Experienced Deep Reinforcement Learning with Generative Adversarial Networks (GANs) for Model-Free Ultra Reliable Low Latency Communication

Computer Science

• Deep Reinforcement Learning 100%
• Generative Adversarial Networks 100%
• Ultra Reliable Low Latency Communication 100%
• Learning Framework 53%
• Resource Allocation 23%
• Network Condition 15%
• Rate Constraint 15%
• Frequency Division Multiple Access 15%
• Learning Agent 15%
• Wireless Networks 7%
• Synthetic Data 7%
• Allocation Problem 7%
• Minimization Problem 7%
• Fixed Points 7%
• Optimal Performance 7%
• Reinforcement Learning 7%
• Theoretical Limit 7%
• Wireless System 7%
• Power Allocation 7%
• Service Requirement 7%
• Access Resource 7%

Engineering

• Reinforcement Learning 100%
• Ultra-Reliable Low Latency Communication 100%
• Rate Constraint 15%
• Extreme Condition 15%
• Network Condition 15%
• Orthogonal Frequency Division Multiple Access 15%
• Simulation Result 7%
• Multiuser 7%
• Broad Range 7%
• Transients 7%
• Power Allocation 7%
• Resource Allocation Problem 7%
• Minimization Problem 7%
• Data Rate 7%
• Fixed Points 7%
• Optimal Performance 7%
• Service Requirement 7%
• Resource Block 7%

Keyphrases

• End-to-end Reliability 16%
• Network Requirements 8%
• Highly Reliable Systems 8%
• Generator Output 8%