Neural Estimation of Multi-User Capacity Regions over Discrete Channels

Keyphrases

• Capacity Region 100%
• Multi-user 100%
• User Capacity 100%
• Neural Estimation 100%
• Discrete Channel 100%
• Communication Scenarios 40%
• Optimization Problem 20%
• State Space 20%
• Neural Network 20%
• Multiple Access Channel 20%
• Optimization Procedure 20%
• Markov Decision Process 20%
• Channel Model 20%
• Optimal Policy 20%
• Reinforcement Learning 20%
• Information Rate 20%
• Continuous Domain 20%
• Multi-user Communications 20%
• Joint Model 20%
• Differentiability 20%
• Process State 20%
• Learning-based Framework 20%
• Reinforcement Learning Algorithm 20%
• Directed Information 20%
• Data-driven Methods 20%
• Two-way Channel 20%
• Decentralized Markov Decision Process 20%

Engineering

• Multiuser 100%
• Capacity Region 100%
• Reinforcement Learning 40%
• Discrete Alphabet 40%
• Markov Decision Process 40%
• Joints (Structural Components) 20%
• Optimisation Problem 20%
• Multiple Access Channel 20%
• Channel Model 20%
• Optimisation Procedure 20%
• Optimal Policy 20%
• Information Rate 20%
• Adaptability 20%

Computer Science

• Capacity Region 100%
• Markov Decision Process 40%
• Reinforcement Learning 40%
• Neural Network 20%
• Optimization Problem 20%
• Multiple Access Channel 20%
• State Space 20%
• Explicit Knowledge 20%
• Information Rate 20%
• Continuous Domain 20%
• Inherent Complexity 20%
• User Communication 20%
• Process State 20%