Transmit power minimization for IRS-assisted NOMA-UAV networks
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Bibliographic record
Abstract
The flexibility of unmanned aerial vehicles (UAVs) allows them to be quickly deployed to support ground users. Intelligent reflecting surface (IRS) can reflect the incident signal and form passive beamforming to enhance the signal in the specific direction. Motivated by the promising benefits of both technologies, we consider a new scenario in this paper where a UAV uses non-orthogonal multiple access to serve multiple users with IRS. According to their distance to the UAV, the users are divided into the close users and remote users. The UAV hovers above the close users due to their higher rate requirement, while the IRS is deployed near the remote users to enhance their received power. We aim at minimizing the transmit power of UAV by jointly optimizing the beamforming of UAV and the phase shift of IRS while ensuring the decoding requirement. However, the problem is non-convex. Therefore, we decompose it into two sub-problems, including the transmit beamforming optimization and phase shift optimization, which are transformed into second-order cone programming and semidefinite programming, respectively. We propose an iterative algorithm to solve the two sub-problems alternatively. Simulation results prove the effectiveness of the proposed scheme in minimizing the transmit power of UAV.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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