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Graph neural networks and deep reinforcement learning based resource allocation for v2x communications
In the rapidly evolving landscape of Internet of Vehicles (IoV) technology, Cellular Vehicle-to-
Everything (C-V2X) communication has attracted much attention due to its superior …
Everything (C-V2X) communication has attracted much attention due to its superior …
A survey on video streaming for next-generation vehicular networks
CJ Huang, HW Cheng, YH Lien, ME Jian - Electronics, 2024 - mdpi.com
As assisted driving technology advances and vehicle entertainment systems rapidly
develop, future vehicles will become mobile cinemas, where passengers can use various …
develop, future vehicles will become mobile cinemas, where passengers can use various …
URLLC-awared resource allocation for heterogeneous vehicular edge computing
Vehicular edge computing (VEC) is a promising technology to support real-time vehicular
applications, where vehicles offload intensive computation tasks to the nearby VEC server …
applications, where vehicles offload intensive computation tasks to the nearby VEC server …
Secure transmission scheme based on joint radar and communication in mobile vehicular networks
Vehicle-to-vehicle (V2V) communication applications face significant challenges to security
and privacy since all types of possible breaches are common in connected and autonomous …
and privacy since all types of possible breaches are common in connected and autonomous …
Delay-sensitive task offloading in vehicular fog computing-assisted platoons
Vehicles in platoons need to process many tasks to support various real-time vehicular
applications. When a task arrives at a vehicle, the vehicle may not process the task due to its …
applications. When a task arrives at a vehicle, the vehicle may not process the task due to its …
Distributed deep reinforcement learning based gradient quantization for federated learning enabled vehicle edge computing
Federated Learning (FL) can protect the privacy of the vehicles in vehicle edge computing
(VEC) to a certain extent through sharing the gradients of vehicles' local models instead of …
(VEC) to a certain extent through sharing the gradients of vehicles' local models instead of …
Cooperative edge caching based on elastic federated and multi-agent deep reinforcement learning in next-generation networks
Edge caching is a promising solution for next-generation networks by empowering caching
units in small-cell base stations (SBSs), which allows user equipments (UEs) to fetch users' …
units in small-cell base stations (SBSs), which allows user equipments (UEs) to fetch users' …
Semantic-aware spectrum sharing in internet of vehicles based on deep reinforcement learning
This article investigates semantic communication in high-speed mobile Internet of Vehicles
(IoV), focusing on spectrum sharing between vehicle-to-vehicle (V2V) and vehicle-to …
(IoV), focusing on spectrum sharing between vehicle-to-vehicle (V2V) and vehicle-to …
A power allocation scheme for MIMO-NOMA and D2D vehicular edge computing based on decentralized DRL
In vehicular edge computing (VEC), some tasks can be processed either locally or on the
mobile edge computing (MEC) server at a base station (BS) or a nearby vehicle. In fact …
mobile edge computing (MEC) server at a base station (BS) or a nearby vehicle. In fact …
Reconfigurable intelligent surface aided vehicular edge computing: Joint phase-shift optimization and multi-user power allocation
Vehicular edge computing (VEC) is an emerging technology with significant potential in the
field of Internet of Vehicles (IoV), enabling vehicles to perform intensive computational tasks …
field of Internet of Vehicles (IoV), enabling vehicles to perform intensive computational tasks …