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 …

With recent advancements, the wireless local area network (WLAN) or wireless fidelity (Wi-
Fi) technology has been successfully utilized to realize sensing functionalities such as …

We study the collaborative image retrieval problem at the wireless edge, where multiple
edge devices capture images of the same object from different angles and locations, which …

Edge inference refers to the use of artificial intelligent (AI) models at the network edge to
provide mobile devices inference services and thereby enable intelligent services such as …

5G has expanded the traditional focus of wireless systems to embrace two new connectivity
types: ultra-reliable low latency and massive communication. The technology context at the …

Sensing is envisioned as a key network function of the sixth-generation (6G) mobile
networks. Artificial intelligence (AI)-empowered sensing fuses features of multiple sensing …

Artificial intelligence (AI) technologies, and particularly deep learning systems, are
traditionally the domain of large-scale cloud servers, which have access to high …

Sensing and edge artificial intelligence (AI) are two key features of the sixth-generation (6G)
mobile networks. Their natural integration, termed Integrated sensing and edge AI (ISEA), is …

Artificial intelligence (AI)-empowered sensing, a key function of 6G networks, fuses features
of multiple sensing views from distributed devices for the edge server to perform accurate …

In this paper, a cloud radio access network (Cloud-RAN) based collaborative edge AI
inference architecture is proposed. Specifically, geographically distributed devices capture …