Joint resource management for MC-NOMA: A deep reinforcement learning approach
This paper presents a novel and effective deep reinforcement learning (DRL)-based
approach to addressing joint resource management (JRM) in a practical multi-carrier non …
approach to addressing joint resource management (JRM) in a practical multi-carrier non …
Artificial intelligence enabled Internet of Things: Network architecture and spectrum access
The explosive growth of wireless devices motivates the development of the internet-of-things
(IoT), which is capable of interconnecting massive and diverse" things" via wireless …
(IoT), which is capable of interconnecting massive and diverse" things" via wireless …
Deep reinforcement learning based mobile edge computing for intelligent Internet of Things
R Zhao, X Wang, J Xia, L Fan - Physical Communication, 2020 - Elsevier
In this paper, we investigate mobile edge computing (MEC) networks for intelligent internet
of things (IoT), where multiple users have some computational tasks assisted by multiple …
of things (IoT), where multiple users have some computational tasks assisted by multiple …
Recent advances in artificial intelligence for wireless internet of things and cyber–physical systems: A comprehensive survey
BA Salau, A Rawal, DB Rawat - IEEE Internet of Things Journal, 2022 - ieeexplore.ieee.org
Advances in artificial intelligence (AI) and wireless technology are driving forward the large
deployment of interconnected smart technologies that constitute cyber–physical systems …
deployment of interconnected smart technologies that constitute cyber–physical systems …
A decoupled learning strategy for massive access optimization in cellular IoT networks
Cellular-based networks are expected to offer connectivity for massive Internet of Things
(mIoT) systems. However, their Random Access CHannel (RACH) procedure suffers from …
(mIoT) systems. However, their Random Access CHannel (RACH) procedure suffers from …
Intelligent resource management at the edge for ubiquitous IoT: An SDN-based federated learning approach
The ubiquitous nature of Internet of Things (IoT) devices has posited many challenges that
need innovative solutions in the 5G era. Software defined networks (SDNs) are becoming …
need innovative solutions in the 5G era. Software defined networks (SDNs) are becoming …
A comprehensive survey on 6G networks: Applications, core services, enabling technologies, and future challenges
Cellular Internet of Things (IoT) is considered as de facto paradigm to improve the
communication and computation systems. Cellular IoT connects massive number of physical …
communication and computation systems. Cellular IoT connects massive number of physical …
Intelligent offloading and resource allocation in heterogeneous aerial access IoT networks
Aerial access networks, comprising a hierarchical model of high-altitude platforms (HAPs)
and multiple unmanned aerial vehicles (UAVs), are considered a promising technology to …
and multiple unmanned aerial vehicles (UAVs), are considered a promising technology to …
A hybrid approach for latency and battery lifetime optimization in IoT devices through offloading and CNN learning
Offloading assists in overcoming the resource constraints of specific elements, making it one
of the primary technical enablers of the Internet of Things (IoT). IoT devices with low battery …
of the primary technical enablers of the Internet of Things (IoT). IoT devices with low battery …
Machine learning in the Internet of Things: Designed techniques for smart cities
Abstract Machine learning is one of the emerging technologies that has grabbed the
attention of academicians and industrialists, and is expected to evolve in the near future …
attention of academicians and industrialists, and is expected to evolve in the near future …