Secure transmission in multi-cell massive MIMO systems
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Bibliographic record
Abstract
In this paper, we consider a multi-cell massive MIMO system with matched-filter precoding and artificial noise (AN) generation at the base station (BS) for secure downlink transmission in the presence of multi-antenna passive eavesdroppers. We derive two tight lower bounds for the achievable ergodic secrecy rate and a tight upper bound on the secrecy outage probability of the considered system. The analytical results are used to optimize the amount of power allocated for AN generation. Our results reveal that AN generation is not required in massive MIMO systems as long as the number of BS antennas is much larger than the number of eavesdropper antennas. However, as the number of eavesdropper antennas increases relative to the number of BS antennas, AN becomes beneficial and the amount of power optimally allocated to AN generation increases with the number of eavesdropper antennas.
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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