Broadband 3-D shared aperture high isolation nine-element antenna array for on-demand millimeter-wave 5G applications
Bibliographic record
Abstract
The paper presents the results of a novel 3-D shared aperture 3 × 3 matrix antenna-array for 26 GHz band 5 G wireless networks. Radiation elements constituting the array are hexagonal-shaped patches that are elevated above the common dielectric substrate by 3.35 mm and excited through a metallic rod of 0.4 mm diameter. The rod protrudes through the substrate of 0.8 mm thickness. It is shown that by isolating each radiating element in the array with a wall suppresses unwanted electromagnetic (EM) wave interactions, resulting in improvement in the antenna’s impedance matching and radiation characteristics. Moreover, the results show that by embedding hexagonal-shaped slots in the patches improve the antenna's gain and radiation efficiency performance. The subwavelength length slots in the patches essentially transform the radiating elements to exhibit metasurface characteristics when the array is illuminated by EM-waves. The proposed array structure has an average gain and radiation efficiency of 20 dBi and 93%, respectively, across 24.0–28.4 GHz. The isolation between its radiation elements is greater than 22 dB. Compared to the unslotted array the improvement in isolation between radiating elements is greater than 11 dB, and the gain and efficiency are better than 10.5 dBi, and 25%, respectively. The compact array has a fractional bandwidth of 16% and a form factor of 20×20×3.35 mm3.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".