Improving User Data Rate Performance for Hybrid RF/VLC Outdoor Vehicular Communications
Maged Fakirah(Chengdu University of Technology), Mesfin Leranso Betalo(Shenzhen University), Mohammad A. B. Mohammad(University of Electronic Science and Technology of China), Supeng Leng(University of Electronic Science and Technology of China), Ahmed Abualnor(Southwest Jiaotong University)
Cited by 4
Related Papers
Multi-Agent Deep Reinforcement Learning-Based Task Scheduling and Resource Sharing for O-RAN-Empowered Multi-UAV-Assisted Wireless Sensor Networks
|IEEE Transactions on Vehicular Technology|2023|55
Dynamic Charging and Path Planning for UAV-Powered Rechargeable WSNs Using Multi-Agent Deep Reinforcement Learning
|IEEE Transactions on Automation Science and Engineering|2025|37
Pattern-based hybrid book recommendation system using semantic relationships
|Scientific Reports|2023|33
Multi-Agent DRL-Based Energy Harvesting for Freshness of Data in UAV-Assisted Wireless Sensor Networks
|IEEE Transactions on Network and Service Management|2024|31
Generative AI-Driven Multiagent DRL for Task Allocation in UAV-Assisted EMPD Within 6G-Enabled SAGIN Networks
|IEEE Internet of Things Journal|2025|20