Federated learning for intrusion detection system: Concepts, challenges and future directions
The rapid development of the Internet and smart devices trigger surge in network traffic
making its infrastructure more complex and heterogeneous. The predominated usage of …
making its infrastructure more complex and heterogeneous. The predominated usage of …
Comprehensive survey on machine learning in vehicular network: Technology, applications and challenges
Towards future intelligent vehicular network, the machine learning as the promising artificial
intelligence tool is widely researched to intelligentize communication and networking …
intelligence tool is widely researched to intelligentize communication and networking …
Future intelligent and secure vehicular network toward 6G: Machine-learning approaches
As a powerful tool, the vehicular network has been built to connect human communication
and transportation around the world for many years to come. However, with the rapid growth …
and transportation around the world for many years to come. However, with the rapid growth …
Data-driven deep learning for automatic modulation recognition in cognitive radios
Automatic modulation recognition (AMR) is an essential and challenging topic in the
development of the cognitive radio (CR), and it is a cornerstone of CR adaptive modulation …
development of the cognitive radio (CR), and it is a cornerstone of CR adaptive modulation …
Quantum machine learning for 6G communication networks: State-of-the-art and vision for the future
The upcoming fifth generation (5G) of wireless networks is expected to lay a foundation of
intelligent networks with the provision of some isolated artificial intelligence (AI) operations …
intelligent networks with the provision of some isolated artificial intelligence (AI) operations …
Survey on machine learning for intelligent end-to-end communication toward 6G: From network access, routing to traffic control and streaming adaption
The end-to-end quality of service (QoS) and quality of experience (QoE) guarantee is quite
important for network optimization. The current 5G and conceived 6G network in the future …
important for network optimization. The current 5G and conceived 6G network in the future …
Model-driven deep learning for physical layer communications
Intelligent communication is gradually becoming a mainstream direction. As a major branch
of machine learning, deep learning (DL) has been applied in physical layer communications …
of machine learning, deep learning (DL) has been applied in physical layer communications …
Deep reinforcement learning for dynamic uplink/downlink resource allocation in high mobility 5G HetNet
Recently, the 5G is widely deployed for supporting communications of high mobility nodes
including train, vehicular and unmanned aerial vehicles (UAVs) largely emerged as the …
including train, vehicular and unmanned aerial vehicles (UAVs) largely emerged as the …
Deep cognitive perspective: Resource allocation for NOMA-based heterogeneous IoT with imperfect SIC
The Internet of Things (IoT) has attracted significant attentions in the fifth generation mobile
networks and the smart cities. However, considering the large numbers of connectivity …
networks and the smart cities. However, considering the large numbers of connectivity …
Machine learning inspired sound-based amateur drone detection for public safety applications
MZ Anwar, Z Kaleem… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
In recent years, popularity of unmanned air vehicles enormously increased due to their
autonomous moving capability and applications in various domains. This also results in …
autonomous moving capability and applications in various domains. This also results in …