Wi-Fi meets ML: A survey on improving IEEE 802.11 performance with machine learning
Wireless local area networks (WLANs) empowered by IEEE 802.11 (Wi-Fi) hold a dominant
position in providing Internet access thanks to their freedom of deployment and configuration …
position in providing Internet access thanks to their freedom of deployment and configuration …
[HTML][HTML] IRATS: A DRL-based intelligent priority and deadline-aware online resource allocation and task scheduling algorithm in a vehicular fog network
Cloud computing platforms support the Internet of Vehicles, but the main bottlenecks are
high latency and massive data transmission in cloud-based processing. Vehicular fog …
high latency and massive data transmission in cloud-based processing. Vehicular fog …
Multiagent reinforcement learning-based semi-persistent scheduling scheme in C-V2X mode 4
B Gu, W Chen, M Alazab, X Tan… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The Third Generation Partnership Project has standardized cellular vehicle-to-everything (C-
V2X) sidelink Mode 4 to support direct communication between vehicles. In Mode 4, the …
V2X) sidelink Mode 4 to support direct communication between vehicles. In Mode 4, the …
Radio resource allocation in 5G-NR V2X: a multi-agent actor-critic based approach
The efficiency of radio resource allocation and scheduling procedures in Cellular Vehicle-to-
X (Cellular V2X) communication networks directly affects link quality in terms of latency and …
X (Cellular V2X) communication networks directly affects link quality in terms of latency and …
Reinforcement learning-based approach for minimizing energy loss of driving platoon decisions
Z Gu, Z Liu, Q Wang, Q Mao, Z Shuai, Z Ma - Sensors, 2023 - mdpi.com
Reinforcement learning (RL) methods for energy saving and greening have recently
appeared in the field of autonomous driving. In inter-vehicle communication (IVC), a feasible …
appeared in the field of autonomous driving. In inter-vehicle communication (IVC), a feasible …
DAI-NET: Toward communication-aware collaborative training for the industrial edge
The industrial edge generates an abundance of spatially distributed and dynamic data that
needs to remain on-site for privacy and security reasons. Collaborative training at the edge …
needs to remain on-site for privacy and security reasons. Collaborative training at the edge …
AI/ML-based services and applications for 6G-connected and autonomous vehicles
AI and ML emerge as pivotal in overcoming the limitations of traditional network optimization
techniques and conventional control loop designs, particularly in addressing the challenges …
techniques and conventional control loop designs, particularly in addressing the challenges …
Coverage-Aware and Reinforcement Learning Using Multi-Agent Approach for HD Map QoS in a Realistic Environment
One effective way to optimize the offloading process is by minimizing the transmission time.
This is particularly true in a Vehicular Adhoc Network (VANET) where vehicles frequently …
This is particularly true in a Vehicular Adhoc Network (VANET) where vehicles frequently …
[HTML][HTML] Enhancing the Minimum Awareness Failure Distance in V2X Communications: A Deep Reinforcement Learning Approach
Vehicle-to-everything (V2X) communication is pivotal in enhancing cooperative awareness
in vehicular networks. Typically, awareness is viewed as a vehicle's ability to perceive and …
in vehicular networks. Typically, awareness is viewed as a vehicle's ability to perceive and …
Multi-agent Assessment with QoS Enhancement for HD Map Updates in a Vehicular Network and Multi-service Environment
Reinforcement Learning (RL) algorithms have been increasingly applied to tackle the
complex challenges of offloading in vehicular ad hoc networks (VANETs), particularly in high …
complex challenges of offloading in vehicular ad hoc networks (VANETs), particularly in high …