) system consisting of four identical elliptical antenna elements arranged in an orthogonal configuration on a Polycarbonate substrates. It operates effectively across the 2.4 GHz band and the 3–14.8 GHz band, enabling seamless connectivity for a range of Greenhouse and wireless applications, including Bluetooth, Wi-Fi, intelligent control systems (ICS), Greenhouse-to-infrastructure (G2I) communication, sensor networks (SN), and Greenhouse-to-network (G2N) connections. Rigorous analysis of antenna diversity performance is conducted, focusing on key parameters such as the envelope correlation coefficient (ECC), diversity gain (DG), total active reflection coefficient (TARC), and channel capacity loss (CCL). The antenna demonstrates exceptional performance, with an ECC of less than 0.005, DG exceeding 10 dB, TARC below − 25 dB, and CCL less than 0.25 bits/s/Hz. Detailed parametric analysis confirms the suitability of this design for 5G Greenhouse applications.

Neurospectral Computation for the Resonant Characteristics of an Equilateral Triangular Patch Antenna on Suspended Substrates

Modeling and design of an equilateral triangular patch antenna on suspended and single substrate are accomplished in this paper. The spectral domain approach is important due to its accuracy, but has a high computational cost. On the other hand, the Artificial Neural Networks (ANNs) have recently become a fast and flexible vehicle for modeling and designing microwave antennas. This paper introduces electromagnetic knowledge combined with ANNs to compute the resonant frequency of the fundamental and higher order modes and to eliminate the difficulties of handling the singularity points encountered in the numerical evaluation of integrals. The resonant frequency results obtained from the neural model are in very good agreement with the experimental and theoretical results available in the literature.

Machine learning-driven design and performance analysis of microstrip antennas for sub-6 GHz/mm Wave 5G networks

In the realm of modern communication systems, antennas are crucial components, with the microstrip patch antenna being particularly notable for its low profile and seamless integration. Despite its widespread use, designing this antenna involves complex simulations to optimize parameters, requiring significant expertise and consuming considerable time and energy. To streamline this process, machine learning (ML) algorithms are being utilized. This paper introduces an innovative approach that employs ML techniques to design a rectangular microstrip patch antenna operating within the sub-6 GHz frequency range (1-6 GHz) and the millimeter frequency range (28-40 GHz). The antenna design maintains consistent patch dimensions positioned strategically at the center, with a thorough examination of patch length and width to enhance performance. Datasets are meticulously prepared, covering output parameters such as beam area, directivity, gain, and radiation efficiency across the specified frequency ranges. By employing various ML algorithms, this study conducts a comprehensive analysis to identify the most effective algorithm for accurately predicting antenna characteristics. The K-nearest neighbor (KNN) algorithm achieved high accuracy across all parameters: gain at 94.23% under sub-6 GHz and 95.93% under millimeter frequency range, directivity at 99.02% and 98.59%, radiation efficiency at 93.94% and 94.28%, and beam area at 99.07% and 98.59% respectively. These results optimize microstrip antenna designs and enhance understanding of the relationship between design parameters and performance outcomes with ML.

Design and enhancement of microstrip patch antenna with frequency selective surface backing for vehicle-to-vehicle communication

Design and enhancement of microstrip patch antenna with frequency selective surface backing for vehicle-to-vehicle communication

Design and analysis of a fabricated modified elliptical patch antenna with slots and partial ground plane techniques for UWB applications

This study presents a novel elliptical microstrip antenna (EMSA) design method for enhanced bandwidth. The proposed EMSA offers versatile polarization control, generating both linear and circular polarization. Wider impedance bandwidths compared to some other patch antennas make it suitable for broadband communication. Its compact size facilitates integration into space-constrained devices. Additionally, it provides polarization diversity for MIMO systems, reducing signal fading. The fabricated EMSA, operating at 7.05 GHz, achieves a simulated bandwidth of 5.7% and a measured bandwidth of 4.28%. It exhibits a return loss of -42 dB, 50 Ω impedance matching, 8.57 dB radiation gain, and a VSWR of 1.016. Two bandwidth enhancement techniques were investigated: reducing the ground plane size and incorporating slots within the patch. The partial ground plane achieved simulated and measured bandwidth improvements of 146% and 167%, respectively. The slotted patch yielded 160% and 180% improvements, respectively.

