Dynamic Spectrum Access in Non-stationary Environments: A DRL-LSTM Integrated Approach

Keyphrases

• Deep Reinforcement Learning (deep RL) 100%
• Long Short-term Memory 100%
• Dynamic Spectrum Access 100%
• Non-stationary Environments 100%
• Markov Decision Process 66%
• Non-stationarity 66%
• Hidden Modes 66%
• Secondary User 66%
• Active Mode 66%
• Memory-based 33%
• Access Issues 33%
• Channel Dynamics 33%
• Reinforcement Learning Framework 33%
• Shared Set 33%
• Secondary Primary 33%
• Channel Access 33%
• Orthogonal Channels 33%
• Spectrum Utilization 33%
• Access Strategy 33%
• Coupled Channels 33%
• Primary User Activity 33%

Engineering

• Reinforcement Learning 100%
• Long Short-Term Memory 100%
• Dynamic Spectrum Access 100%
• Stationarity 66%
• Primary User 66%
• Markov Decision Process 66%
• Secondary User 66%
• Active Mode 66%
• Simulation Result 33%
• Spectrum Utilization 33%

Computer Science

• Deep Reinforcement Learning 100%
• Long Short-Term Memory Network 100%
• Dynamic Spectrum Access 100%
• Markov Decision Process 66%
• Secondary User 66%
• Learning Framework 33%
• Channel Access 33%
• Spectrum Utilization 33%