LSTM-Aided Selective Beam Tracking in Multi-Cell Scenario for mmWave Wireless Systems

Keyphrases

• Beam Tracking 100%
• Beamforming 100%
• Millimeter Wave 100%
• Wireless Systems 100%
• Long Short-term Memory 100%
• Multi-cell Scenario 100%
• Energy Overhead 75%
• Urban Areas 25%
• Memory-based 25%
• Power Consumption 25%
• Minimal Resources 25%
• Power Saving 25%
• Signaling Overhead 25%
• Multi-cell 25%
• Ray Tracing 25%
• Millimeter Wave Systems 25%
• Navigation Route 25%
• Digital Signal Processor 25%
• Reliable Communication 25%
• Additional Power 25%
• Resource Consumption 25%
• Tracking Approach 25%
• Cell Deployment 25%
• Tracking Accuracy 25%
• Analog Beamforming 25%
• Digital Beamforming 25%
• Adaptive Power 25%
• Chipset 25%
• 5G NR 25%
• Deep Reinforcement Learning (deep RL) 25%
• Reinforcement Learning Approach 25%
• Link Tracking 25%

Engineering

• Beamforming 100%
• Cell Scenario 100%
• Long Short-Term Memory 100%
• Electric Power Utilization 25%
• Millimeter Wave 25%
• Signaling Overhead 25%
• Reinforcement Learning 25%
• Digital Signal Processor 25%
• Reliable Communication 25%
• Resource Consumption 25%
• Multiple Cell 25%
• Learning Approach 25%
• Digital Beamforming 25%

Computer Science

• Wireless System 100%
• Long Short-Term Memory Network 100%
• ray-tracing 50%
• Power Consumption 50%
• Digital Signal Processor 50%
• Reliable Communication 50%
• Resource Consumption 50%
• Learning Approach 50%
• Deep Reinforcement Learning 50%