Matching Combined Heterogeneous Multi-Agent Reinforcement Learning for Resource Allocation in NOMA-V2X Networks

Computer Science

• Channel Assignment 16%
• Communication Overhead 16%
• Computation Complexity 16%
• Deep Reinforcement Learning 16%
• Energy Efficiency 16%
• multi agent 33%
• Multi-Agent Reinforcement Learning 100%
• Multiple Access 16%
• Noma 100%
• Quality of Service 16%
• Resource Allocation 100%
• Service Requirement 16%
• Spectrum Efficiency 16%
• spectrum sharing 16%