Hybrid Machine-Learning-Based Spectrum Sensing and Allocation With Adaptive Congestion-Aware Modeling in CR-Assisted IoV Networks

Computer Science

• Channel Access 25%
• Cognitive Radio 100%
• Deep Learning Model 25%
• Intelligent Network 25%
• Internet of Vehicles 100%
• Learning System 100%
• Machine Learning 100%
• Network Capacity 25%
• Noise-to-Signal Ratio 25%
• Optimal Network 25%
• Performance Gain 25%
• Priori Knowledge 25%
• Radio Environment 25%
• Representation Learning 25%
• Spectrum Occupancy 25%
• Spectrum Resource 25%
• Support Vector Machine 25%
• Vehicle Density 25%
• Vehicular Communication 25%
• Vehicular Network 25%

Engineering

• Cognitive Radio 100%
• Dedicated Channel 33%
• Deep Learning Method 33%
• Intelligent Network 33%
• Learning System 100%
• Network Capacity 33%
• Network Node 33%
• Optimization Approach 33%
• Priori Knowledge 33%
• Radio Environment 33%
• Radio Spectra 33%
• Signal-to-Noise Ratio 33%
• Spectrogram 33%
• Spectrum Occupancy 33%
• Spectrum Resource 33%
• Support Vector Machine 33%