Compact 28GHz Microstrip Patch Antenna Design with Reduced SAR for 5G Applications
Bibliographic record
Abstract
Fulfilling the requirements of 5G applications necessitates the design of low-cost, compact, and high-performance antennas capable of supporting high data rates.As these antennas are often in direct contact with the human body, it is imperative to limit radiation exposure.This study presents the design of a Microstrip Patch Antenna (MSPA) with a resonant frequency of 28 GHz.The performance of the proposed design is evaluated using Computer Simulation Technology (CST) software.Considering the importance of compactness in 5G applications, the dimensions of the proposed antenna have been optimized for this purpose.This paper also discusses the role of the ground plane in reducing the Specific Absorption Rate (SAR).The proposed MSPA design demonstrates a high gain of 7.3 dB, a radiation efficiency of 89.4%, and compact dimensions of 5.18×3.36×0.3mm.The maximum SAR value is 1.68 W/kg (per 1 g of tissue), or 0.121 W/kg (per 10 g of tissue).These results suggest that the proposed design holds promising potential for enabling low-cost, compact, high-speed 5G devices that are safe for human tissues.This is particularly relevant for wearable devices, the Internet of Things (IoT), and mobile wireless networks.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".