Secure Integrated Sensing and Communication Aided by IRS-UAV
Bibliographic record
Abstract
The secure transmission of integrated sensing and communication signals aided by intelligent reflecting surface (IRS) and unmanned aerial vehicle (UAV) is investigated in this paper, with another aerial target as a potential eavesdropper. Moreover, artificial noise (AN) is introduced to disrupt the eavesdropping, while enhancing the sensing signal-to-noise ratio. To maximize the sum secrecy rate, we jointly optimize the active and passive beamformings, AN power and UAV deployment. The formulated non-convex problem is decomposed into three subproblems and solved with an efficient algorithm iteratively. Specifically, we first introduce auxiliary variables to transform the non-convex subproblems into convex ones. Then, the UAV deployment and active and passive beamformings can be derived by successive convex approximation and semi-definite relaxation, respectively. Finally, we present simulation results to validate the effectiveness of the proposed scheme.
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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 | 0.000 |
| 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) | 0.000 | 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".