A Wideband Reconfigurable Surface Enabled by Schiffman Phase Shifter for 6G cmWave OAM Beam Scanning
Bibliographic record
Abstract
This paper introduces a compact wideband Reconfigurable Intelligent Surface (RIS) leveraging Schiffman phase shifters to overcome the traditional narrowband limitations of RIS technology. The proposed design achieves ±15∘ phase balance across a broad frequency range of 7.5–13 GHz, addressing a key challenge in RIS design. The proposed RIS features a compact unit cell, with dimensions of (0.25λ×0.25λ) at 10.25 GHz, integrating a single PIN diode and a tailored internal geometry to enable efficient phase control and scalable implementation. Experimental validation is carried out in two phases: initially, the unit cell is characterized using a waveguide setup; subsequently, a 30cm×30cm RIS panel is fabricated and tested under horn antenna excitation. The measured data exhibit strong agreement with simulations, demonstrating the accuracy and robustness of the proposed design. The full RIS surface is further evaluated for its reconfigurability and ability to generate Orbital Angular Momentum (OAM) beam scanning. These findings highlight the design’s potential for enabling key 6G communication features, offering a compact and wideband RIS solution through the integration of Schiffman phase shifters and contributing to advancements in next-generation wireless systems.
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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 | 0.001 |
| 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".