Biblio

The fifth-generation and beyond mobile networks should support extremely high and diversified requirements from a wide variety of emerging applications. It is envisioned that more advanced radio transmission, resource allocation, and networking techniques are required to be developed. Fulfilling these tasks is challenging since network infrastructure becomes increasingly complicated and heterogeneous. One promising solution is to leverage the great potential of Artificial Intelligence (AI) technology, which has been explored to provide solutions ranging from channel prediction to autonomous network management, as well as network security. As of today, however, the state of the art of integrating AI into wireless networks is mainly limited to use a dedicated AI algorithm to tackle a specific problem. A unified framework that can make full use of AI capability to solve a wide variety of network problems is still an open issue. Hence, this paper will present the concept of intelligence slicing where an AI module is instantiated and deployed on demand. Intelligence slices are applied to conduct different intelligent tasks with the flexibility of accommodating arbitrary AI algorithms. Two example slices, i.e., neural network based channel prediction and anomaly detection based industrial network security, are illustrated to demonstrate this framework.