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 …

This paper studies a new multi-device edge artificial-intelligent (AI) system, which jointly
exploits the AI model split inference and integrated sensing and communication (ISAC) to …

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 …

In this paper, we consider deploying multiple unmanned aerial vehicles (UAVs) to provide
integrated sensing, communication, and computation (ISCC) services. During serving …

We consider distributed inference at the wireless edge, where multiple clients with an
ensemble of models, each trained independently on a local dataset, are queried in parallel …

Split AI inference partitions an artificial intelligence (AI) model into multiple parts, enabling
the offloading of computation-intensive AI services. Resource allocation is critical for the …

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

A task-oriented over-the-air computation (AirComp) scheme is proposed in this paper for
multi-device edge split inference system. In the considered system, local noise-corrupted …

Incorporating both semantic level information and effectiveness level performance, the task-
oriented semantic communication system has been designed for various tasks of different …

Cellular networks are evolving from connected everything in fifth-generation (5G) to a new
paradigm of connected intelligence in sixth-generation (6G). Towards this end, intelligent …