Design and Optimization of Microstrip Patch Antenna using Artificial Neural Networks

doi:10.35940/ijitee.i1097.0789s19

Cited by 12 publications

(5 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A neural network-based model for creating an ultra-wideband patch antenna with a microstrip was developed by Kaur et al [32]. The suggested design bandwidth grows as the ground area decreases.…”

Section: Literature Review -mentioning

confidence: 99%

An Organised and Focused Review of a Microstrip Patch Antenna for Its Deployment in Biomedical Applications

Bhowmick

2024

IJSREM

View full text Add to dashboard Cite

Reviewing microstrip antennas for diverse applications is the goal of this paper. The designing of microstrip patch antennae is a new study subject established for utilise in 5th generation communications applications. An antenna is a group of interconnected devices that work together to transmit and receive radio waves as a single antenna. Antennas come in many sizes and shapes. An antenna design that is low profile, lightweight, and results-oriented is the microstrip patch. In the future, microstrip patch antenna may be used for various 6G communication systems applications. Furthermore, 6G communication applications can be developed for additional devices, such as autonomous cars, machine learning, artificial neural network algorithms, radar, internet of things (IoT), biomedical, and vehicle-to-vehicle (V2V) communication. In the past, 4G wireless applications employed the multiple input, numerous output (MIMO) pattern as a standard geometry. This study covers several types of antennas, their geometric structures, different methods for analyzing their features, and their dimensions. The component of the substrate substances, loss tangent, the thickness, return loss, bandwidth, voltage-standing-wave ratio (VSWR), gain, and orientation from the earlier publications will also be covered. Keywords – microstrip, patch, antenna, IoT, biomedical, V2V, MIMO, VSWR

show abstract

Section: Literature Review -mentioning

confidence: 99%

An Organised and Focused Review of a Microstrip Patch Antenna for Its Deployment in Biomedical Applications

Bhowmick

2024

IJSREM

View full text Add to dashboard Cite

show abstract

“…Viswanadh [30], a microstrip antenna array is discussed in the paper referred to as for use in millimeter-wave applications in the frequency ranges of 24.25 GHz to 27.5 GHz and 26.5 GHz to 29.5 GHz. The end product is a 4-element antenna array that has dual-band 𝑆 [32], a Neural Network Model for designing an ultra-wideband microstrip patch antenna. Reduced ground size increases the proposed design bandwidth.…”

Section: Literature Reviewmentioning

confidence: 99%

Microstrip patch antennas for various applications: a review

Rana

Rana²,

Rahman³

2023

IJEECS

View full text Add to dashboard Cite

<span lang="EN-US">This paper aims to review microstrip antennas for various applications. The design of microstrip patch antennas is a new research field developed for use in 5th generation communication applications. An antenna is a collection of multiple devices connected together that function as a single antenna to send or receive radio waves. Antennas can be of different shapes and sizes. The microstrip patch is an antenna pattern that is light in weight, low profile, and focuses on producing results. In the future, microstrip patch antennas may be used for some 6G communication systems applications. In addition, 6G communication applications can be created on other devices, including biomedical, autonomous vehicles, vehicle-to-vehicle (V2V) communication, internet of things (IoT), machine learning, Artificial Neural Network Algorithms, radar, and wireless communication. In the past, the multiple input, multiple output (MIMO) pattern was a standard geometry used in 4G wireless applications. This paper discusses the geometric structures of antennas, various analysis methods for antenna characteristics, antenna dimensions, and many different types of antennas. Also, it will discuss the previous papers' substrate materials, loss tangent, thickness, return loss, bandwidth, voltage-standing-wave-ratio (VSWR), gain, and directivity.</span>

show abstract

“…In the initial step, data samples are categorized into training (approximately 70%), testing (15%), and validation (15%) sets. The percentage allocation may vary based on specific application requirements [18][19][20]. Subsequently, the network size is determined, specifying the number of hidden layers and neurons in each layer.…”

Section: Antenna Design Using Neural Network Modelmentioning

confidence: 99%

Design and Optimization of Sierpinski Carpet Fractal Antenna Using Artificial Neural Network (Ann) and High Frequency Structure Simulator (Hfss) Computational Techniques

Patil,

Vanjerkhede

2023

ecb

View full text Add to dashboard Cite

In the realm of modern wireless communication systems, the demand for compact, efficient, and multifunctional antennas has led to the exploration of novel design paradigms. In the field of wireless communication with constantly evolving antenna technology the need for antennas with enhanced bandwidth, gain and low profile is tremendously increasing. Fractal antennas have garnered significant attention due to their unique characteristics that lead to improved performance and miniaturization with broadband/multiband characteristic in modern wireless communication systems. This paper presents the design and optimization of a Sierpinski Carpet fractal antenna using advanced computational techniques. In this paper the design process which begins with the generation of the Sierpinski Carpet fractal structure by iteratively subdividing a square into smaller squares and removing specific portions following a predefined pattern. The novel approach is based on the Artificial Neural Network (ANN) and a High Frequency Structure Simulator (HFSS) as a computational tool in the designing of proposed antenna. These methods provide accurate simulations of the antenna radiation patterns, impedance characteristics, and resonant frequencies across multiple frequency bands. The optimization process aims to enhance parameters like bandwidth, gain, radiation efficiency, and impedance matching for the frequency band between 2 GHz and 8 GHz, thus providing multiband capabilities of Fractal antenna to be utilized for Wi-Fi & WiMAX systems..The findings of the design and optimization of the Sierpinski Carpet fractal antenna presented in this paper showcase the potential of combining intricate fractal geometries with computational techniques. In this work, Artificial Neural Networks prove to be the optimal choice for antenna design and optimization .This synergy leads to antennas with enhanced performance characteristics, making them valuable components in the ever-evolving field of wireless communication systems.

show abstract

Design and Optimization of Microstrip Patch Antenna using Artificial Neural Networks

Cited by 12 publications

References 8 publications

An Organised and Focused Review of a Microstrip Patch Antenna for Its Deployment in Biomedical Applications

An Organised and Focused Review of a Microstrip Patch Antenna for Its Deployment in Biomedical Applications

Microstrip patch antennas for various applications: a review

Design and Optimization of Sierpinski Carpet Fractal Antenna Using Artificial Neural Network (Ann) and High Frequency Structure Simulator (Hfss) Computational Techniques

Contact Info

Product

Resources

About