AI models for green communications towards 6G

B Mao, F Tang, Y Kawamoto… - … Surveys & Tutorials, 2021 - ieeexplore.ieee.org
Green communications have always been a target for the information industry to alleviate
energy overhead and reduce fossil fuel usage. In the current 5G and future 6G eras, there is …

Vehicular edge computing and networking: A survey

L Liu, C Chen, Q Pei, S Maharjan, Y Zhang - Mobile networks and …, 2021 - Springer
As one key enabler of Intelligent Transportation System (ITS), Vehicular Ad Hoc Network
(VANET) has received remarkable interest from academia and industry. The emerging …

Wireless networked multirobot systems in smart factories

KC Chen, SC Lin, JH Hsiao, CH Liu… - Proceedings of the …, 2020 - ieeexplore.ieee.org
Smart manufacturing based on artificial intelligence and information communication
technology will become the main contributor to the digital economy of the upcoming …

Reinforcement learning-empowered mobile edge computing for 6G edge intelligence

P Wei, K Guo, Y Li, J Wang, W Feng, S Jin, N Ge… - Ieee …, 2022 - ieeexplore.ieee.org
Mobile edge computing (MEC) is considered a novel paradigm for computation-intensive
and delay-sensitive tasks in fifth generation (5G) networks and beyond. However, its …

Popularity-aware online task offloading for heterogeneous vehicular edge computing using contextual clustering of bandits

Y Lin, Y Zhang, J Li, F Shu, C Li - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
Vehicular edge computing (VEC) has become a promising enabler for ultrareliable and low-
latency communications (URLLC) vehicular networks by providing computational resources …

Minimum Latency‐Secure Key Transmission for Cloud‐Based Internet of Vehicles Using Reinforcement Learning

V Akilandeswari, A Kumar… - Computational …, 2022 - Wiley Online Library
The Internet of Vehicles (IoV) communication key management level controls the
confidentiality and security of its data, which may withstand user identity‐based attacks such …

[HTML][HTML] Task offloading for edge-IoV networks in the industry 4.0 era and beyond: A high-level view

M Talebkhah, A Sali, V Khodamoradi… - … Science and Technology …, 2024 - Elsevier
As a promising platform on the Internet of Things (IoT), the smart Internet of Vehicle (IoV) has
emerged with the advent of the key connectivity to Industry 4.0, ie Fifth-Generation Mobile …

[HTML][HTML] Multi-agent reinforcement learning for edge information sharing in vehicular networks

R Wang, X Jiang, Y Zhou, Z Li, D Wu, T Tang… - Digital Communications …, 2022 - Elsevier
To guarantee the heterogeneous delay requirements of the diverse vehicular services, it is
necessary to design a full cooperative policy for both Vehicle to Infrastructure (V2I) and …

Multi-Timescale Control and Communications With Deep Reinforcement Learning—Part I: Communication-Aware Vehicle Control

T Liu, L Lei, K Zheng, X Shen - IEEE Internet of Things Journal, 2023 - ieeexplore.ieee.org
An intelligent decision-making system enabled by vehicle-to-everything (V2X)
communications is essential to achieve safe and efficient autonomous driving (AD), where …

Latency-optimal mmWave radio access for V2X supporting next generation driving use cases

SY Lien, YC Kuo, DJ Deng, HL Tsai, A Vinel… - IEEE …, 2018 - ieeexplore.ieee.org
With the facilitation of the fifth generation new radio, vehicle-to-everything applications have
entered a brand new era to sustain the next generation driving use cases of advanced …