A SON decision-making framework for intelligent management in 5G mobile networks

The 5th Generation (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.

[1]  Christian Bonnet,et al.  OpenAirInterface: A Flexible Platform for 5G Research , 2014, CCRV.

[2]  Jose M. Alcaraz Calero,et al.  The SELFNET Approach for Autonomic Management in an NFV/SDN Networking Paradigm , 2016, Int. J. Distributed Sens. Networks.

[3]  Raquel Barco,et al.  Optimization of load balancing using fuzzy Q-Learning for next generation wireless networks , 2013, Expert Syst. Appl..

[4]  Vincenzo Sciancalepore,et al.  From network sharing to multi-tenancy: The 5G network slice broker , 2016, IEEE Communications Magazine.

[5]  Muhammad Ali Imran,et al.  Controlling self healing cellular networks using fuzzy logic , 2012, 2012 IEEE Wireless Communications and Networking Conference (WCNC).

[6]  Honggang Zhang,et al.  Network slicing as a service: enabling enterprises' own software-defined cellular networks , 2016, IEEE Communications Magazine.

[7]  Wei Jiang,et al.  Intelligent network management for 5G systems: The SELFNET approach , 2017, 2017 European Conference on Networks and Communications (EuCNC).

[8]  Wei Jiang,et al.  Experimental results for artificial intelligence-based self-organized 5G networks , 2017, 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC).