A Novel Miniaturized Hexagonal-Shaped Patch Antenna for Microwave 5G Communications

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Rashika K
Thirisha S
Uthayakumar G.S

Abstract

The creation of a hexagon-shaped patch antenna for Sub-6GHz 5G communications is presented in this study. For 5G wireless applications, the suggested antenna can resonate at the center frequency of 6 GHz. The proposed antenna features a hexagonal design, multiple radiating slots with partial ground and is fed with a microstrip feedline. It measures 17.5 × 22.2 × 1.6 mm3 and operates on the N102 band at 6 GHz. Return loss, VSWR, peak gain, and impedance bandwidth are all elements of the performance of the proposed antenna. The proposed antenna employs slots that cover the frequency range of 5.92 GHz to 6.35 GHz. At a resonant frequency of 6.1 GHz, the suggested antenna's reflection coefficient (S11) is 44.6 dB, with a peak gain of roughly 3.2 dB. Thus, the suggested antenna can be used for 5G wireless applications operating at 6 GHz

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[1]
Rashika K, Thirisha S, and Uthayakumar G.S , Trans., “A Novel Miniaturized Hexagonal-Shaped Patch Antenna for Microwave 5G Communications”, IJIES, vol. 12, no. 2, pp. 1–4, Feb. 2025, doi: 10.35940/ijies.B1088.12020225.
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References

Patchin, Justin & Hinduja, Sameer. (2006). Bullies Move Beyond the Schoolyard A Preliminary Look at Cyberbullying. Youth Violence and Juvenile Justice. 4. 148-169. DOI: https://doi.org/10.1177/1541204006286288

Rosa, Hugo & Salgado Pereira, Nádia & Ribeiro, Ricardo & Ferreira, Paula & Carvalho, Joao & Oliveira, Sofia & Coheur, Luisa & Paulino, Paula & Veiga Simão, Ana Margarida & Trancoso, Isabel. (2019). Automatic cyberbullying detection: A systematic review. Computers in Human Behavior. 93. 333-345. DOI: https://doi.org/10.1016/j.chb.2018.12.021

K. S. Alam, S. Bhowmik and P. R. K. Prosun, "Cyberbullying Detection: An Ensemble Based Machine Learning Approach," 2021 Third International Conference on Intelligent Communication Technologies and Virtual Mobile Networks (ICICV), Tirunelveli, India, 2021, pp. 710-715, Doi: https://doi.org/10.1109/ICICV50876.2021.9388499

Abdullah, Alqahtani., Mohammad, Ilyas. (2024). A Machine Learning Ensemble Model for the Detection of Cyberbullying. DOI: 10.48550/arxiv.2402.12538 https://doi.org/10.5121/ijaia.2024.15108

Pankaj, Shah., Shivali, Chopra. (2024). Mixed Language Text Classification Using Machine Learning: Cyberbullying Detection System. 514-518. DOI: https://doi.org/10.1201/9781003405580-83

Jinan, Redha, Mutar. (2024). Cyberbullying Messages Detection Using Machine Learning and Deep Learning. International journal of advances in scientific research and engineering, 10(03):19-29. DOI: https://doi.org/10.31695/IJASRE.2024.3.3

K. S. Raj, K. Tej, N. K. S, S. K. T and S. Vajipayajula, "Ensemble Techniques for Malicious Threat Detection," 2024 International Conference on Inventive Computation Technologies (ICICT), Lalitpur, Nepal, 2024, pp. 1543-1545, DOI: https://doi.org/10.1109/ICICT60155.2024.10544694

Prasad, K. L., Anusha, P., Rao, M., & Rao, Dr. K. V. (2019). A Machine Learning based Preventing the Occurrence of Cyber Bullying Messages on OSN. In International Journal of Recent Technology and Engineering (IJRTE) (Vol. 8, Issue 3, pp. 1861–1865). DOI: https://doi.org/10.35940/ijrte.a9164.078219

Jalda, C.S., Polimetla, U.B., Nanda, A.K., Nanda, S. (2024). A Comparison Study of Cyberbullying Detection Using Various Machine Learning Algorithms. In: Sathees kumaran, S., Zhang, Y., Balas, V.E., Hong, Tp., Pelusi, D. (eds) Intelligent Computing for Sustainable Development. ICICSD 2023. Communications in Computer and Information Science, vol 2122. Springer, Cham. DOI: https://doi.org/10.1007/978-3-031-61298-5_4

Bhagyashree, Kadam. (2023). Cyberbullying Detection using Machine Learning Algorithms. International Journal For Science Technology And Engineering, 11(5):1326-1328. DOI: https://doi.org/10.22214/ijraset.2023.51749

Muneer A, Alwadain A, Ragab MG, Alqushaibi A. Cyberbullying Detection on Social Media Using Stacking Ensemble Learning and Enhanced BERT. Information. 2023; 14(8):467. DOI: https://doi.org/10.3390/info14080467

