Channel-Informed RIS Analysis and Optimization Using Hybrid Ray-Tracing and Full-Wave Simulation Framework
Bibliographic record
Abstract
This paper introduces a hybrid approach combining ray-tracing (RT) and full-wave numerical analysis to evaluate and optimize reconfigurable intelligent surfaces (RISs) in deterministic channels. Unlike traditional methods relying on statistical models, our approach integrates RT for deterministic channel mapping and finite element method (FEM)-based simulations to assess RIS impacts in realistic, site-specific scenarios. A nondiagonal impedance matrix is formed to link channel transfer functions to RIS tunable load impedances, accounting for mutual coupling between unit cells and enabling precise optimization for enhanced communication performance. A varactor-based RIS operating in the sub-6 GHz frequency band is designed and fabricated, with extensive simulations and real-world measurements conducted in single-input single-output (SISO) and single-input multiple-output (SIMO) scenarios. A measurement-based closedloop optimization process further refines RIS configurations. Results demonstrate substantial signal strength improvements, with strong agreement between simulations and measurements, confirming the practicality and effectiveness of the proposed method for advanced RIS-enabled communication systems.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".