An Adaptive and Distributed Network Selection Mechanism for 5G Networks

Abstract 5G networks aim to support a vast amount of data exchange, through network densification, including the integration of multiple radio access technologies (RATs) under a unified radio access and core network. This integration creates a heterogeneous environment where end devices dynamically select the most suitable RAT for consuming a service via a new or even an ongoing communication session. This paper proposes a distributed and adaptive network selection mechanism to address this challenge. The proposed mechanism comprises two co-operating algorithms, one located at the user equipment (UE), and the other at the core network. Its main objective is to satisfy user preferences regarding monetary cost, quality of service, security, energy consumption etc., while safeguarding an operator's traffic engineering policy to avoid congestion. A key feature of the mechanism is the use of a dynamic threshold used to find the sweet spot between a well-balanced access network and maximizing the number of user sessions placed into their most preferred RAT. This threshold is adjusted in real time according to the experienced network conditions. Extensive network performance and quality of experience simulations show that the proposed mechanism accomplishes its objectives and can be used to provide efficient traffic steering decisions.