Enhancing wireless applications through reconfigurable electro-mechanical reflectarray antenna design for beam steering
Bibliographic record
Abstract
The growing interest in reconfigurable intelligent surfaces (RIS) for wireless communications is evident, particularly in addressing challenges beyond the normal incidence condition of electromagnetic waves. This paper introduces an innovative approach to achieve beam steering in reflecting-type array structures, specifically reflectarrays, through the use of Reconfigurable Electro-Mechanical Reflectarray (REMR) technology. The REMR structure, equipped with a cam-shaped actuator beneath each unit cell's ground plane, serves as the basis for this design. The proposed design involves multiple reflective strips at variable heights, enabling significant adaptability to incident waves at various angles. By incorporating a cam-shaped actuator beneath the ground plane of each unit cell, a mechanical phase shifter acts as a continuous modifier of phase for incident waves, resulting in the realization of the REMR effect. The REMR structure demonstrates consistent phase and amplitude responses, facilitating efficient beam steering. Simulation and measurement results show a remarkable unwrapped phase shift range of [Formula: see text] and beam steering over a broad spectrum of incidence angles from [Formula: see text] to [Formula: see text]. Additionally, the REMR structure maintains stability even when powered off in the "defined gradient mode" due to a memory function preserving gradient states. The fabrication process utilizes 3D printers, offering flexibility and ease of customization. This comprehensive approach holds significant potential for advancing RIS technologies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 0.000 |
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 teacher head, 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".