Despite the basic premise that next-generation wireless networks (e.g., 6G) will be artificial intelligence (AI)-native, to date, most existing efforts remain either qualitative or incremental extensions to existing “AI for wireless” paradigms. Indeed, creating AI-native wireless networks faces significant technical challenges due to the limitations of data-driven, … [Read more...] about Causal Reasoning: Charting a Revolutionary Course for Next-Generation AI-Native Wireless Networks
Data models
When Connected and Automated Vehicles Meet Mobile Crowdsensing: A Perception and Transmission Framework in the Metaverse
The metaverse employs globally distributed computing and communication infrastructures to construct an immersive digital world. Its continuous synchronization and hyperinteractivity create a dilemma involving tremendous volumes of sensory data and scarce spectrum resources. Connected and automated vehicle (CAV) networks integrate onboard sensing, communication, computation, and … [Read more...] about When Connected and Automated Vehicles Meet Mobile Crowdsensing: A Perception and Transmission Framework in the Metaverse
How Does a Digital Twin Network Work Well for Connected and Automated Vehicles: Joint Perception, Planning, and Control
The cutting-edge technology of connected and automated vehicles (CAVs) will advance transportation systems for the foreseeable future. CAVs are expected to maintain fully automated judgment and manipulation without human intervention and, additionally, create safer driving and smarter traffic management. Digital twins (DTs) are the quiet but powerful forces enabling these new … [Read more...] about How Does a Digital Twin Network Work Well for Connected and Automated Vehicles: Joint Perception, Planning, and Control
Federated Learning-Assisted Vehicular Edge Computing: Architecture and Research Directions
Recently, realizing machine learning (ML)-based technologies with the aid of mobile edge computing (MEC) in the vehicular network to establish an intelligent transportation system (ITS) has gained considerable interest. To fully utilize the data and onboard units of vehicles, it is possible to implement federated learning (FL), which can locally train the model and centrally … [Read more...] about Federated Learning-Assisted Vehicular Edge Computing: Architecture and Research Directions
Artificial Intelligence-Assisted Network Slicing: Network Assurance and Service Provisioning in 6G
6G networks are expected to provide instant global connectivity and enable the transition from “connected things” to “connected intelligence,” where promising network slicing can play an important role in network assurance and service provisioning for various demanding vertical application scenarios. On the basis of diversified massive data, artificial intelligence … [Read more...] about Artificial Intelligence-Assisted Network Slicing: Network Assurance and Service Provisioning in 6G
