Return Loss Optimization in Rectangular Microstrip Patch Antennas Using Response Surface Methodology (RSM) for 5G Applications Article Swipe
Thanh Tran
,
Vinh Dang
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.4108/eetinis.v12i3.8948
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.4108/eetinis.v12i3.8948
In recent decades, wireless communication has advanced significantly. People increasingly rely on the Internet of Things, cloud computing, and big data analytics. These services require higher data rates, faster transmission and reception times, greater coverage, and increased throughput. 5G technology supports all of these features. Antennas, essential components of modern wireless devices, must be designed to meet the growing demand for fast and intelligent products. This study aims to optimize the dimensions and characteristics of a rectangular patch antenna. To examine the impact of independent variables (such as patch length, patch width, inset slot length, and inset slot width) on the response variables (return loss and resonant frequency), Response Surface Methodology (RSM) combined with Central Composite Design (CCD) was applied. The findings of the RSM analysis indicated that the experimental data were best represented by a quadratic polynomial model, with regression coefficients exceeding 0.970 for all responses. The optimized parameters identified are as follows: a patch length of 4.7 mm, a patch width of 4.7 mm, an inset slot length of 0.8 mm, and an inset slot width of 1.0 mm. The antenna designed using these optimized parameters achieved a target return loss of -45.865 dB at a frequency of 28.122 GHz. Finally, the results were validated using CST Studio Suite, which demonstrated good agreement with the experimental data.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.4108/eetinis.v12i3.8948
- https://publications.eai.eu/index.php/inis/article/download/8948/3612
- OA Status
- diamond
- References
- 30
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4411245596
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4411245596Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.4108/eetinis.v12i3.8948Digital Object Identifier
- Title
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Return Loss Optimization in Rectangular Microstrip Patch Antennas Using Response Surface Methodology (RSM) for 5G ApplicationsWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2025Year of publication
- Publication date
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2025-06-12Full publication date if available
- Authors
-
Thanh Tran, Vinh DangList of authors in order
- Landing page
-
https://doi.org/10.4108/eetinis.v12i3.8948Publisher landing page
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https://publications.eai.eu/index.php/inis/article/download/8948/3612Direct link to full text PDF
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YesWhether a free full text is available
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-
diamondOpen access status per OpenAlex
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https://publications.eai.eu/index.php/inis/article/download/8948/3612Direct OA link when available
- Concepts
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Microstrip antenna, Return loss, Response surface methodology, Materials science, Patch antenna, Microstrip, Electronic engineering, Acoustics, Computer science, Physics, Antenna (radio), Engineering, Telecommunications, Machine learningTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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30Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.using | 184, 207 |
| abstract_inverted_index.which | 211 |
| abstract_inverted_index.width | 162, 177 |
| abstract_inverted_index.28.122 | 200 |
| abstract_inverted_index.Design | 116 |
| abstract_inverted_index.People | 8 |
| abstract_inverted_index.Studio | 209 |
| abstract_inverted_index.Suite, | 210 |
| abstract_inverted_index.demand | 59 |
| abstract_inverted_index.faster | 28 |
| abstract_inverted_index.higher | 25 |
| abstract_inverted_index.impact | 82 |
| abstract_inverted_index.length | 156, 169 |
| abstract_inverted_index.model, | 138 |
| abstract_inverted_index.modern | 49 |
| abstract_inverted_index.rates, | 27 |
| abstract_inverted_index.recent | 1 |
| abstract_inverted_index.return | 191 |
| abstract_inverted_index.target | 190 |
| abstract_inverted_index.times, | 32 |
| abstract_inverted_index.width) | 98 |
| abstract_inverted_index.width, | 91 |
| abstract_inverted_index.(return | 103 |
| abstract_inverted_index.-45.865 | 194 |
| abstract_inverted_index.Central | 114 |
| abstract_inverted_index.Surface | 109 |
| abstract_inverted_index.Things, | 15 |
| abstract_inverted_index.antenna | 182 |
| abstract_inverted_index.examine | 80 |
| abstract_inverted_index.greater | 33 |
| abstract_inverted_index.growing | 58 |
| abstract_inverted_index.length, | 89, 94 |
| abstract_inverted_index.require | 24 |
| abstract_inverted_index.results | 204 |
| abstract_inverted_index.Finally, | 202 |
| abstract_inverted_index.Internet | 13 |
| abstract_inverted_index.Response | 108 |
| abstract_inverted_index.achieved | 188 |
| abstract_inverted_index.advanced | 6 |
| abstract_inverted_index.analysis | 125 |
| abstract_inverted_index.antenna. | 78 |
| abstract_inverted_index.applied. | 119 |
| abstract_inverted_index.combined | 112 |
| abstract_inverted_index.decades, | 2 |
| abstract_inverted_index.designed | 54, 183 |
| abstract_inverted_index.devices, | 51 |
| abstract_inverted_index.findings | 121 |
| abstract_inverted_index.follows: | 153 |
| abstract_inverted_index.optimize | 69 |
| abstract_inverted_index.resonant | 106 |
| abstract_inverted_index.response | 101 |
| abstract_inverted_index.services | 23 |
| abstract_inverted_index.supports | 40 |
| abstract_inverted_index.wireless | 3, 50 |
| abstract_inverted_index.Antennas, | 45 |
| abstract_inverted_index.Composite | 115 |
| abstract_inverted_index.agreement | 214 |
| abstract_inverted_index.coverage, | 34 |
| abstract_inverted_index.essential | 46 |
| abstract_inverted_index.exceeding | 142 |
| abstract_inverted_index.features. | 44 |
| abstract_inverted_index.frequency | 198 |
| abstract_inverted_index.increased | 36 |
| abstract_inverted_index.indicated | 126 |
| abstract_inverted_index.optimized | 148, 186 |
| abstract_inverted_index.products. | 64 |
| abstract_inverted_index.quadratic | 136 |
| abstract_inverted_index.reception | 31 |
| abstract_inverted_index.validated | 206 |
| abstract_inverted_index.variables | 85, 102 |
| abstract_inverted_index.analytics. | 21 |
| abstract_inverted_index.components | 47 |
| abstract_inverted_index.computing, | 17 |
| abstract_inverted_index.dimensions | 71 |
| abstract_inverted_index.identified | 150 |
| abstract_inverted_index.parameters | 149, 187 |
| abstract_inverted_index.polynomial | 137 |
| abstract_inverted_index.regression | 140 |
| abstract_inverted_index.responses. | 146 |
| abstract_inverted_index.technology | 39 |
| abstract_inverted_index.Methodology | 110 |
| abstract_inverted_index.frequency), | 107 |
| abstract_inverted_index.independent | 84 |
| abstract_inverted_index.intelligent | 63 |
| abstract_inverted_index.rectangular | 76 |
| abstract_inverted_index.represented | 133 |
| abstract_inverted_index.throughput. | 37 |
| abstract_inverted_index.coefficients | 141 |
| abstract_inverted_index.demonstrated | 212 |
| abstract_inverted_index.experimental | 129, 217 |
| abstract_inverted_index.increasingly | 9 |
| abstract_inverted_index.transmission | 29 |
| abstract_inverted_index.communication | 4 |
| abstract_inverted_index.significantly. | 7 |
| abstract_inverted_index.characteristics | 73 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 2 |
| citation_normalized_percentile.value | 0.13055165 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |