On the road to 6G: Visions, requirements, key technologies, and testbeds

CX Wang, X You, X Gao, X Zhu, Z Li… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
Fifth generation (5G) mobile communication systems have entered the stage of commercial
deployment, providing users with new services, improved user experiences as well as a host …

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 **ong… - … Surveys & Tutorials, 2024 - ieeexplore.ieee.org
Artificial Intelligence-Generated Content (AIGC) is an automated method for generating,
manipulating, and modifying valuable and diverse data using AI algorithms creatively. This …

A full dive into realizing the edge-enabled metaverse: Visions, enabling technologies, and challenges

M Xu, WC Ng, WYB Lim, J Kang, Z **ong… - … Surveys & Tutorials, 2022 - ieeexplore.ieee.org
Dubbed “the successor to the mobile Internet,” the concept of the Metaverse has grown in
popularity. While there exist lite versions of the Metaverse today, they are still far from …

Split learning over wireless networks: Parallel design and resource management

W Wu, M Li, K Qu, C Zhou, X Shen… - IEEE Journal on …, 2023 - ieeexplore.ieee.org
Split learning (SL) is a collaborative learning framework, which can train an artificial
intelligence (AI) model between a device and an edge server by splitting the AI model into a …

AI-native network slicing for 6G networks

W Wu, C Zhou, M Li, H Wu, H Zhou… - IEEE Wireless …, 2022 - ieeexplore.ieee.org
With the global rollout of fifth generation (5G) networks, it is necessary to look beyond 5G
and envision 6G networks. 6G networks are expected to have space-air-ground integrated …

Combining federated learning and edge computing toward ubiquitous intelligence in 6G network: Challenges, recent advances, and future directions

Q Duan, J Huang, S Hu, R Deng… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
Full leverage of the huge volume of data generated on a large number of user devices for
providing intelligent services in the 6G network calls for Ubiquitous Intelligence (UI). A key to …

Pushing AI to wireless network edge: An overview on integrated sensing, communication, and computation towards 6G

G Zhu, Z Lyu, X Jiao, P Liu, M Chen, J Xu, S Cui… - Science China …, 2023 - Springer
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 …

DetFed: Dynamic resource scheduling for deterministic federated learning over time-sensitive networks

D Yang, W Zhang, Q Ye, C Zhang… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
In this paper, we present a three-layer (ie, device, field, and factory layers) deterministic
federated learning (FL) framework, named DetFed, which accelerates collaborative learning …

Llm-based edge intelligence: A comprehensive survey on architectures, applications, security and trustworthiness

O Friha, MA Ferrag, B Kantarci… - IEEE Open Journal …, 2024 - ieeexplore.ieee.org
The integration of Large Language Models (LLMs) and Edge Intelligence (EI) introduces a
groundbreaking paradigm for intelligent edge devices. With their capacity for human-like …

QoE fairness resource allocation in digital twin-enabled wireless virtual reality systems

J Feng, L Liu, X Hou, Q Pei, C Wu - IEEE journal on selected …, 2023 - ieeexplore.ieee.org
Wireless virtual reality (VR) is expected to be a technology that revolutionizes human
interaction and perceived media, where the quality of experience (QoE) is an important …