With the increasing demand for intelligent services, the sixth-generation (6G) wireless
networks will shift from a traditional architecture that focuses solely on a high transmission …

In this tutorial paper, we look into the evolution and prospect of network architecture and
propose a novel conceptual architecture for the 6th generation (6G) networks. The proposed …

Artificial Intelligence-Generated Content (AIGC) is an automated method for generating,
manipulating, and modifying valuable and diverse data using AI algorithms creatively. This …

Split learning (SL) is a collaborative learning framework, which can train an artificial
intelligence (AI) model between a device and an edge server by splitting the AI model into a …

Incentive plays an important role in knowledge discovery, as it impels users to provide high-
quality knowledge. To promise incentive schemes with transparency, blockchain technology …

Federated learning (FL) is a popular edge learning approach that utilizes local data and
computing resources of network edge devices to train machine learning (ML) models while …

Extremely large-scale multiple-input-multiple-output (XL-MIMO), which offers vast spatial
degrees of freedom, has emerged as a potentially pivotal enabling technology for the sixth …

Conventional machine learning approaches aggregate all training data in a central server,
which causes massive communication overhead of data transmission and is also vulnerable …

With the gradual popularization of self-driving, it is becoming increasingly important for
vehicles to smartly make the right driving decisions and autonomously obey traffic rules by …

In this paper, we present a three-layer (ie, device, field, and factory layers) deterministic
federated learning (FL) framework, named DetFed, which accelerates collaborative learning …