Graph neural networks and deep reinforcement learning based resource allocation for v2x communications

M Ji, Q Wu, P Fan, N Cheng, W Chen… - IEEE Internet of …, 2024 - ieeexplore.ieee.org
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 …

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 …

URLLC-awared resource allocation for heterogeneous vehicular edge computing

Q Wu, W Wang, P Fan, Q Fan, J Wang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
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 …

Secure transmission scheme based on joint radar and communication in mobile vehicular networks

Y Yao, F Shu, Z Li, X Cheng… - IEEE transactions on …, 2023 - ieeexplore.ieee.org
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 …

Delay-sensitive task offloading in vehicular fog computing-assisted platoons

Q Wu, S Wang, H Ge, P Fan, Q Fan… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
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 …

Distributed deep reinforcement learning based gradient quantization for federated learning enabled vehicle edge computing

C Zhang, W Zhang, Q Wu, P Fan, Q Fan… - IEEE Internet of …, 2024 - ieeexplore.ieee.org
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 …

Cooperative edge caching based on elastic federated and multi-agent deep reinforcement learning in next-generation networks

Q Wu, W Wang, P Fan, Q Fan, H Zhu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
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' …

Semantic-aware spectrum sharing in internet of vehicles based on deep reinforcement learning

Z Shao, Q Wu, P Fan, N Cheng, W Chen… - IEEE Internet of …, 2024 - ieeexplore.ieee.org
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 …

A power allocation scheme for MIMO-NOMA and D2D vehicular edge computing based on decentralized DRL

D Long, Q Wu, Q Fan, P Fan, Z Li, J Fan - Sensors, 2023 - mdpi.com
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 …

Reconfigurable intelligent surface aided vehicular edge computing: Joint phase-shift optimization and multi-user power allocation

K Qi, Q Wu, P Fan, N Cheng, W Chen… - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
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 …