Robust Secure Energy Efficient Beamforming for mmWave UAV Communications With Jittering
Bibliographic record
Abstract
This letter proposes a robust secure and energy efficient beamforming (BF) scheme for a millimeter-wave unmanned aerial vehicle (UAV) communication system with imperfect angle-of-departure (AoD) estimation of air-to-ground channel caused by jittering. Specifically, an optimization problem is formulated to maximize the worst-case secrecy energy efficiency (SEE), defined as the ratio of the sum achievable secrecy rate (ASR) to the total power consumption, subject to the UAV transmit power constraint. Due to the difficulty in solving this problem arisen from the AoD uncertainties and the non-convex structures of SEE and ASR, we first adopt the discretization method to simplify AoD uncertainties to a deterministic form and then exploit the successive convex approximation approach with auxiliary variables to convert the original problem into a convex one. Finally, an iterative algorithm is designed to obtain the suboptimal solution. Numerical results are provided to confirm the effectiveness and superiority of the proposed robust BF scheme compared to some benchmark schemes.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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".