Joint Secure Transceiver Design and Power Allocation for AN-Assisted MIMO Networks
Why this work is in the frame
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Bibliographic record
Abstract
In this paper, we focus on antieavesdropping design in a multicell multiuser interference channel coexisting with a multiantenna eavesdropper, in which multiuser interference arises as a nonneglectable factor in securing communication. Supposing the eavesdropper is equipped with an arbitrary number of antennas, we jointly exploit the role of inherent multiuser interference and artificial noise (AN) to enhance security, and propose a noniterative secure transceiver design under a multiple input multiple output (MIMO) framework. The quantity relationship of system parameters is then analyzed to ensure feasibility. And the achievable secrecy rate is then derived without any knowledge of the eavesdropper. Finally, to balance the power allocated to AN and secrecy data, a power allocation strategy aiming at maximizing the achievable secrecy rate is designed, while guaranteeing legitimate users the required quality of service. With the adopted design, both the multiuser interference and AN are leveraged to facilitate communication security such that the proposed secure transceiver design can adapt to changes in eavesdropping antennas. Extensive numerical results have verified our analysis and demonstrated that the proposed power allocation strategy outperforms the baseline algorithms in terms of the achievable secrecy rate.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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