User-cell association in heterogenous small cell networks: A context-aware approach

Deploying small cells to complement the traditional cellular networks is foreseen as a major feature of the next generation of wireless networks. In this paper, a novel approach for addressing the cell association problem in heterogenous small cell networks is proposed. The presented approach exploits different types of information extracted from the user devices and environment to improve the way in which users are assigned to their serving small cell base stations (SBSs). We formulate the problem within the framework of matching theory, where the players, namely the users and SBSs, have interdependent preferences over the members of the opposite set. We also utilize the fuzzy synthetic evaluation to formulate the preference of SBSs over the users. To solve the problem, we propose a novel algorithm that leads to a stable matching among the users and SBSs and the proposed approach can balance the traffic among the cells while also satisfying the QoS of the users. Simulation results present that the proposed context-aware matching approach yields significant performance gains, in terms of the average utility per user, when comparing with some other approaches.