Stacked-Intelligent-Surface-Assisted MIMO Integrated Sensing and Communication
Bibliographic record
Abstract
This paper investigates the application of Stacked Intelligent Surfaces (SIS) in Integrated Sensing and Communication (ISAC) systems. Unlike conventional multiple-input multiple-output (MIMO) systems, SIS offer unique advantages in terms of complexity and energy efficiency by performing signal processing directly on radio waves, potentially reducing the need for extensive RF chains and antennas. We explore two SIS-assisted ISAC schemes: a hybrid digital-analog beamforming scheme and an analog-only beamforming scheme. To evaluate these schemes, we consider two case studies: integrated data transmission with channel estimation for the hybrid scheme, and data transmission integrated with target detection for the analog-only scheme. In the first scenario, we demonstrate that SIS can provide better rates and channel estimation accuracy compared with hybrid beamforming in multiple-input single-output (MISO) systems. In the second scenario, we show that SIS enable data transmission with target detection and radar beamforming that closely match binary-beam MIMO. Finally, we outline several future extensions to further enhance the capabilities and applicability of SIS-assisted ISAC 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 | 0.000 |
| 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".