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- W4376619848 abstract "Unmanned Aerial Vehicles (UAVs) have become popular carriers of aerial Base Stations (BSs) to cover temporal hotspots and off-load the transmission requirements of mobile users. Although the UAV-BSs can ignore the terrestrial obstacles, using them to fast deploy for off-loading still faces the time-efficiency problem of jointly optimizing multi-objectives: such as the amount of UAV-BS swarm, 3D deployment locations, and allocating users. This work transforms the above joint optimization problem into a combinatorial problem and proposes data-driven heuristic solutions with both time efficiency and robustness. To alleviate the pressure of collecting data, this paper offers a generative neural network-based framework. Results show that the proposed data-aware method can well address the above problem with less computation iterations compared with benchmark methods." @default.
- W4376619848 created "2023-05-17" @default.
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- W4376619848 date "2023-07-01" @default.
- W4376619848 modified "2023-09-24" @default.
- W4376619848 title "UAV assisted cellular network traffic offloading: Joint swarm, 3D deployment, and user allocation optimization based on a data-aware method" @default.
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- W4376619848 doi "https://doi.org/10.1016/j.comnet.2023.109812" @default.
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