Joint User Grouping and UAV Placement for UAV-Enabled Distributed MIMO Systems
Bibliographic record
Abstract
The cooperation of unmanned aerial vehicles (UAVs) with ground users to form a distributed MIMO (D-MIMO) system is a promising approach to improve the quality of wireless service in communication hot-spots. However, the performance of the system is jointly constrained by the placement of UAV-base stations (UAV-BSs) and the backhaul signal processing capabilities of ground stations. To address the above issues, this paper proposes a cooperative framework for UAV-BS in communication hot-spots, which effectively enhances system performance by jointly considering access link optimization and ground station processing capacity constraints. Specifically, by dividing ground users into several groups and forming independent D-MIMO subsystems with corresponding UAV-BS clusters, the system capacity and connection probability are effectively improved. The joint optimization problem of user grouping and UAV-BS placement is modeled as a non-convex optimization problem, and an efficient solution combining heuristic search and expectation-maximization (EM) algorithm is proposed. Simulation results demonstrate that the proposed framework can significantly improve the communication performance of the system while satisfying backhaul processing capacity constraints.
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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) | 0.000 | 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".