Ergodic Secrecy Rate of $K$-User MISO Broadcast Channel With Improved Random Beamforming
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Bibliographic record
Abstract
In this paper, we study the secrecy performance of a K-user multi-input single-output (MISO) broadcast channel with random beamforming (RB), where the transmitter is equipped with N antennas, and the eavesdropper has Ne antennas. We first propose a signal-splitting random beamforming (SSRB) scheme for a single-user MISO wiretap channel, and then improve the SSRB scheme with power-minimizing (PM), which is called a PM-SSRB scheme. To improve the spectral efficiency of a multiuser network, we combine PM with non-orthogonal multiple access (NOMA), and propose a hybrid NOMA (H-NOMA) scheme and a signal-splitting NOMA (SS-NOMA) scheme for the K-user MISO wiretap channel, respectively. The sum ergodic secrecy rate of the K-user scenario is analyzed comprehensively, and a closed-form expression for the lower bound on the ergodic secrecy rate is also derived for the single-user case. Simulation results show that, compared with the traditional hybrid artificial fast-fading scheme (AFF) and artificial noise (AN) scheme, the proposed SSRB scheme and PM-SSRB scheme perform much better in terms of the ergodic secrecy rate in all power regimes. More importantly, when the eavesdropper has more antennas than the transmitter, our schemes always outperform the AFF and AN schemes. The PM-SSRB scheme is also shown to be superior to the secret-key AFF scheme. For the multiuser case, the SS-NOMA scheme can achieve higher ergodic secrecy rate than the H-NOMA scheme.
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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 | 0.001 | 0.001 |
| 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