Circular RIS-Enabled Channel Estimation and Localization for Multi-User ISAC Systems
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Bibliographic record
Abstract
Integrated sensing and communication (ISAC) is emerging as a key enabler to address the increasing demands of spectrum and throughput for ubiquitous sensing and communication. Hereafter, we consider the channel estimation and localization for multi-user ISAC systems assisted by the reconfigurable intelligent surface (RIS) technology. In order to acquire precise environmental information, we propose a novel circular RIS architecture with circularly arranged reflecting unit cells. By modeling the training signal as a low-rank third-order canonical polyadic tensor, we transform the channel estimation problem into a tensor deconstruction task. By leveraging the phase mode excitation principle, we develop a customized RIS training pattern, and retrieve the equivalent channel parameters by subspace estimation algorithms. By exploring the characteristics of RIS array manifolds and free-space propagation, we implement a unique decoupling of channel parameters for user localization, which cannot be supported by traditional linear RIS topologies. Moreover, the design degrees of freedom in the spatial and frequency dimensions are also exploited to further enhance the proposed algorithms. Simulation results indicate that the circular RIS-enabled channel estimation schemes can recover the propagation information with remarkable accuracy, thereby offering a high-level resolution of localization.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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 it