Cellular-Connected UAV Trajectory Design with Connectivity Constraint: A Deep Reinforcement Learning Approach

IEEE Transactions on Green Communications and Networking ◽

10.1109/tgcn.2021.3073916 ◽

2021 ◽

pp. 1-1

Author(s):

Yunfei Gao ◽

Lin Xiao ◽

Fahui Wu ◽

Dingcheng Yang ◽

Zhongxiang Sun

Keyword(s):

Reinforcement Learning ◽

Learning Approach ◽

Trajectory Design ◽

Connectivity Constraint

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Energy-efficient UAV trajectory design for backscatter communication: A deep reinforcement learning approach

China Communications ◽

10.23919/jcc.2020.10.009 ◽

2020 ◽

Vol 17 (10) ◽

pp. 129-141

Author(s):

Yiwen Nie ◽

Junhui Zhao ◽

Jun Liu ◽

Jing Jiang ◽

Ruijin Ding

Keyword(s):

Reinforcement Learning ◽

Energy Efficient ◽

Learning Approach ◽

Trajectory Design ◽

Backscatter Communication

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Joint Trajectory Design and BS Association for Cellular-Connected UAV: An Imitation Augmented Deep Reinforcement Learning Approach

IEEE Internet of Things Journal ◽

10.1109/jiot.2021.3093116 ◽

2021 ◽

pp. 1-1

Author(s):

Yu-Jia Chen ◽

Da-Yu Huang

Keyword(s):

Reinforcement Learning ◽

Learning Approach ◽

Trajectory Design

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Trajectory Design for UAV-Based Internet-of-Things Data Collection: A Deep Reinforcement Learning Approach

IEEE Internet of Things Journal ◽

10.1109/jiot.2021.3102185 ◽

2021 ◽

pp. 1-1

Author(s):

Yang Wang ◽

Zhen Gao ◽

Jun Zhang ◽

Xianbin Cao ◽

Dezhi Zheng ◽

...

Keyword(s):

Reinforcement Learning ◽

Data Collection ◽

Internet Of Things ◽

Learning Approach ◽

Trajectory Design

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3D UAV Trajectory Design and Frequency Band Allocation for Energy-Efficient and Fair Communication: A Deep Reinforcement Learning Approach

IEEE Transactions on Wireless Communications ◽

10.1109/twc.2020.3016024 ◽

2020 ◽

Vol 19 (12) ◽

pp. 7796-7809

Author(s):

Ruijin Ding ◽

Feifei Gao ◽

Xuemin Sherman Shen

Keyword(s):

Reinforcement Learning ◽

Frequency Band ◽

Energy Efficient ◽

Learning Approach ◽

Trajectory Design

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Trajectory Design and Generalization for UAV Enabled Networks:A Deep Reinforcement Learning Approach

2020 IEEE Wireless Communications and Networking Conference (WCNC) ◽

10.1109/wcnc45663.2020.9120668 ◽

2020 ◽

Author(s):

Xuan Li ◽

Qiang Wang ◽

Jie Liu ◽

Wenqi Zhang

Keyword(s):

Reinforcement Learning ◽

Learning Approach ◽

Trajectory Design

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Three-Dimensional Trajectory Design for Multi-User MISO UAV Communications: A Deep Reinforcement Learning Approach

10.1109/iccc52777.2021.9580401 ◽

2021 ◽

Author(s):

Yang Wang ◽

Zhen Gao

Keyword(s):

Reinforcement Learning ◽

Three Dimensional ◽

Learning Approach ◽

Trajectory Design

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Trajectory Design in UAV-Aided Mobile Crowdsensing: A Deep Reinforcement Learning Approach

ICC 2021 - IEEE International Conference on Communications ◽

10.1109/icc42927.2021.9500579 ◽

2021 ◽

Author(s):

Xi Tao ◽

Abdelhakim Senhaji Hafid

Keyword(s):

Reinforcement Learning ◽

Learning Approach ◽

Trajectory Design ◽

Mobile Crowdsensing

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Intelligent Trajectory Design for Secure Full- Duplex MIMO-UAV Relaying Against Active Eavesdroppers: A Model-Free Reinforcement Learning Approach

IEEE Access ◽

10.1109/access.2020.3048021 ◽

2021 ◽

Vol 9 ◽

pp. 4447-4465

Author(s):

Milad Tatar Mamaghani ◽

Yi Hong

Keyword(s):

Reinforcement Learning ◽

Full Duplex ◽

Learning Approach ◽

Trajectory Design ◽

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Service Chaining Offloading Decision in the EdgeAI: A Deep Reinforcement Learning Approach

2020 21st Asia-Pacific Network Operations and Management Symposium (APNOMS) ◽

10.23919/apnoms50412.2020.9237048 ◽

2020 ◽

Author(s):

Minkyun Lee ◽

Choong Seon Hong

Keyword(s):

Reinforcement Learning ◽

Learning Approach

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Emergent Control of MPSoC Operation by a Hierarchical Supervisor / Reinforcement Learning Approach

2020 Design, Automation & Test in Europe Conference & Exhibition (DATE) ◽

10.23919/date48585.2020.9116574 ◽

2020 ◽

Author(s):

Florian Maurer ◽

Bryan Donyanavard ◽

Amir M. Rahmani ◽

Nikil Dutt ◽

Andreas Herkersdorf

Keyword(s):

Reinforcement Learning ◽

Learning Approach

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