Towards Efficient and Optimal Joint Beamforming and Antenna Selection: A Machine Learning Approach

Keyphrases

• Machine Learning Approach 100%
• Antenna Selection 100%
• Joint Beamforming 100%
• Graph Neural Network 100%
• Branch-and-bound Algorithm 75%
• Neural Network 50%
• Reduced Complexity 25%
• Numerical Experiments 25%
• Wireless Communication 25%
• Vanilla 25%
• Branch-and-bound 25%
• Joint Transmission 25%
• Approximate Solution 25%
• Near-optimal Solution 25%
• High Probability 25%
• Selection Problem 25%
• Feasible Solution 25%
• Dynamic Nature 25%
• NP-hard Problem 25%
• Computational Burden 25%
• Communication Scenarios 25%
• Suboptimal Solutions 25%
• Transmit Beamforming 25%
• Transmitting Antennas 25%
• Greedy Method 25%
• Imitation Learning 25%
• Supervised Deep Learning 25%
• Non-convex Relaxation 25%
• Neural Network Method 25%

Computer Science

• Machine Learning Approach 100%
• Graph Neural Network 100%
• Branch-and-Bound Algorithm 75%
• Wireless Communication 25%
• Branch-and-Bound Algorithm Design 25%
• Problem Selection 25%
• Supervised Learning 25%
• Approximate Solution 25%
• Feasible Solution 25%
• Dynamic Nature 25%

Chemical Engineering

• Learning System 100%
• Neural Network 100%
• Scalability 25%
• Supervised Learning 25%