Joint Design of Optimal Precoding and Cooperative Jamming for Multiuser Secure Broadcast Systems
Bibliographic record
Abstract
A multiuser secure broadcast system is considered, where there are one multiantenna base station (BS), multiple single-antenna legitimate users, one multiantenna friendly jammer (FJ), and one multiantenna eavesdropper (Eve). We jointly design the optimal precoding matrix at the BS and the jamming covariance matrix at the FJ by minimizing the total transmit power of the BS and FJ under the signal-to-interference-plus-noise ratio constraints at the users and Eve. To solve this challenging problem, when the FJ has more antennas than the users and Eve, we first find the optimal structure of the jamming covariance matrix and, then, convert the problem into its equivalentconvexform. Also, we propose an iterative algorithm to jointly design the precoding and jamming covariance matrices in all scenarios. The solution obtained by this algorithm is shown to be asymptotically optimal when the FJ has more antennas than the users and Eve. Numerical results show that the proposed schemes considerably outperform the existing schemes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".