A SON decision-making framework for intelligent management in 5G mobile networks
Wei Jiang, Mathias Strufe, Hans Dieter Schotten · 2017
The 5thGeneration (5G) mobile system is envisioned to become more complicated and heterogeneous to meet the radical Key Performance Indicators specified in ITU-R IMT-2020. It imposes a great challenge on today's manual and semi-automated network management in 3G/4G systems. Taking advantage of cutting-edge technologies in the area of Artificial Intelligence and Self-Organized Network (SON), the concept of intelligent network management provides an effective solution and therefore attracts the attention of 5G research community. In this paper, a SON decision-making framework is proposed to provide a possible method to realize intelligent management for the upcoming 5G networks. Two complementary decision-making approaches, namely Rule-based and Machine Learning-based intelligence, their interactions, and lifecycle management of intelligence slices are presented. Moreover, the setup of a wireless network test-bed, as well as some experimental results to verify the effectiveness of the proposed framework, are illustrated.