Machine Learning Based on Patch Antenna Design and Optimization for 5G Applications at 28GHz

Machine Learning Based on Patch Antenna Design and Optimization for 5G Applications at 28GHz

A Compact X and Ku Band Quad Port MIMO Antenna with Path Loss aModel for Urban Macro and Micro Environments

The prospective of multiple-input multiple-output (MIMO) technology to increase network reliability and enhanced data throughput has made it essential in modern wireless communication systems. In this study, a new X and Ku band MIMO antenna with improved isolation is designed and analyzed using a shared radiator. To improve system performance, the MIMO antenna system was built to provide greater isolation between antenna elements by inserting inverted H-shape parasitic components within the radiators, resulting in an out-of-phase current of a comparable magnitude to the coupling current. The antenna achieves an isolation level greater than 15 dB across the operational frequency of 8.5-18.5 GHz with overall dimensions of 25 × 22 × 0.5 mm3 on RT duroid 5880 substrate. Furthermore, the developed MIMO antenna is investigated for radiation characteristics, with a maximum gain of 5.8 dB and acceptable diversity features. A path loss study for the designed antenna is performed using the ABG and CI models under the urban macro and micro model scenarios. The proposed shared radiator quad port MIMO antenna is optimized to realize compactness, wider impedance bandwidth, and inter-port isolation. The antenna design outcomes from simulation and experimental data make it a good contender for use in contemporary communication systems.

Exploring the Opportunities of Applying RFID Technology in Smart Agriculture

This paper explores the opportunities of applying RFID (radio-frequency identification) technology in smart agriculture. With the projected increase in global population and the resulting higher demand for food production, the agricultural industry is under pressure to find more efficient and sustainable ways to meet these needs. Radio-frequency identification (RFID) technology has been recently adopted in the agriculture industry as a means of improving efficiency and productivity towards achieving smart agriculture. RFID technology is revolutionizing smart agriculture, offering automation, real-time monitoring and data-driven decision-making. Integrating RFID tags with plants and soil samples optimizes resource utilization, crop health management, traceability and quality assurance. RFID in smart agriculture offers opportunities for resource optimization, crop health management, traceability and automation. Leveraging RFID technology, farmers can elevate productivity, reduce costs, improve sustainability and meet global demands. Adopting RFID in agriculture revolutionizes traditional practices, enabling efficient and sustainable farming. RFID-enabled traceability enhances food safety, quality assurance and transparency in the food supply chain. The objective of this paper is to explore the potential of RFID technology in smart agriculture and highlight the significance of effective RFID antenna design for optimizing food production, addressing global challenges and fostering a more efficient, sustainable and resilient agricultural sector.

Versatile unsupervised design of antennas using flexible parameterization and computational intelligence methods

Developing contemporary antennas is a challenging endeavor that requires considerable engineering insight. The most laborious stage is to devise an antenna architecture that delivers the required functionalities, e.g., multiband operation. Iterative by nature (hands-on topology modifications, parametric studies, trial-and-error geometry selection), it typically takes many weeks and requires considerable engagement from a human expert. Consequently, only a few possible design options concerning the fundamental antenna geometry may be considered. Automated topology rendition and geometry parameter optimization are highly relevant, especially from the industrial perspective. Therein, reducing time-to-market and limiting the involvement of trained experts is critical. This research proposes an innovative procedure for unsupervised development of planar antennas. Our method leverages flexible antenna parameterization based on re-sizable elliptical patches. It permits the realization of a massive number of geometries of diverse shapes and complexities using a small number of decision variables. Computational intelligence methods are employed to conduct antenna evolution exclusively based on specifications and possible constraints (e.g., maximum size). Fine-tuning of the structure geometry is achieved through low-cost local search routines. Our methodology is demonstrated by designing several antennas featuring distinct characteristics (broadband, single-, dual- and triple-band). The obtained results, supported by experimental data, underscore the presented approach’s versatility and capability to render unconventional topologies at reasonably low computational expenses. As mentioned earlier, the design process is fully automated without human expert involvement.

Retraction Note: Analytical design of wideband dielectric polygonal directional beam antennas

Retraction Note: Analytical design of wideband dielectric polygonal directional beam antennas

Design and optimization of flexible DGS-based microstrip antenna for wearable devices in the Sub-6 GHz range using the nelder-mead simplex algorithm

This study introduces a Nelder-Mead Simplex Algorithm based low-profile, flexible, and wearable defected ground structure (DGS)-loaded deformed microstrip antenna for Sub-6 GHz 5 G applications. It is fabricated on a low-loss 20 mil Rogers RT/Duroid 5880 substrate and the antenna demonstrates robust performance with reflection coefficient magnitude (|S11|) of –22.34 dB with peak gain of about 5.57 dBi at resonant frequency (fr) of 2.185 GHz. Comprehensive key performance metrics such as |S11|, far-field gain patterns, and specific absorption rate (SAR) of the proposed antenna is demonstrated. The SAR for 1 g and 10 g tissues at various separation distances are analyzed and presented by utilizing human multilayer phantom model with antenna. Additionally, the lowest SAR is measured to be 0.0959 W/kg for 1 g of tissue and 0.0755 W/kg for 10 g of tissue when the antenna is placed 0.291λ0 away from the model. The study also explores the proposed antenna performance under various bending conditions for the conformability analysis and in different on-body scenarios, with placement on the hand, leg, and chest. The measured |S11| values, particularly strong on the chest, underscore the antenna effectiveness for wearable technology.

