Age of information aware radio resource management in vehicular networks: A proactive deep reinforcement learning perspective
In this paper, we investigate the problem of age of information (AoI)-aware radio resource
management for expected long-term performance optimization in a Manhattan grid vehicle …
management for expected long-term performance optimization in a Manhattan grid vehicle …
Delay-optimal virtualized radio resource scheduling in software-defined vehicular networks via stochastic learning
Due to the high density of vehicles and various types of vehicular services, it is challenging
to guarantee the quality of vehicular services in current Long-Term Evolution (LTE) networks …
to guarantee the quality of vehicular services in current Long-Term Evolution (LTE) networks …
Deep-learning-based wireless resource allocation with application to vehicular networks
It has been a long-held belief that judicious resource allocation is critical to mitigating
interference, improving network efficiency, and ultimately optimizing wireless communication …
interference, improving network efficiency, and ultimately optimizing wireless communication …
Reinforcement learning-based radio resource control in 5G vehicular network
Y Zhou, F Tang, Y Kawamoto… - IEEE Wireless …, 2019 - ieeexplore.ieee.org
Recently, the number of user equipment with high mobility (such as vehicles) and the high
traffic demand is immensely increasing. To sustaining the traffic demand, Time Division …
traffic demand is immensely increasing. To sustaining the traffic demand, Time Division …
Artificial intelligence inspired transmission scheduling in cognitive vehicular communications and networks
The Internet of Things (IoT) platform has played a significant role in improving road transport
safety and efficiency by ubiquitously connecting intelligent vehicles through wireless …
safety and efficiency by ubiquitously connecting intelligent vehicles through wireless …
Scheduling the operation of a connected vehicular network using deep reinforcement learning
Driven by the expeditious evolution of the Internet of Things, the conventional vehicular ad
hoc networks will progress toward the Internet of Vehicles (IoV). With the rapid development …
hoc networks will progress toward the Internet of Vehicles (IoV). With the rapid development …
Deep reinforcement learning based resource management for multi-access edge computing in vehicular networks
In this paper, we study joint allocation of the spectrum, computing, and storing resources in a
multi-access edge computing (MEC)-based vehicular network. To support different vehicular …
multi-access edge computing (MEC)-based vehicular network. To support different vehicular …
Resource scheduling based on deep reinforcement learning in UAV assisted emergency communication networks
Unmanned aerial vehicle (UAV) assisted emergency communication is an important
technique for future B5G/6G scenario. The UAV is usually considered as a mobile relay to …
technique for future B5G/6G scenario. The UAV is usually considered as a mobile relay to …
Learning-based joint resource slicing and scheduling in space-terrestrial integrated vehicular networks
In this paper, we investigate the resource slicing and scheduling problem in the space-
terrestrial integrated vehicular networks to support both delay-sensitive services (DSSs) and …
terrestrial integrated vehicular networks to support both delay-sensitive services (DSSs) and …
Neural combinatorial deep reinforcement learning for age-optimal joint trajectory and scheduling design in UAV-assisted networks
In this article, an unmanned aerial vehicle (UAV)-assisted wireless network is considered in
which a battery-constrained UAV is assumed to move towards energy-constrained ground …
which a battery-constrained UAV is assumed to move towards energy-constrained ground …
相关搜索
- deep reinforcement resource management
- deep reinforcement vehicular networks
- resource management vehicular networks
- learning perspective vehicular networks
- reinforcement learning resource scheduling
- wireless networks resource allocation
- reinforcement learning resource allocation
- stochastic learning vehicular networks