Machine learning-aided operations and communications of unmanned aerial vehicles: A contemporary survey
Over the past decade, Unmanned Aerial Vehicles (UAVs) have provided pervasive, efficient,
and cost-effective solutions for data collection and communications. Their excellent mobility …
and cost-effective solutions for data collection and communications. Their excellent mobility …
Multi-agent reinforcement learning based resource management in MEC-and UAV-assisted vehicular networks
In this paper, we investigate multi-dimensional resource management for unmanned aerial
vehicles (UAVs) assisted vehicular networks. To efficiently provide on-demand resource …
vehicles (UAVs) assisted vehicular networks. To efficiently provide on-demand resource …
[HTML][HTML] Role of machine learning in resource allocation strategy over vehicular networks: a survey
I Nurcahyani, JW Lee - Sensors, 2021 - mdpi.com
The increasing demand for smart vehicles with many sensing capabilities will escalate data
traffic in vehicular networks. Meanwhile, available network resources are limited. The …
traffic in vehicular networks. Meanwhile, available network resources are limited. The …
Deep reinforcement learning-based energy-efficient edge computing for internet of vehicles
Mobile network operators (MNOs) allocate computing and caching resources for mobile
users by deploying a central control system. Existing studies mainly use programming and …
users by deploying a central control system. Existing studies mainly use programming and …
Learning based channel allocation and task offloading in temporary UAV-assisted vehicular edge computing networks
C Yang, B Liu, H Li, B Li, K Xie… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
High-level autonomous decision making system is one of the key technologies in intelligent
transportation networks, it requires the traffic information within a certain range of vehicles in …
transportation networks, it requires the traffic information within a certain range of vehicles in …
Delay optimization in mobile edge computing: Cognitive UAV-assisted eMBB and mMTC services
Mobile edge computing (MEC) in cognitive radio networks is an optimistic technique for
improving the computational capability and spectrum utilization efficiency. In this study, we …
improving the computational capability and spectrum utilization efficiency. In this study, we …
DRL‐based intelligent resource allocation for diverse QoS in 5G and toward 6G vehicular networks: a comprehensive survey
The vehicular network is taking great attention from both academia and industry to enable
the intelligent transportation system (ITS), autonomous driving, and smart cities. The system …
the intelligent transportation system (ITS), autonomous driving, and smart cities. The system …
5G deployment models and configuration choices for industrial cyber-physical systems–A state of art overview
The digital transformation of Industry 4.0 is driven by the automation of manufacturing
processes. In this context, communication plays a vital role and the emergence of 5G …
processes. In this context, communication plays a vital role and the emergence of 5G …
[HTML][HTML] Game-theoretic physical layer authentication for spoofing detection in internet of things
Y Wu, T Jing, Q Gao, Y Wu, Y Huo - Digital Communications and Networks, 2023 - Elsevier
Abstract The Internet of Things (IoT) has permeated various fields relevant to our lives. In
these applications, countless IoT devices transmit vast amounts of data, which often carry …
these applications, countless IoT devices transmit vast amounts of data, which often carry …
Towards uav-based mec service chain resilience evaluation: A quantitative modeling approach
J Bai, X Chang, RJ Rodríguez… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Unmanned aerial vehicle (UAV) and network function virtualization (NFV) facilitate the
deployment of multi-access edge computing (MEC). In the UAV-based MEC (UMEC) …
deployment of multi-access edge computing (MEC). In the UAV-based MEC (UMEC) …