Proof of Concept Low-Loss Reconfigurable Reflectarray for Beam Steering
Bibliographic record
Abstract
This paper presents a low-loss reconfigurable reflectarray (RA) design in the X-Band. It has been observed in the literature that the majority of the reconfigurable RAs are operating at the lower frequency bands (less than 5 GHz). This work is based on stretching the string towards the higher frequency bands and observing the performance of reconfigurable RAs in various aspects. An X-Band low-loss, and compact reconfigurable RA is investigated. A varactor loaded aperture coupled element is used to achieve the phase tuning agility. The element is designed by dividing the transmission line (TL) into two parts, and electronically connecting them through a single surface mount Hyper abrupt varactor diode. The proposed element exhibits 265° dynamic phase tuning ability. The element is a square of length 15.6mm (0.6 × λ at 10.5 GHz). A biasing network is also designed to isolate the RF signal from the DC. An equivalent circuit model is verified with the full-wave analysis. A reconfigurable RA of 3 × 3 elements is designed, and its ability to ±45° dynamic beam steering is evaluated for center-fed and offset feeding method. The proposed RA exhibits good potential in electronically steering the beam within ±40° with a scan loss of 4.5 dBi (from broadside), with both feed method (@ 10.5 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 | 0.000 | 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".