Joint Optimization of User Association and User Satisfaction in Heterogeneous Cellular Networks

In this paper, we address the joint problem of user association and resource allocation in wireless heterogeneous networks. Therefore, we formulate an optimization approach considering two objectives, namely, maximizing the number of served User Equipments (UEs) and maximizing the sum of the UE utilities. Precisely, the aim is to associate UEs with the optimal Radio Access Technology (RAT) and to allocate to these UEs the optimal Resource Units (RUs) based on their requested services and contracts. Our problem is challenging because it is mixed integer non-linear optimization. To tackle this difficulty, we provide a Mixed Integer Linear Programming (MILP) re-formulation of the problem that makes it computationally tractable. Various preferences for user association and resource allocation are conducted by tuning: on the one hand, the weights associated with different services and contracts, on the other hand, the weights associated with the considered two objectives. The optimal solution of the MILP problem is computed for a realistic network scenario and compared with legacy solution. Extensive simulation results show that the proposed optimization approach improves the overall network performance while considering the UE requested service and contract: it outperforms legacy solutions in terms of user satisfaction. Moreover, it provides an efficient distribution of UEs on the different RATs.