Edge learning for B5G networks with distributed signal processing: Semantic communication, edge computing, and wireless sensing

W Xu, Z Yang, DWK Ng, M Levorato… - IEEE journal of …, 2023 - ieeexplore.ieee.org
To process and transfer large amounts of data in emerging wireless services, it has become
increasingly appealing to exploit distributed data communication and learning. Specifically …

Security and Privacy on 6G Network Edge: A Survey

B Mao, J Liu, Y Wu, N Kato - IEEE Communications Surveys & …, 2023 - ieeexplore.ieee.org
To meet the stringent service requirements of 6G applications such as immersive cloud
eXtended Reality (XR), holographic communication, and digital twin, there is no doubt that …

Blockchain Meets Covert Communication: A Survey

Z Chen, L Zhu, P Jiang, C Zhang, F Gao… - … Surveys & Tutorials, 2022 - ieeexplore.ieee.org
Covert communication enables covert information transmission in an undetectable way to
prevent the exposure of communication behaviors. Blockchain-based covert communication …

Profit maximization for cache-enabled vehicular mobile edge computing networks

W Zhou, J Xia, F Zhou, L Fan, X Lei… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
In this paper, we investigate a multiuser cache-enabled vehicular mobile edge computing
(MEC) network, where one edge server (ES) has some caching and computing capabilities …

Blockchain-based federated learning for industrial metaverses: Incentive scheme with optimal aoi

J Kang, D Ye, J Nie, J Xiao, X Deng… - 2022 IEEE …, 2022 - ieeexplore.ieee.org
The emerging industrial metaverses realize the map-ping and expanding operations of
physical industry into virtual space for significantly upgrading intelligent manufacturing. The …

Unleashing the power of edge-cloud generative ai in mobile networks: A survey of aigc services

M Xu, H Du, D Niyato, J Kang, Z Xiong, S Mao… - arXiv preprint arXiv …, 2023 - arxiv.org
Artificial Intelligence-Generated Content (AIGC) is an automated method for generating,
manipulating, and modifying valuable and diverse data using AI algorithms creatively. This …

Compact Learning Model for Dynamic Off-Chain Routing in Blockchain-Based IoT

Z Li, W Su, M Xu, R Yu, D Niyato… - IEEE Journal on Selected …, 2022 - ieeexplore.ieee.org
Dynamic off-chain routing in payment channel network (PCN)-based Internet of Things (IoT)
is attracting increasing research attention. However, there are two major issues in dynamic …

FedRelay: Federated Relay Learning for 6G Mobile Edge Intelligence

P Li, Y Zhong, C Zhang, Y Wu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Federated learning (FL) is a promising training paradigm to achieve ubiquitous intelligence
for future 6 G communication systems. However, it is challenging to apply FL in 6G-enabled …

Privacy-preserving Intelligent Resource Allocation for Federated Edge Learning in Quantum Internet

M Xu, D Niyato, Z Yang, Z Xiong, J Kang… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
Federated edge learning (FEL) is a promising paradigm of distributed machine learning that
can preserve data privacy while training the global model collaboratively. However, FEL is …

AI-driven Packet Forwarding with Programmable Data Plane: A Survey

W Quan, Z Xu, M Liu, N Cheng, G Liu… - … Surveys & Tutorials, 2022 - ieeexplore.ieee.org
The existing packet forwarding technology cannot meet the increasing requirements of
Internet development due to its rigid framework. Application of artificial intelligence (AI) for …