Context-aware and priority-based user association and resource allocation in heterogeneous wireless networks

Abstract : Heterogeneous wireless networks (HWNs) are usually characterized by the integration of cellular networks and wireless local area networks (WLANs) to meet user requirements and enhance system capacity. This paper proposes a user association and downlink resource allocation algorithm in HWNs with users having different priorities. The proposed solution employs contextual information related to the preferences of the users, their requested data rate, and the characteristics of networks. The user preference is translated through a profit function that is based on the received signal quality and the power consumption at mobile terminals (MTs). Accordingly, an optimization problem is formulated to maximize the overall user satisfaction for each priority level. The formulated problem throws firm restrictions to prevent low-priority users from allocating resources utilized by other users with higher priorities. We then propose a novel heuristic approach with polynomial-time complexity to approximate the formulated problem. Furthermore, the system architecture is discussed and a new solution management strategy is proposed to limit the complexity of the algorithm. Simulation results show that the proposed approximation method maintains the nearest performance to the optimal solution.
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Mohamad Zalghout, Ayman Khalil, Matthieu Crussière, Samih Abdul-Nabi, Jean-François Hélard. Context-aware and priority-based user association and resource allocation in heterogeneous wireless networks. Computer Networks, Elsevier, 2019, 149, pp.76-92. ⟨10.1016/j.comnet.2018.11.001⟩. ⟨hal-01978032⟩

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