Multi-connectivity as an enabler for reliable low latency communications—An overview
MT Suer, C Thein, H Tchouankem… - … Surveys & Tutorials, 2019 - ieeexplore.ieee.org
Emerging applications such as wireless industrial control or vehicular communications pose
strict requirements in terms of latency and reliability on wireless communication systems …
strict requirements in terms of latency and reliability on wireless communication systems …
Intelligent massive MIMO systems for beyond 5G networks: An overview and future trends
Machine learning (ML) which is a subset of artificial intelligence is expected to unlock the
potential of challenging large-scale problems in conventional massive multiple-input …
potential of challenging large-scale problems in conventional massive multiple-input …
Multi-agent DRL for task offloading and resource allocation in multi-UAV enabled IoT edge network
The Internet of Things (IoT) edge network has connected lots of heterogeneous smart
devices, thanks to unmanned aerial vehicles (UAVs) and their groundbreaking emerging …
devices, thanks to unmanned aerial vehicles (UAVs) and their groundbreaking emerging …
Effective prediction and resource allocation method (EPRAM) in fog computing environment for smart healthcare system
FM Talaat - Multimedia Tools and Applications, 2022 - Springer
Recently, many concepts in technology has been changed. According to the digital
transformation trends, Internet of Things (IoT) represents an interested research issue. As …
transformation trends, Internet of Things (IoT) represents an interested research issue. As …
A load balancing and optimization strategy (LBOS) using reinforcement learning in fog computing environment
Fog computing (FC) can be considered as a computing paradigm which performs Internet of
Things (IoT) applications at the edge of the network. Recently, there is a great growth of data …
Things (IoT) applications at the edge of the network. Recently, there is a great growth of data …
Reinforcement learning for adaptive resource allocation in fog RAN for IoT with heterogeneous latency requirements
In light of the quick proliferation of Internet of things (IoT) devices and applications, fog radio
access network (Fog-RAN) has been recently proposed for fifth generation (5G) wireless …
access network (Fog-RAN) has been recently proposed for fifth generation (5G) wireless …
An overview of intelligent wireless communications using deep reinforcement learning
Future wireless communication networks tend to be intelligentized to accomplish the
missions that cannot be preprogrammed. In the new intelligent communication systems …
missions that cannot be preprogrammed. In the new intelligent communication systems …
Learning based mobility management under uncertainties for mobile edge computing
Mobile edge computing (MEC) offloads computation-intensive applications and overcomes
the long latency by pushing data traffic towards the network edges. With base stations (BSs) …
the long latency by pushing data traffic towards the network edges. With base stations (BSs) …
Reinforcement learning-based dynamic band and channel selection in cognitive radio ad-hoc networks
In cognitive radio (CR) ad-hoc network, the characteristics of the frequency resources that
vary with the time and geographical location need to be considered in order to efficiently use …
vary with the time and geographical location need to be considered in order to efficiently use …
Reinforcement learning-based user scheduling and resource allocation for massive MU-MIMO system
G Bu, J Jiang - 2019 IEEE/CIC International Conference on …, 2019 - ieeexplore.ieee.org
User Scheduling and resource allocation in massive multi-user multiple-input multiple-
output (MU-MIMO) systems can be regarded as a multi-objective optimization problem from …
output (MU-MIMO) systems can be regarded as a multi-objective optimization problem from …