Signal Enhancing: Bi-Static ISAC with IRS-Mounted Target
Why this work is in the frame
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Bibliographic record
Abstract
Integrated sensing and communication (ISAC) has developed into a critical paradigm to enable beyond communication capabilities while enhancing the dual functions concurrently. However, ISAC may encounter performance limitations, due to unfavorable channel conditions and limited target size. In this paper, we investigate the intelligent reconfigurable surface (IRS)-aided bi-static ISAC networks, where the IRS is mounted directly on the surface of target. Specifically, we maximize the sensing signal-to-noise ratio (SNR) while satisfying the users’ communication requirements through jointly optimizing the transmit beamforming and IRS reflection. To solve this problem, an alternating optimization (AO) algorithm is employed to decouple the optimization variables and iteratively solve the two subproblems. Simulation results are presented to show the effectiveness of the proposed scheme.
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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 | 0.000 |
| 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) | 0.002 | 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