Experimental investigation of a dual mode antenna using characteristic mode analysis with enhanced directivity for GSM/5G applications

N, Sathishkumar; Palanisamy, Satheeshkumar; Khalaf, Osamah Ibrahim; Natarajan, Rajesh; Algburi, Sameer; Hamam, Habib

doi:10.1016/j.heliyon.2024.e32217

Heliyon

2024

DOI: 10.1016/j.heliyon.2024.e32217

|View full text |Cite

Experimental investigation of a dual mode antenna using characteristic mode analysis with enhanced directivity for GSM/5G applications

Sathishkumar N,

Satheeshkumar Palanisamy,

Osamah Ibrahim Khalaf

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article4

Relationship

Self Cite0

Independent4

Authors

Journals

Cited by 4 publications

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Hybrid CNN‐GNN Framework for Enhanced Optimization and Performance Analysis of Frequency‐Selective Surface Antennas

Palanisamy,

Karunanithi,

Periyasamy

et al. 2024

Int J Communication

View full text Add to dashboard Cite

Frequency‐selective surface (FSS) antennas are critical in modern communication systems, where optimizing their design for enhanced performance is essential. However, traditional methods often struggle with the complexity of FSS structures, leading to suboptimal designs. This paper addresses these limitations by proposing a novel CNN‐GNN hybrid network (CGHN) framework for FSS antenna optimization. The proposed methodology integrates convolutional neural networks (CNNs) for efficient feature extraction of spatial patterns within FSS designs and graph neural networks (GNNs) to model the relational dependencies between unit cells. This approach ensures that both local features and global interactions are captured, leading to more accurate and optimized antenna designs. The objective is to enhance the performance of FSS antennas by leveraging the complementary strengths of CNNs and GNNs, with an emphasis on improving design accuracy and efficiency. The novelty lies in the combination of CNN's localized pattern recognition with GNN's relational learning, which together enable a comprehensive understanding of the antenna's behavior. The proposed CGHN framework achieves a 96.78% accuracy rate in predicting optimal FSS designs, with a 23.84% boost in performance due to CNN‐driven feature extraction. Additionally, implementing stochastic gradient descent with gradient clipping increased the F1 score by 15%. Compared with existing techniques, the proposed method demonstrates significant improvements in both accuracy and efficiency, making it a superior choice for FSS antenna design optimization.

show abstract

Hybrid CNN‐GNN Framework for Enhanced Optimization and Performance Analysis of Frequency‐Selective Surface Antennas

Palanisamy,

Karunanithi,

Periyasamy

et al. 2024

Int J Communication

View full text Add to dashboard Cite

show abstract

Modeling of Inscribed Dual Band Circular Fractal Antenna for Wi‐Fi Application Using Descartes Circle Theorem

Palanisamy,

Vaddinuri,

Khan

et al. 2024

Engineering Reports

View full text Add to dashboard Cite

This study focuses on the modeling of a dual‐band circular fractal antenna designed for Wi‐Fi applications by utilizing the Descartes Circle Theorem. The antenna's geometry is characterized by self‐similar fractal patterns, enabling enhanced performance in dual frequency bands relevant to Wi‐Fi communication. Current research is trending towards the development of antennas capable of operating across various Wi‐Fi bands, and the emerging 6 GHz band. In this article, there is also a focus on achieving ultra‐wideband functionality to cater to the requirements of future wireless technologies. Incorporation with Circuits and Systems: Ongoing efforts are directed at seamlessly integrating these antennas with RF circuits and communication systems to enhance their practical utility and applicability. The exploration of unconventional fractal shapes and the utilization of advanced optimization algorithms present promising avenues for enhancing antenna performance and achieving miniaturization. This research contributes to the advancement of compact and efficient antenna designs for wireless communication systems. Detailed considerations are given to the 2.4 and 5.55 GHz bands to ensure compatibility with standard Wi‐Fi protocols. The designed circular fractal antenna is compared with the conventional circular patch antenna and the results were analyzed. At the resonating frequency of 2.4 and 5.55 GHz, circular patch antenna has a reflection coefficient (S11) of −18.1 and −13.51, respectively with a peak gain of 3.6 dBi, whereas, the designed circular fractal antenna shows an improved reflection coefficient, S11 of −22.0 and −15.5 dB at the same resonating frequency with a peak gain of 11.7920 dBi. The radiation pattern shows that the antenna radiated in unidirectional pattern with the front‐to‐back ratio of 101.4 which is higher than circular patch antenna. The miniaturized antenna is fabricated through photo etching process, tested, and validated.

show abstract

Machine learning-based detection of DDoS attacks on IoT devices in multi-energy systems

Sakr,

Fouda,

Ashour

et al. 2024

Egyptian Informatics Journal

View full text Add to dashboard Cite

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Experimental investigation of a dual mode antenna using characteristic mode analysis with enhanced directivity for GSM/5G applications

Cited by 4 publications

References 31 publications

Hybrid CNN‐GNN Framework for Enhanced Optimization and Performance Analysis of Frequency‐Selective Surface Antennas

Hybrid CNN‐GNN Framework for Enhanced Optimization and Performance Analysis of Frequency‐Selective Surface Antennas

Modeling of Inscribed Dual Band Circular Fractal Antenna for Wi‐Fi Application Using Descartes Circle Theorem

Machine learning-based detection of DDoS attacks on IoT devices in multi-energy systems

Contact Info

Product

Resources

About