FedSSC: Joint client selection and resource management for communication-efficient federated vehicular networks

S Liu, P Guan, J Yu, A Taherkordi - Computer Networks, 2023 - Elsevier
As a promising distributed technology, federated learning (FL) has been widely used in
vehicular networks involving large amounts of IoT-enabled sensor data, which derives …

Impact of dust and sand on 5G communications for connected vehicles applications

E Abuhdima, J Liu, C Zhao, A Elqaouaq… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
Recent research activities are focused on improving Vehicle-to-Vehicle Communication
(V2V) based on the 5G Technology. V2V applications are important because they are …

Robust, resilient and reliable architecture for v2x communications

MA Khan, S Ghosh, SA Busari, KMS Huq… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
The new developments in mobile edge computing (MEC) and vehicle-to-everything (V2X)
communications has positioned 5G and beyond in a strong position to answer the market …

MCLA task offloading framework for 5G-NR-V2X-based heterogeneous VECNs

MA Mirza, Y Junsheng, S Raza… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Ensuring dependable quality of service (QoS) and quality of experience (QoE) for
computation-intensive and delay-sensitive applications in vehicles can be a challenging …

MilliCar: An ns-3 module for mmWave NR V2X networks

M Drago, T Zugno, M Polese, M Giordani… - Proceedings of the 2020 …, 2020 - dl.acm.org
Vehicle-to-vehicle (V2V) communications have opened the way towards cooperative
automated driving as a means to guarantee improved road safety and traffic efficiency. The …

A comparative evaluation of propagation characteristics of vehicular VLC and MMW channels

F Aghaei, HB Eldeeb, M Uysal - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Vehicle-to-vehicle (V2V) communication is an underlying key technology to realize future
intelligent transportation systems. Both millimeter wave (MMW) communication and visible …

RFID: Towards low latency and reliable DAG task scheduling over dynamic vehicular clouds

Z Liu, M Liwang, S Hosseinalipour… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Vehicular cloud (VC) platforms integrate heterogeneous and distributed resources of moving
vehicles to offer timely and cost-effective computing services. However, the dynamic nature …

GA-DRL: Graph Neural Network-Augmented Deep Reinforcement Learning for DAG Task Scheduling over Dynamic Vehicular Clouds

Z Liu, L Huang, Z Gao, M Luo… - … on Network and …, 2024 - ieeexplore.ieee.org
Vehicular Clouds (VCs) are modern platforms for processing of computation-intensive tasks
over vehicles. Such tasks are often represented as Directed Acyclic Graphs (DAGs) …

Towards safe automated driving: Design of software-defined dynamic mmwave v2x networks and poc implementation

Z Li, T Yu, R Fukatsu, GK Tran… - IEEE Open Journal of …, 2021 - ieeexplore.ieee.org
The technical exploration of safe automated driving has evolved from single vehicle
intelligence to vehicular networking. Therefore, to a certain extent, the safety requirements …

Deep learning-based path loss prediction for fifth-generation new radio vehicle communications

S Sung, W Choi, H Kim, J Jung - IEEE Access, 2023 - ieeexplore.ieee.org
Fifth-generation (5G) technology is rapidly spreading to vehicle-to-vehicle (V2V)
communication, which requires high reliability, high data transmission rate, and low latency …