Global miniaturization of broadband antennas by prescreening and machine learning

The development of contemporary electronic components, particularly antennas, places significant emphasis on miniaturization. This trend is driven by the emergence of technologies such as mobile communications, the internet of things, radio-frequency identification, and implantable devices. The need for small size is accompanied by heightened demands on electrical and field properties, posing a considerable challenge for antenna design. Shrinking physical dimensions can compromise performance, making miniaturization-oriented parametric optimization a complex and heavily constrained task. Additionally, the task is multimodal due to typical parameter redundancy resulting from various topological modifications in compact antennas. Identifying truly minimum-size designs requires a global search approach, as the popular nature-inspired algorithms face challenges related to computational efficiency and the need for reliable full-wave electromagnetic (EM) simulation to evaluate device’s characteristics. This study introduces an innovative machine learning procedure for cost-effective global optimization-based miniaturization of antennas. Our technique includes parameter space pre-screening and the iterative refinement of kriging surrogate models using the predicted merit function minimization as an infill criterion. Concurrently, the design task incorporates design constraints implicitly by means of penalty functions. The combination of these mechanisms demonstrates superiority over conventional techniques, including gradient search and electromagnetic-driven nature-inspired optimization. Numerical experiments conducted on four broadband antennas indicate that the proposed framework consistently yields competitive miniaturization rates across multiple algorithm runs at low costs, compared to the benchmark.

Machine learning‐driven design of dual‐band antennas using PGGAN and enhanced feature mapping

AbstractThis paper presents a systematic antenna design methodology that integrates machine learning, leveraging the progressive growth technique of Progressive Growing of GANs (PGGAN) to generate images of various dual‐band PIFA‐like antenna structures. The process involves using data augmentation methods to generate 4180 antenna samples. In the latent space, the authors employ Latin Hypercube Sampling to maintain diversity and combine it with the Hough Transform to enhance the edge features of the antennas while providing labelling functionality. This labelling method strengthens the relationship between antenna frequency and wavelength characteristics. The paper clearly outlines the design process, starting from the simulation of two types of single‐frequency PIFA‐like antennas (2.45 and 5.2 GHz, respectively) to the completion of PGGAN's generation task, resulting in a novel dual‐band Wi‐Fi PIFA‐like antenna structure. The measurement results of the dual‐band antennas exhibit excellent consistency with the simulation results.

Miniaturized Arrow-Shaped Flexible Filter-Embedded Antenna for Industrial and Medical Applications

This paper presents the design and characterization of a coplanar waveguide (CPW) fed, low-profile, and flexible arrow-shaped filtenna for ISM band applications at 2.45 GHz. The antenna design involves an innovative approach incorporating etching slots to achieve miniaturization by 34%, contrasting with a traditional quadrilateral-shaped antenna. After the attainment of desired miniaturization, the unwanted harmonics are also mitigated by deploying simple filtering methodology. A perpendicular rectangular stub is strategically introduced to the feedline, effectively minimizing harmonics across a broad frequency range of 3.3–11.0 GHz. Through simulations and measurements, the results indicate that the antenna’s operational band spans from 2.276 to 2.75 GHz, encompassing the entire ISM band (2.4–2.5 GHz). Notably, the antenna demonstrates promising radiation characteristics, including omnidirectional gain of approximately 2.2 dBi and a radiation efficiency exceeding 95%. With a compact overall size of 0.24λ × 0.20λ × 0.0005λ (where λ is the free-space wavelength at 2.45 GHz), coupled with wide harmonic rejection property, the proposed arrow-shaped flitenna emerges as a compelling candidate for ISM band applications.

Advanced design and analysis of dual element MIMO antenna for Ultra-Wideband Applications

