Analysis and design of ultra-wideband PRGW hybrid coupler using PEC/PMC waveguide model
Bibliographic record
Abstract
In this paper, a new method to facilitate the design of Printed Ridge Gap Waveguide (PRGW) structures is introduced. One of the main difficulties in designing such structures is related to their simulation process which is really time and energy-consuming. Therefore, a suitable boundary condition is considered to bring about the primary structure without involving the bed of nails or mushroom unit cells. Using this technique, a wideband PRGW 3 dB hybrid double-box coupler is designed to serve in mm-wave frequencies at a center frequency of 30 GHz, which can be deployed for the next generation of mobile communication. The designed coupler provides a wide matching and isolation bandwidth with low output amplitude imbalance, which is unique in comparison with current couplers. The prototype of the proposed coupler is fabricated and measured where the simulation and measurement results show a good agreement indicating the strength of the proposed method in PRGW structure design as well. The measured results show the couplers achieve better than 10-dB return loss and isolation over the frequency range from 25 to 40 GHz (46% BW) with the power-split unbalance and phase error within ± 1 dB and ± 5°, respectively. In addition, square mushrooms are chosen here to satisfy the high impedance surface. Not only do they bring about larger stop bandwidth, but also their configuration facilitates the arrangement of them around the coupler. The proposed design has superb characteristics such as low profile, low loss, and easy integration with microwave circuits and systems that can be suitable for designing mm-wave beamforming networks.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".