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Q-Learning Based Predictive Relay Selection for Optimal Relay Beamforming
Anastasios Dimas
, Konstantinos Diamantaras
,
Athina P. Petropulu
School of Engineering, Electrical & Computer Engineering
Research output
:
Chapter in Book/Report/Conference proceeding
›
Conference contribution
6
Scopus citations
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Dive into the research topics of 'Q-Learning Based Predictive Relay Selection for Optimal Relay Beamforming'. Together they form a unique fingerprint.
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Keyphrases
Learning-based
100%
Signal-to-interference Ratio
100%
Relay Selection
100%
Relay Beamforming
100%
Q-learning
100%
Average Signal
100%
Optimal Relay
100%
Adaptive Change
50%
Wireless
50%
Beamforming
50%
Communication Environment
50%
Self-adaptive
50%
Reinforcement Learning Approach
50%
Statistical Knowledge
50%
Source Signal
50%
Ratio Performance
50%
Autonomous Networks
50%
Engineering
Noise Ratio
100%
Q-Learning
100%
Beamforming
100%
Reinforcement Learning
50%
Learning Approach
50%
Source Signal
50%
Support Communication
50%
Computer Science
Reinforcement Learning
100%
Communication Environment
100%
Performance Ratio
100%
Learning Approach
100%