This investigation uses the Genetic Optimization Method to convert a wide-band MIMO antenna into a UWB (3.1GHz–10.6 GHz) MIMO antenna. Initially, a 22 × 42, mm2 wideband 2X2 MIMO antenna was designed using commercial Flame Retardant-4 material. The structure of the antenna patch was designed using half-circular forms on the half-ground plane. The designed MIMO antenna operates throughout a large frequency range of 4.8–9.8 GHz. While it was successful in achieving broad band characteristics, this MIMO antenna was unable to reach ultra-wide band characteristics. The MIMO antenna was operated in UWB ranges by a parametric study, which indicated that the resonating characteristics can be significantly modified by inserting a rectangular slot into the ground plane. Throughout the operational range, it was important to be concerned about improved gain and good isolation. Accordingly, optimization was carried out in order to accomplish the essential, multi-objective goals. The difficult multi-objective design goal is now reduced to an optimization challenge by means of genetic algorithm based random search. One of the performance goals that this optimization strategy aimed to fulfil was an increase in isolation to –20 dB across the entire Ultra-Wideband, with S11 being below –10 dB from 3.1 to 10.6 GHz. It is recommended to randomly select the parameters from their respective ranges for this work. This led to the selection of an optimizer based on random searches. In the operating range, the UWB has a respectable gain of 4 dB to 6 dB and increased isolation to –20 dB, according to the genetic algorithm optimizer’s execution of the predefined multiple-objective task.

Design of 5G Millimeter-wave Filtering Antenna with Γ-shaped Slot Radiators Coupled to Substrate Integrated Waveguide Cavity

Design of 5G Millimeter-wave Filtering Antenna with Γ-shaped Slot Radiators Coupled to Substrate Integrated Waveguide Cavity

Wideband star-shaped antenna based on artificial magnetic conductor surface for unidirectional radiation

Gathering the advantages of low profile, high gain, high efficiency, and wideband operation in a planar antenna is a challenging objective for the antenna designer. Low profile wideband antennas are usually characterized by low gain. An antenna of wideband impedance matching usually suffers continuous variations of the gain over such a wideband due to the variation of the radiation mechanisms and surface current distributions over the frequency band of impedance matching. Therefore, the motivation of the present work is to provide both impedance matching and stabilized high gain by the aid of wideband artificial magnetic conductor (AMC) with a design of the unit cell that is suitable to the antenna structure and the desired frequency band. The present work, proposes the utilization of low-size wideband AMS surface (AMCS) to be placed behind a wideband omnidirectional antenna to enhance the gain over the frequency band of operation. In this way, the radiating structure combines high gain and wideband operation in the same design. A wideband planar monopole printed antenna is designed to operate as omnidirectional antenna with perfect impedance matching and radiation efficiency over the frequency band 3.6-7.2GHz when placed in free space. The gain of the free-standing antenna varies from 2dBi to 4.5dBi over the frequency band. A wideband AMCS is designed to enhance the antenna gain over frequency band of operation. The designed AMCS is composed of only 3×3 unit cells and overall dimensions of 10×10cm. This surface is placed parallel to the planar antenna at a distance 1.7cm behind it. The enhanced gain of the radiating structure of the AMCS-backed antenna reaches 8.5dBi without affecting the bandwidth over which the input impedance is matched to the feeding line. The radiation efficiency of the AMCS-backed antenna is maintained above 98% over the frequency band of operation (3.7-7.2GHz). The wideband antenna and the AMCS are fabricated for practical evaluation of the overall AMCS-backed antenna performance including the measurements of impedance matching, gain and radiation efficiency. The measurements and simulation results are in good consent.

Low SAR ultra compact UWB vivaldi non-uniform slot antennas for breast cancer detection

Abstract Breast cancer is one of the growing issues among women. Current ultrawideband (UWB) antennas utilized for Microwave Imaging (MI) present several limitations, such as resolution and penetration trade-offs, large dimensions of the antennas degrade patient comfort, and clutter in the received signal. To tackle these restrictions, this study presents the design, fabrication, and testing of ultra-compact Vivaldi antennas based on the new Vivaldi non-uniform slot profile antenna (VNSPA) theory. These antennas, with their significant slot length reductions of 50 % and 60 %, and circuit area reductions of 72.74 % (Antenna A) and 81.8 % (Antenna B), hold great promise for modern wireless communication and medical fields. Antenna A and B provide matching S11 values of less than −11.36 dB and −10.21 dB and peak gains of 5.9 dBi and 6 dBi through 2.63–12.33 GHz and 3.16–14.34 GHz, respectively. Although Antenna B is 30.58 % smaller than Antenna A, it provides 13.24 % bandwidth (BW) with a 1.7 % gain enhancement, highlighting the significance of the exponential nonuniform slot profile (ENSP) shape on the antenna’s performance. Antenna B provides good Breast Cancer Detection (BCD) results through UWB MI. The simulation in this work, which is performed using computer simulation technology (CST) software, agrees well with the practical results to prove the antenna’s capabilities in detecting tumors in a breast. These results, like the directive stable radiation patterns and low specific absorption rate (SAR) values, ensure the proposed antennas are good candidates for modern wireless communication applications such as reader antennas in body area networks and high-resolution medical applications such as BCD.

A detailed review of 5G MIMO and array antenna design evolution with performance enhancement for mmWave applications

A detailed review of 5G MIMO and array antenna design evolution with performance enhancement for mmWave applications