TBS Joint Optimization to Serve mmWave High Altitude UAVs: A Counterfactual MAB Approach
Bibliographic record
Abstract
High-altitude uncrewed aerial vehicles (UAVs) with millimeter wave communication are well-suited for fifth-generation (5G) and beyond applications. UAVs may cause significant interference to ground user equipment (GUE). We consider using a moving tethered aerial base station (TBS) as an alternative to a terrestrial base station. We consider, the UAV and GUE locations as contexts to perform joint TBS location, UAV and GUE power allocation optimization in a three-dimensional environment. We propose a contextual multi-armed bandit framework using a novel counterfactual Thompson sampling (CTS) algorithm. We compare its performance against a joint optimization using vanilla Thompson sampling (TS) and single optimization TS (SOTS) approaches. Our results show that the CTS approach converges faster. We conclude that the CTS-based approach achieves better interference mitigation for both aerial and ground users.
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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 | 0.000 | 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) | 0.001 | 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".