Secure Beamforming for Cognitive Satellite Terrestrial Networks With Unknown Eavesdroppers
Why this work is in the frame
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Bibliographic record
Abstract
This article proposes a beamforming (BF) scheme for a cognitive satellite terrestrial network, where the base station (BS) and a cooperative terminal (CT) are exploited as green interference resources to enhance the system security performance in the presence of unknown eavesdroppers. Different from the related works, we assume that only imperfect channel information of the mobile user (MU) and earth station (ES) is available. Specifically, we formulate an optimization problem with the objective to degrade the possible wiretap channels within the private signal beampattern region, while imposing constraints on the signal-to-interference-plus-noise ratio (SINR) at the MU, the interference level of the ES and the total transmit power budget of the BS and CT. To solve this mathematically intractable problem, we propose a joint artificial noise generation and cooperative jamming BF scheme to suppress the interception. Finally, the effectiveness and superiority of the proposed BF scheme are confirmed through computer simulations.
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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 | 0.001 |
| 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