Fast Power Control Adaptation via Meta-Learning for Random Edge Graph Neural Networks

Keyphrases

• Average Sum Rate 25%
• Channel Coefficients 25%
• Channel Condition 25%
• Channel State Information 25%
• Control Adaptation 100%
• Convolutional Architecture 25%
• Data-driven Design 25%
• Decentralized Wireless Networks 25%
• Edge Graph 100%
• Fast Power Control 100%
• Few-shot Adaptation 25%
• First-order 25%
• Graph Convolutional Network 25%
• Graph Neural Network 100%
• Interference Graph 25%
• Linear Graphs 25%
• Meta-learning 100%
• Multiple Topologies 25%
• Network Configuration 25%
• Neural Network Architecture 25%
• Policy Mapping 25%
• Power Control 25%
• Power Control Policy 50%
• Power Vector 25%
• Random Edge 100%
• Spatial Weights 25%
• Stochastic Optimization Problem 25%
• Time-varying Topology 25%

Engineering

• Channel Condition 50%
• Channel State Information 50%
• Design Method 50%
• Maximization 50%
• Neural Network Architecture 50%
• Optimisation Problem 50%
• Power Control 100%
• Power Control Policy 100%
• Power Vector 50%

Computer Science

• Channel Condition 25%
• Channel State Information 25%
• Graph Neural Network 100%
• Interference Graph 25%
• Network Configuration 25%
• Neural Network Architecture 25%
• Optimization Problem 25%
• Stochastic Optimization 25%
• sum rate 25%
• Wireless Networks 25%