Pushing AI to wireless network edge: An overview on integrated sensing, communication, and computation towards 6G
Pushing artificial intelligence (AI) from central cloud to network edge has reached board
consensus in both industry and academia for materializing the vision of artificial intelligence …
consensus in both industry and academia for materializing the vision of artificial intelligence …
Deep learning-enabled semantic communication systems with task-unaware transmitter and dynamic data
H Zhang, S Shao, M Tao, X Bi… - IEEE Journal on …, 2022 - ieeexplore.ieee.org
Existing deep learning-enabled semantic communication systems often rely on shared
background knowledge between the transmitter and receiver that includes empirical data …
background knowledge between the transmitter and receiver that includes empirical data …
Task-oriented communications for 6G: Vision, principles, and technologies
Driven by the interplay among artificial intelligence, digital twin, and wireless networks, 6G is
envisaged to go beyond data-centric services to provide intelligent and immersive …
envisaged to go beyond data-centric services to provide intelligent and immersive …
Digital twin enhanced federated reinforcement learning with lightweight knowledge distillation in mobile networks
The high-speed mobile networks offer great potentials to many future intelligent applications,
such as autonomous vehicles in smart transportation systems. Such networks provide the …
such as autonomous vehicles in smart transportation systems. Such networks provide the …
Computation offloading and resource allocation in MEC-enabled integrated aerial-terrestrial vehicular networks: A reinforcement learning approach
As important services of the future sixth-generation (6G) wireless networks, vehicular
communication and mobile edge computing (MEC) have received considerable interest in …
communication and mobile edge computing (MEC) have received considerable interest in …
Trustworthy federated learning via blockchain
The safety-critical scenarios of artificial intelligence (AI), such as autonomous driving,
Internet of Things, smart healthcare, etc., have raised critical requirements of trustworthy AI …
Internet of Things, smart healthcare, etc., have raised critical requirements of trustworthy AI …
Machine learning for large-scale optimization in 6g wireless networks
The sixth generation (6G) wireless systems are envisioned to enable the paradigm shift from
“connected things” to “connected intelligence”, featured by ultra high density, large-scale …
“connected things” to “connected intelligence”, featured by ultra high density, large-scale …
Task offloading with multi-tier computing resources in next generation wireless networks
With the development of next-generation wireless networks, the Internet of Things (IoT) is
evolving towards the intelligent IoT (iIoT), where intelligent applications usually have …
evolving towards the intelligent IoT (iIoT), where intelligent applications usually have …
Task-oriented sensing, computation, and communication integration for multi-device edge AI
This paper studies a new multi-device edge artificial-intelligent (AI) system, which jointly
exploits the AI model split inference and integrated sensing and communication (ISAC) to …
exploits the AI model split inference and integrated sensing and communication (ISAC) to …
Graph neural networks for wireless communications: From theory to practice
Deep learning-based approaches have been developed to solve challenging problems in
wireless communications, leading to promising results. Early attempts adopted neural …
wireless communications, leading to promising results. Early attempts adopted neural …