Design and analysis of a 60 GHz high gain wideband magneto electric dipole antenna array based on trapped printed gap waveguide technology
Bibliographic record
Abstract
This paper introduces an innovative design and analysis of a magneto-electric dipole antenna exhibiting high-gain, ultra-wideband operation, and stable radiation characteristics in the 60-GHz mm-wave band. Furthermore, the trapped printed gap waveguide (TPGW) technology is presented as a low-cost, minimal-loss, and low-dispersion guiding structure to feed the proposed antenna. The antenna covers a relative matching bandwidth of over 33.33% from 50 to 70 GHz with a maximum gain up to 8 dBi. In addition, the antenna is integrated with a perforated dielectric substrate layer lens on the antenna's broadside location, enhancing the gain by an average of 3 dB along its entire operational bandwidth. Moreover, an efficient approach for designing a large ME dipole antenna array and its corporate feeding network is presented. Both ME-dipole sub-arrays and the out-of-phase power divider with WR-15 standard interface are designed and studied separately, where a systematic design procedure is presented to obtain initial design parameters. A 2 × 2 planar antenna array is designed and implemented, featuring proper integration between the radiating elements and a differentially fed wide-bandwidth TPGW power divider. Then, the operation of the individual components has been assessed using simulation and measurements. Furthermore, an in-depth mathematical analysis is presented to investigate the potential resonance conditions arising from disparities in complementary components. Consequently, a proposed solution is provided to break the resonance loop and shield the two opposing sub-arrays. The 2 × 2 array of ME-dipoles has overall dimensions of 1.6[Formula: see text] ×1.4[Formula: see text] and demonstrates an impedance bandwidth ([Formula: see text]- 10 dB) exceeding 33.33% at 60 GHz, with a peak gain of over 18 dBi.
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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".