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 for wireless communications in the Internet of Things: A comprehensive survey
Abstract The Internet of Things (IoT) is expected to require more effective and efficient
wireless communications than ever before. For this reason, techniques such as spectrum …
wireless communications than ever before. For this reason, techniques such as spectrum …
Knowledge-driven service offloading decision for vehicular edge computing: A deep reinforcement learning approach
The smart vehicles construct Internet of Vehicle (IoV), which can execute various intelligent
services. Although the computation capability of a vehicle is limited, multi-type of edge …
services. Although the computation capability of a vehicle is limited, multi-type of edge …
An intelligent traffic load prediction-based adaptive channel assignment algorithm in SDN-IoT: A deep learning approach
Due to the fast increase of sensing data and quick response requirement in the Internet of
Things (IoT) delivery network, the high speed transmission has emerged as an important …
Things (IoT) delivery network, the high speed transmission has emerged as an important …
A deep reinforcement learning-based dynamic traffic offloading in space-air-ground integrated networks (SAGIN)
Space-Air-Ground Integrated Networks (SAGIN) is considered as the key structure of the
next generation network. The space satellites and air nodes are the potential candidates to …
next generation network. The space satellites and air nodes are the potential candidates to …
On removing routing protocol from future wireless networks: A real-time deep learning approach for intelligent traffic control
Recently, deep learning has appeared as a breakthrough machine learning technique for
various areas in computer science as well as other disciplines. However, the application of …
various areas in computer science as well as other disciplines. However, the application of …
Towards artificial intelligence enabled 6G: State of the art, challenges, and opportunities
S Zhang, D Zhu - Computer Networks, 2020 - Elsevier
Abstract 6G is expected to support the unprecedented Internet of everything scenarios with
extremely diverse and challenging requirements. To fulfill such diverse requirements …
extremely diverse and challenging requirements. To fulfill such diverse requirements …
Energy-efficient UAV routing for wireless sensor networks
Recently, an unmanned aerial vehicle (UAV) has been widely adopted to make efficient use
of network resources in such areas as internet of things (IoT), sensor networks and three …
of network resources in such areas as internet of things (IoT), sensor networks and three …
Intelligent routing based on reinforcement learning for software-defined networking
DM Casas-Velasco, OMC Rendon… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Traditional routing protocols employ limited information to make routing decisions, which
can lead to a slow adaptation to traffic variability, as well as restricted support to the Quality …
can lead to a slow adaptation to traffic variability, as well as restricted support to the Quality …
Internet of intelligence: A survey on the enabling technologies, applications, and challenges
The Internet of Intelligence is conceived as an emerging networking paradigm, which will
make intelligence as easy to obtain as information. This paper provides an overview of the …
make intelligence as easy to obtain as information. This paper provides an overview of the …