Toward an Automated Data Offloading Framework for Multi-RAT 5G Wireless Networks

Offloading among multiple radio access technologies (RATs) is an effective solution to tackle some of the key challenges faced by 5G wireless networks. While making an offloading decision, in user-centric offloading schemes, the network context is not taken into account, which limits the full utilization of the potential offered by these techniques. Therefore, in this work, we develop a data offloading framework wherein a user defines a tuple, which includes a request for data service and the associated delay limit, and the user equipment (UE) translates this tuple into an optimal offloading policy by taking into account the network context. The data offloading problem is formulated by assuming a finite horizon Markov decision process (MDP), and an analytical data offloading model is derived by using stochastic geometry for modeling the spatial domain of a multi-RAT wireless network, and by employing Markov process for capturing mobility of users. In order to validate the performance of derived model, we also solve the offloading problem by using policy iteration (PI) algorithm. The results show that the analytical algorithm outperforms the iterative algorithm. We also benchmark the proposed framework against standard data offloading methods.