Context-oriented multi-RAT user association and resource allocation with triple decision in 5G heterogeneous networks

In the upcoming 5G heterogeneous networks, leveraging multiple radio access technologies (RATs) shows to be a crucial issue in achieving RAT multiplexing gain to meet the explosive traffic demand. For always best connection (ABC), users tend to activate parallel transmission across all available RATs. However from a system-wide perspective, this might not be optimal given the context of network load, interference and diverse service requirements. To intelligently determine how to use these multi-RAT access resources concurrently, this paper proposes a joint multi-RAT user association and resource allocation strategy with triple decision and integrated context awareness of users and networks. A dynamic game based ant colony algorithm (GACA) is designed to simultaneously maximize the system utility and the fairness of resource allocation. Simulation results show that it’s more reasonable to make multi-RAT association decision from a system-wide view-point than from an individual one. Compared to max-SNR based and ABC based strategies, the proposed method alleviates network congestion and optimizes resource allocation. It obtains 39%~70% performance improvement.