[HTML][HTML] Joint Optimization of Age of Information and Energy Consumption in NR-V2X System Based on Deep Reinforcement Learning
As autonomous driving may be the most important application scenario of the next
generation, the development of wireless access technologies enabling reliable and low …
generation, the development of wireless access technologies enabling reliable and low …
Optimizing Age of Information in Vehicular Edge Computing with Federated Graph Neural Network Multi-Agent Reinforcement Learning
With the rapid development of intelligent vehicles and Intelligent Transport Systems (ITS),
the sensors such as cameras and LiDAR installed on intelligent vehicles provides higher …
the sensors such as cameras and LiDAR installed on intelligent vehicles provides higher …
Semantic-Aware Spectrum Sharing in Internet of Vehicles Based on Deep Reinforcement Learning
This work aims to investigate semantic communication in high-speed mobile Internet of
vehicles (IoV) environments, with a focus on the spectrum sharing between vehicle-to …
vehicles (IoV) environments, with a focus on the spectrum sharing between vehicle-to …
Semantic-Aware Resource Allocation Based on Deep Reinforcement Learning for 5G-V2X HetNets
This letter proposes a semantic-aware resource allocation (SARA) framework with flexible
duty cycle (DC) coexistence mechanism (SARADC) for 5G-V2X Heterogeneous Network …
duty cycle (DC) coexistence mechanism (SARADC) for 5G-V2X Heterogeneous Network …
Reconfigurable Intelligent Surface Assisted VEC Based on Multi-Agent Reinforcement Learning
Vehicular edge computing (VEC) is an emerging technology that enables vehicles to
perform high-intensity tasks by executing tasks locally or offloading them to nearby edge …
perform high-intensity tasks by executing tasks locally or offloading them to nearby edge …