Achievable secrecy rate analysis in mmWave ad hoc networks with multi‐array antenna transmission and artificial noise
Bibliographic record
Abstract
Abstract This paper analyzes the achievable secrecy rate in a millimeter wave (mmWave) ad hoc network with multi‐array antenna transmission in the presence of non‐colluding and colluding eavesdroppers. By exploiting the tools of stochastic geometry, the average achievable secrecy rate is derived, taking into consideration the impact of blockages, directional beamforming, and Nakagami‐ m fading. Moreover, a simple yet effective artificial noise transmission (Tx‐AN) technique is applied at the transmitting nodes to enhance the secrecy performance while the channel state information at the desired transmitter is unknown. Numerical and simulation results are presented for the average achievable secrecy rate in the mmWave ad hoc network without and with the Tx‐AN technique. For example, at the high transmit power (>20 dBm), the average achievable secrecy rate with the Tx‐AN technique is up to three times higher than that obtained when the Tx‐AN technique is not used. Furthermore, the results demonstrate the secrecy robustness of the Tx‐AN technique against increasing eavesdroppers' intensity. Finally, the proper power allocation between the message and AN signals that maximizes the average achievable secrecy rate is computed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".