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Deep-Reinforcement-Learning-Based Drone Base Station Deployment for Wireless Communication Services
Getaneh Berie Tarekegn
*
, Rong Terng Juang
, Hsin Piao Lin
, Yirga Yayeh Munaye
,
Li Chun Wang
, Mekuanint Agegnehu Bitew
*
此作品的通信作者
電機工程學系
開源智能聯網研究中心
研究成果
:
Article
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同行評審
54
引文 斯高帕斯(Scopus)
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Keyphrases
Learning-based
100%
Wireless Services
100%
Base Station Deployment
100%
Deep Reinforcement Learning (deep RL)
100%
Drone Base Station
100%
Communication Networks
50%
Network Connectivity
50%
Communication Coverage
50%
Received Signal
25%
Neural Network
25%
Mobile Users
25%
Network Performance
25%
User Location
25%
Dynamic Environment
25%
Convolutional Neural Network
25%
Estimation Model
25%
Control Strategy
25%
Dynamic Control
25%
Promising Solutions
25%
Network Throughput
25%
Transmission Coverage
25%
Link Quality
25%
Highly Flexible
25%
Wireless Communication Systems
25%
User Requirements
25%
Network Design
25%
Flexible Deployment
25%
Drone
25%
Significant Networks
25%
Q-learning Algorithm
25%
Dynamic Mobility
25%
Deep Q-learning Algorithm
25%
Transmission Network
25%
Mobility Control
25%
Link Quality Estimation
25%
Flexible Dynamics
25%
Scalable Control
25%
Computer Science
Learning Algorithm
100%
Wireless Communication
100%
Communication Service
100%
Network Connectivity
100%
Deployment Base Station
100%
Deep Reinforcement Learning
100%
Convolutional Neural Network
50%
Network Performance
50%
Dynamic Environment
50%
Control Strategy
50%
wireless communication system
50%
User Requirement
50%
Network Design
50%