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 …
Reinforcement learning for intelligent healthcare systems: A review of challenges, applications, and open research issues
The rise of chronic disease patients and the pandemic pose immediate threats to healthcare
expenditure and mortality rates. This calls for transforming healthcare systems away from …
expenditure and mortality rates. This calls for transforming healthcare systems away from …
Multi-agent reinforcement learning for network selection and resource allocation in heterogeneous multi-RAT networks
The rapid production of mobile devices along with the wireless applications boom is
continuing to evolve daily. This motivates the exploitation of wireless spectrum using …
continuing to evolve daily. This motivates the exploitation of wireless spectrum using …
Toward QoS monitoring in IoT edge devices driven healthcare—a systematic literature review
Smart healthcare is altering the delivery of healthcare by combining the benefits of IoT,
mobile, and cloud computing. Cloud computing has tremendously helped the health industry …
mobile, and cloud computing. Cloud computing has tremendously helped the health industry …
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 …
Reinforcement learning for intelligent healthcare systems: A comprehensive survey
The rapid increase in the percentage of chronic disease patients along with the recent
pandemic pose immediate threats on healthcare expenditure and elevate causes of death …
pandemic pose immediate threats on healthcare expenditure and elevate causes of death …
Intelligent-slicing: An AI-assisted network slicing framework for 5G-and-beyond networks
AA Abdellatif, A Abo-Eleneen… - … on Network and …, 2023 - ieeexplore.ieee.org
5G-and-beyond networks are designed to fulfill the communication and computation
requirements of various industries, which requires not only transporting the data, but also …
requirements of various industries, which requires not only transporting the data, but also …
Exploiting multi-modal fusion for urban autonomous driving using latent deep reinforcement learning
Human driving decisions are the leading cause of road fatalities. Autonomous driving
naturally eliminates such incompetent decisions and thus can improve traffic safety and …
naturally eliminates such incompetent decisions and thus can improve traffic safety and …
Hierarchical multi-agent DRL-based framework for joint multi-RAT assignment and dynamic resource allocation in next-generation HetNets
This article considers the problem of cost-aware downlink sum-rate maximization via joint
optimal radio access technologies (RATs) assignment and power allocation in next …
optimal radio access technologies (RATs) assignment and power allocation in next …
Network selection based on evolutionary game and deep reinforcement learning in space-air-ground integrated network
K Fan, B Feng, X Zhang, Q Zhang - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
In next generation communication system, space-air-ground integrated network (SAGIN)
would be utilized to provide ubiquitous and unlimited wireless connectivity with large …
would be utilized to provide ubiquitous and unlimited wireless connectivity with large …