A Bidirectional MEMS-Like Passive Beamformer for Emerging Millimeter-Wave Applications
Bibliographic record
Abstract
In this article, the design and implementation of a low-loss bidirectional microelectromechanical system (MEMS)-like passive beamformer for emerging millimeter-wave (mm-Wave) applications are illustrated. A 4$\times $4 phased-array antenna (PAA) is fabricated employing the proposed beamformer for demonstration. The phase shifter (PS) embedded in the beamformer operates based on the principle of loaded-transmission line (TL) PSs. Slow wave mechanism is employed to shrink the size of the PS. The PS measurement results show the average insertion loss (IL) of 1.3 dB in all the tuning states and the IL variation is 0.9 dB. The PS provides 380° of the phase tuning range in a compact footprint area of 2.4 mm$\times $3 mm. The antenna array incorporates slot-coupled patch antennas with left-handed circularly polarized (LHCP) radiation. The operating frequency bandwidth of the antenna system ranges from 28 to 30 GHz to provide co-pol/X-pol discrimination of more than 12 dB for all the steering angles. Measurement results show the beam steering angular range of ± 30° in both elevation and azimuth planes. The measurement results also show the peak directivity of 18.48 dBic and the radiation efficiency of 58% at boresight at the frequency of 29 GHz. The efficiency drops 16% when the steering angle reaches the maximum.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".