3D Drone-cell deployment optimization for drone assisted radio access networks
Why this work is in the frame
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Bibliographic record
Abstract
Drone-cell can enhance both the capacity and the coverage of Radio Access Networks (RAN) through relaying data between base stations and potential users. In this paper, we investigate the 3D spatial deployment problem of drone-cell in Drone Assisted Radio Access Networks (DA-RAN), and propose a solution based on the Particle Swarm Optimization (PSO) algorithm. According to the drone-to-ground channel model, we formulate the drone-cell deployment problem with the objective to maximize coverage ratio of necessary users, while maintaining the link qualities between drone-cells and RAN. We design the per-Drone Iterated PSO (DI-PSO) algorithm to find the optimized deployments corresponding to different number of drone-cells. Simulation results show that the drone-cell deployments generated by the DI-PSO algorithm can improve RAN connectivity, and achieve higher coverage ratio when compared with the pure PSO based approach.
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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