Scheduling UAV Swarm with Attention-based Graph Reinforcement Learning for Ground-to-air Heterogeneous Data Communication-Reference-Cited by-同舟云学术

Scheduling UAV Swarm with Attention-based Graph Reinforcement Learning for Ground-to-air Heterogeneous Data Communication

Published:2023-10-08 Issue: Volume: Page:
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Container-title:Adjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing & the 2023 ACM International Symposium on Wearable Computing
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Author:

Ren Jiyuan¹^ORCID,Xu Yanggang¹^ORCID,Li Zuxin¹^ORCID,Hong Chaopeng²^ORCID,Zhang Xiao-Ping³^ORCID,Chen Xinlei⁴^ORCID

Affiliation:

1. Tsinghua-Berkeley Shenzhen Institute, Tsinghua University, China

2. Tsinghua Shenzhen International Graduate School, Tsinghua University, China and Key Laboratory of Ecological Remediation and Carbon Sequestration, Institute of Environment and Ecology, China

3. Tsinghua Shenzhen International Graduate School, Tsinghua University, China and RISC-V International Open Source Laboratory, China

4. Shenzhen International Graduate School, Tsinghua University, China and Pengcheng Laboratory, China

Funder

Guangdong Innovative and Entrepreneurial Research Team Program

Shenzhen 2022 Stabilization Support Program

National Key R&D program of China

Tsinghua Shenzhen International Graduate School Cross-disciplinary Research and Innovation Fund Research Plan

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3594739.3612905

Reference37 articles.

1. Average Worst-Case Secrecy Rate Maximization via UAV and Base Station Resource Allocation

2. Optimal LAP Altitude for Maximum Coverage

3. 3-D Placement of an Unmanned Aerial Vehicle Base Station (UAV-BS) for Energy-Efficient Maximal Coverage

4. DrunkWalk

5. Design Experiences in Minimalistic Flying Sensor Node Platform through SensorFly

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