A Secure Multiradio Resource Scheme Using Cooperative DRL Agents for Heterogeneous Inter-RAN Slicing Under Hardware Impairments

Keyphrases

• Deep Reinforcement Learning (deep RL) 100%
• Hardware Impairments 100%
• Reinforcement Learning Agent 100%
• Multi-radio 100%
• RAN Slicing 100%
• Self-optimization 100%
• Network Slicing 66%
• Radio Resources 66%
• Advanced Encryption Standard 66%
• Service Level Agreement 33%
• Traffic Load 33%
• Spectral Efficiency 33%
• Reinforcement Learning Framework 33%
• Quality of Service Guarantee 33%
• Learning Process 33%
• Training Time 33%
• Secure Communication 33%
• Multi-slice 33%
• Optimization Scheme 33%
• Network Paradigm 33%
• Actor-critic 33%
• Innovative Technologies 33%
• Memory Network 33%
• Non-ideal Hardware 33%
• Multi-actor 33%
• Partially Observable Markov Decision Process 33%
• Major Challenges 33%
• Open Radio Access Network (O-RAN) 33%
• Memory Usage 33%
• Term Memory 33%
• Sixth Generation (6G) Networks 33%
• Fluctuating Traffic 33%
• Security Resource Allocation 33%
• Zero-touch Networks 33%

Computer Science

• Deep Reinforcement Learning 100%
• Network Slicing 100%
• Learning Agent 100%
• Advanced Encryption Standard 100%
• Quality of Service 50%
• Resource Allocation 50%
• Service-Level Agreement 50%
• Learning Framework 50%
• Service Requirement 50%
• Long Short-Term Memory Network 50%
• Learning Process 50%
• Markov Decision Process 50%
• Spectral Efficiency 50%
• Network Paradigm 50%
• Secure Communication 50%
• 6G 50%