0 Datasets
0 Files
Get instant academic access to this publication’s datasets.
Yes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.
Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.
Yes, message the author after sign-up to request supplementary files or replication code.
Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaborationJoin our academic network to download verified datasets and collaborate with researchers worldwide.
Get Free AccessThis paper proposes to deploy multiple unmanned aerial vehicle (UAV) mounted base stations to serve ground users collaboratively in outdoor environments with obstacles. In particular, the geographic information is employed to capture the blockage effects for air-to-ground (A2G) links caused by buildings, and a realistic blockage-aware A2G channel model is proposed to characterize the continuous variation of the channel at different locations. Based on the proposed channel model, we formulate a joint design problem of UAV three-dimensional (3-D) positioning and resource allocation, including the user association and subcarrier allocation, to maximize the minimum achievable rate among users. We propose a suboptimal iterative algorithm to solve the mixed-integer non-convex optimization problem. Specifically, the UAV positioning and resource allocation are alternately optimized in each iteration by employing the successive convex approximation (SCA) and matching theory, respectively. Simulation results reveal that the proposed algorithm outperforms several benchmark schemes in terms of the minimum achievable rate.
Pengfei Yi, Lipeng Zhu, Zhenyu Xiao, Rui Zhang, Zhu Han, Xiang‐Gen Xia (2023). Optimization of Multi-UAV Base Stations Under Blockage-Aware Channel Model. ICC 2022 - IEEE International Conference on Communications, pp. 4992-4997, DOI: 10.1109/icc45041.2023.10279600.
Datasets shared by verified academics with rich metadata and previews.
Authors choose access levels; downloads are logged for transparency.
Students and faculty get instant access after verification.
Type
Article
Year
2023
Authors
6
Datasets
0
Total Files
0
Language
English
Journal
ICC 2022 - IEEE International Conference on Communications
DOI
10.1109/icc45041.2023.10279600
Access datasets from 50,000+ researchers worldwide with institutional verification.
Get Free Access