Enhancing <scp>5G</scp> antenna performance by using <scp>3D FSS</scp> structures
Bibliographic record
Abstract
In this work, an enhanced 3D frequency selective surface (FSS) patch antenna is proposed for 5G applications. A 23 to 26 GHz patch antenna was first designed before improving its performance by adding a 3 × 5 unit cell two-layer 2D transmission FSS structure. Then, reflective walls were placed on the side edges of the obtained structure in order to focus the incident field towards the main lobe; the aim being to build a 3D FSS structure without requiring the 3D printing technique. The total size of the obtained antenna is of 40 × 40 × 14 mm3. A comparative study was carried out between the performances of the patch antenna, the 2D FSS antenna and the 3D FSS antenna. A good agreement was observed between simulated results and measurements. An improvement of almost 3 and 2 dBi was obtained compared to the 2D FSS case, respectively, in simulated and measured results, while the side lobes in radiation patterns were decreased by more than 4 dBi, which confirms the adequate proposed design in switching to 3D structures.
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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 | 0.001 | 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".