Secure Robust Resource Allocation in the Presence of Active Eavesdroppers Using Full-Duplex Receivers
Why this work is in the frame
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Bibliographic record
Abstract
We propose a robust resource allocation framework to provide physical layer security for a multiple input single output (MISO) communication system. In the considered system, we assume that the both legitimate receiver and eavesdropper are in full-duplex (FD) mode and compare the corresponding performance to conventional cooperative jamming frameworks where a half-duplex (HD) receiver is at hand. In the present paper, the adversary intends to optimize its transmit and jamming signal parameters so as to minimize the MISO secrecy rate between the legitimate transmitter and receivers. The proposed self-protection scheme eliminates the need for external helpers and provides system robustness. Moreover, we investigate robustness against channel state information uncertainty. Optimal power allocation is obtained based on worst-case secrecy rate maximization, under legitimate transmitter power constraint in the presence of an active eavesdropper. Numerical results are then provided to confirm the advantages of using FD receivers.
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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) | 0.000 | 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