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Context-aware multi-RAT connection with bi-level decision in 5G heterogeneous networks

In the upcoming 5G heterogeneous networks, connection of multiple radio access technologies (RATs) shows to be a crucial issue in achieving RAT multiplexing gain to meet the explosive traffic demand. In multi-RAT environments, users tend to activate parallel transmission across all available RATs for always best connection (ABC). However from a system-wide perspective, this might not be optimal given network context (network load and interference). Thus, an intelligent multi-RAT connection strategy is needed to determine how to use these access resources concurrently. This paper proposed a multi-RAT connection strategy with bi-level decision and integrated context awareness. Incorporating context information of both network side and user side, it makes double decisions on a) which exact RATs set to occupy, and b) which exact access point (AP) with each occupied RAT to access to. Ant colony algorithm (ACA) is used to search the optimal connection strategy for maximal system utility. Simulation results show that it's more reasonable to make multi-RAT connection decisions from a system-wide viewpoint. Compared to the connection strategies under guidance of max-SNR and ABC, the proposed method reduces network congestion and interference, and obtains more than 49% performance improvement.