AI for UAV-assisted IoT applications: A comprehensive review
With the rapid development of the Internet of Things (IoT), there are a dramatically
increasing number of devices, leading to the fact that only using terrestrial infrastructure can …
increasing number of devices, leading to the fact that only using terrestrial infrastructure can …
The frontiers of deep reinforcement learning for resource management in future wireless HetNets: Techniques, challenges, and research directions
Next generation wireless networks are expected to be extremely complex due to their
massive heterogeneity in terms of the types of network architectures they incorporate, the …
massive heterogeneity in terms of the types of network architectures they incorporate, the …
Flight delay prediction based on aviation big data and machine learning
Accurate flight delay prediction is fundamental to establish the more efficient airline
business. Recent studies have been focused on applying machine learning methods to …
business. Recent studies have been focused on applying machine learning methods to …
UAV-enhanced intelligent offloading for Internet of Things at the edge
With the explosive growth of diverse Internet of Things (IoT) applications, mobile edge
computing (MEC) has been brought to settle the conflict between computation-intensive …
computing (MEC) has been brought to settle the conflict between computation-intensive …
Resource allocation and trajectory design for MISO UAV-assisted MEC networks
Mobile Edge Computing (MEC) is a promising technology in the next generation network,
which provides computing services for user equipments (UEs) to reduce the task delay and …
which provides computing services for user equipments (UEs) to reduce the task delay and …
Beyond D2D: Full dimension UAV-to-everything communications in 6G
In this paper, we consider an Internet of unmanned aerial vehicles (UAVs) over cellular
networks, where UAVs work as aerial users to collect various sensory data, and send the …
networks, where UAVs work as aerial users to collect various sensory data, and send the …
Dynamic clustering in federated learning
In the resource management of wireless networks, Federated Learning has been used to
predict handovers. However, non-independent and identically distributed data degrade the …
predict handovers. However, non-independent and identically distributed data degrade the …
Resource management in UAV-assisted wireless networks: An optimization perspective
Wireless networks are expected to provide connectivity to an increasing number of users
with heterogeneous requirements. Future wireless networks will integrate aerial and …
with heterogeneous requirements. Future wireless networks will integrate aerial and …
A secure flexible and tampering-resistant data sharing system for vehicular social networks
Vehicular social networks (VSNs) have emerged as the promising paradigm of vehicular
networks that can improve traffic safety, relieve traffic congestion and even provide …
networks that can improve traffic safety, relieve traffic congestion and even provide …
Deep reinforcement learning for radio resource allocation and management in next generation heterogeneous wireless networks: A survey
Next generation wireless networks are expected to be extremely complex due to their
massive heterogeneity in terms of the types of network architectures they incorporate, the …
massive heterogeneity in terms of the types of network architectures they incorporate, the …