Millimeter-Wave High-Gain SIW End-Fire Bow-tie Antenna
Bibliographic record
Abstract
This communication presents a high-gain bow-tie antenna that operates across 57-64 GHz for application in high data rate point-to-point communication systems. The proposed antenna consists of a pair of bow-tie radiators, where each radiator is etched on the opposite side of the common dielectric substrate and fed through substrate integrated waveguide (SIW) feed-line. The bow-tie radiators are arranged to cross each other symmetrically by tilting the feed-lines by 30° to enhance the antenna gain and to obtain the required radiation pattern. The antenna is loaded with a pair of double G-shaped resonators (DGRs) that are located in a region between the radiators and SIW to suppress the back-lobe level in the H-plane. Embedded in the E-plane of the antenna is an array of zero-index metamaterial (ZIM) unit-cells whose purpose is to effectively confine the electromagnetic waves in the end-fire direction to enhance its gain performance. A prototype antenna was fabricated and its performance was measured to validate the simulation results. The proposed structure exhibits a gain of 11.8-12.5 dBi over the frequency range of 57-64 GHz with reflection coefficient less than $- 11\;\hbox{dB}$. In addition, the proposed antenna exhibits good cross-polarization, which is less than $- 17\;\hbox{dB}$ in both E- and H-planes at 60 GHz.
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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 | 0.001 | 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".