VHetNets for AI and AI for VHetNets: An Anomaly Detection Case Study for Ubiquitous IoT

Vertical heterogeneous networks (VHetNets) and artificial intelligence (AI) play critical roles in 6G and beyond networks. This article presents an AI-native VHetNets architecture to enable the synergy of VHetNets and AI, thereby supporting varieties of AI services while facilitating the intelligent network management. Anomaly detection stands as an essential AI service across various applications in Internet of Things (IoT), including intrusion detection, state monitoring, analysis of device activities, and security supervision. In this article, we first discuss the possibilities of VHetNets used for distributed AI model training to provide the anomaly detection service for ubiquitous IoT, i.e., VHetNets for AI. After that, we study the application of AI approaches in helping implement the intelligent network management functionalities for VHetNets, i.e., AI for VHetNets, whose aim is to facilitate the efficient implementation of the anomaly detection service. Finally, a case study is presented to demonstrate the efficiency and effectiveness of the proposed AInative VHetNets-enabled anomaly detection framework.