4 papers
Pruning-Aware Multi-Cluster Co-Inference for Large AI Models in AI-RANs
Xiaowen Cao, Zhonghao Lyu, Shicheng Chu +6
The increasing scale and computational demands of large artificial intelligence models (LAIMs) present significant challenges for efficient inference in resource-constrained distri…
Sense Smarter, Think Better: A Survey on Edge Perception for Next-Generation Networks
Zhonghao Lyu, Xiaowen Cao, Xianxin Song +11
Edge perception has emerged as a foundational capability for future wireless networks, enabling the network edge to proactively sense, interpret, and interact with the physical env…
Integrated Sensing, Communication, and Computation for Over-the-Air Federated Edge Learning
Dingzhu Wen, Sijing Xie, Xiaowen Cao +4
This paper studies an over-the-air federated edge learning (Air-FEEL) system with integrated sensing, communication, and computation (ISCC), in which one edge server coordinates mu…
Edge Perception: Intelligent Wireless Sensing at Network Edge
Yuanhao Cui, Xiaowen Cao, Guangxu Zhu +2
Future sixth-generation (6G) networks are envisioned to support intelligent applications across various vertical scenarios, which have stringent requirements on high-precision sens…