1 citations · 1 across the 6 of their papers we have counts for
6 papers
Semantic-Relevance Based Sensor Selection for Edge-AI Empowered Sensing Systems
Zhiyan Liu, Kaibin Huang
The sixth-generation (6G) mobile network is envisioned to incorporate sensing and edge artificial intelligence (AI) as two key functions. Their natural convergence leads to the eme…
Integrated Sensing and Edge AI: Realizing Intelligent Perception in 6G
Zhiyan Liu, Xu Chen, Hai Wu +4
Sensing and edge artificial intelligence (AI) are envisioned as two essential and interconnected functions in sixth-generation (6G) mobile networks. On the one hand, sensing-empowe…
Over-the-Air Fusion of Sparse Spatial Features for Integrated Sensing and Edge AI over Broadband Channels
Zhiyan Liu, Qiao Lan, Kaibin Huang
The 6G mobile networks feature two new usage scenarios -- distributed sensing and edge artificial intelligence (AI). Their natural integration, termed integrated sensing and edge A…
Over-the-Air Multi-View Pooling for Distributed Sensing
Zhiyan Liu, Qiao Lan, Anders E. Kalør +2
Sensing is envisioned as a key network function of the 6G mobile networks. Artificial intelligence (AI)-empowered sensing fuses features of multiple sensing views from devices dist…
Semantic Data Sourcing for 6G Edge Intelligence
Kaibin Huang, Qiao Lan, Zhiyan Liu +1
As a new function of 6G networks, edge intelligence refers to the ubiquitous deployment of machine learning and artificial intelligence (AI) algorithms at the network edge to empow…
In-situ Model Downloading to Realize Versatile Edge AI in 6G Mobile Networks
Kaibin Huang, Hai Wu, Zhiyan Liu +1
The sixth-generation (6G) mobile networks are expected to feature the ubiquitous deployment of machine learning and AI algorithms at the network edge. With rapid advancements in ed…