Ali, A., & Syed, A. M. (2022). Cyberbullying Detection using Machine Learning. Pakistan Journal of Engineering and Technology, 3(2), 45–50. DOI: https://doi.org/10.51846/vol3iss2pp45-50

Patil, P., Raul, S., Raut, D., & Nagarhalli, T. (2023). Hate Speech Detection using Deep Learning and Text Analysis. 2023 7th International Conference on Intelligent Computing and Control Systems (ICICCS), 322–330. DOI: https://doi.org/10.1109/iciccs56967.2023.10142895

Hondor, Saragih., Jonson, Manurung. (2024). 1. Leveraging the BERT Model for Enhanced Sentiment Analysis in Multicontextual Social Media Content. Jurnal Manajemen Informatika C.I.T. Medicom, DOI: https://doi.org/10.35335/cit.Vol16.2024.766.pp82-89

Amisha, Sharma., Diya, Khajuria., Ayushi., Ritu, Rani., Garima, Jaiswal., Mala, Saraswat. (2023). LSTM-Based Model for Classification of Tweets. 1-7. DOI: https://doi.org/10.1109/ASIANCON58793.2023.10270665

Yamaguchi, A., Margatina, K., Chrysostomou, G., & Αλέτρας, Ν. (2021). Frustratingly Simple Pretraining Alternatives to Masked Language Modeling. cornell university. DOI: https://doi.org/10.48550/arxiv.2109.01819

Sun, Y., Hao, C., Zheng, Y., & Qiu, H. (2021). NSP-BERT: A Prompt-based Few-Shot Learner Through an Original Pre-training Task--Next Sentence Prediction. cornell university. DOI: https://doi.org/10.48550/arxiv.2109.03564

Devlin, J., Chang, M., Lee, K., & Toutanova, K. (2018). BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. arXiv (Cornell University). DOI: https://doi.org/10.48550/arxiv.1810.04805

Hochreiter, S., & Schmidhuber, J. (1997). Long Short-Term Memory. Neural Computation, 9(8), 1735–1780. DOI: https://doi.org/10.1162/neco.1997.9.8.1735

Witten, I. H., Frank, E., Hall, M. A., & Pal, C. J. (2017). Ensemble learning. In Elsevier eBooks (pp. 479–501). DOI: https://doi.org/10.1016/b978-0-12-804291-5.00012-x

Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, L., & Polosukhin, I. (2017b, June 12). Attention Is All You Need. arXiv.org. https://arxiv.org/abs/1706.03762

Hoque, M. N., & Seddiqui, M. H. (2024). Detecting cyberbullying text using the approaches with machine learning models for the low-resource Bengali language. IAES International Journal of Artificial Intelligence, 13(1), 358. DOI: https://doi.org/10.11591/ijai.v13.i1.pp358-367

Chen, S., He, K., & Wang, J. (2024). Chinese Cyberbullying Detection Using XLNet and Deep Bi-LSTM Hybrid Model. Information, 15(2), 93. DOI: https://doi.org/10.3390/info15020093

Shibly, F. H. A., Sharma, U., & Naleer, H. M. M. (2022). Performance Comparison of Machine Learning and Deep Learning Algorithms in Detecting Online Hate Speech (pp. 695–706). Springer Nature Singapore. DOI:

https://doi.org/10.1007/978-981-19-2821-5_59

Farasalsabila, F., Utami, E., & Hanafi, H. (2024). Deteksi Cyberbullying Menggunakan BERT dan Bi-LSTM. Jurnal Teknologi, 17(1). DOI: https://doi.org/10.34151/jurtek.v17i1.4636

Sunitharam, Dr. C., Nandini, P. S., & K, R. (2023). Detection of Cyber-Bullying Through Sentimental Analysis. In International Journal of Soft Computing and Engineering (Vol. 13, Issue 1, pp. 16–20). DOI: https://doi.org/10.35940/ijsce.a3594.0313123

Angelis, J. D., & Perasso, G. (2020). Cyberbullying Detection Through Machine Learning: Can Technology Help to Prevent Internet Bullying? In International Journal of Management and Humanities (Vol. 4, Issue 11, pp. 57–69). DOI: https://doi.org/10.35940/ijmh.k1056.0741120

Sharma, P. (2023). Advancements in OCR: A Deep Learning Algorithm for Enhanced Text Recognition. In International Journal of Inventive Engineering and Sciences (Vol. 10, Issue 8, pp. 1–7). DOI: https://doi.org/10.35940/ijies.f4263.0810823

Prashar, S., & Bhakar, S. (2019). Real

Time Cyberbullying Detection. In International Journal of Engineering and Advanced Technology (Vol. 9, Issue 2, pp. 5197–5201). DOI: https://doi.org/10.35940/ijeat.b4253.129219

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