Multiband Self-Affine Fractal Antenna with Performance for 5G Connectivity
Bibliographic record
Abstract
This paper introduces a novel self-affine fractal antenna tailored for 5G applications, featuring a unique grid structure over three iterations powered by a discrete port. Constant Square Sizes do not change in size between iterations, as traditional fractal does. This demonstrates exceptional multiband performance at frequencies of 0.65, 1.07, 2, 2.14, 2.8, 4, 5.2 and 5.8[Formula: see text]GHz. The observed radiation pattern exhibits omnidirectional and bidirectional characteristics across the tested frequency range. A key innovation lies in the antenna’s self-affine fractal geometry, which achieves superior multiband functionality and miniaturization without compromising performance. A strong agreement is observed between simulated and experimental results, highlighting the reliability of the design. Compared to previously reported geometries, this antenna offers superior multiband functionality and gain, making it highly suitable for 5G applications, including cellular communication and aeronautical systems. It also uses a space-filling technique, setting a new benchmark for high-gain compact antennas.
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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".