Decoupled Multiple Association in Full-Duplex Ultra-Dense Networks: An Evolutionary Game Approach

User association is indispensable for the operation of wireless network and has critical impacts on system performance. For most existing work, user associations are typically coupled, which require a user equipment (UE) to associate with the same base station (BS) in uplink (UL) and downlink (DL). However, wireless networks are becoming heterogeneous and densifying, which generates intrinsic distinctions (transmission power, data traffic and backhaul capacity etc.) between UL and DL. Accordingly, coupled association may no longer be optimal. In this work, we explore decoupled user association in full-duplex ultra-dense networks (UDNs), which allows a UE to associate with different BSs in UL and DL respectively. Furthermore, to fully exploit the benefits of UDNs, multiple association, referring to associating a UE with multiple BSs, is jointly adopted in UL and DL. Considering the dynamic and complicated association process, an evolutionary game (EG) is formulated, where UEs are players, and their strategies are association selections in UL/DL. Particularly, evolutionary equilibrium is viewed as the stable solution to the formulated problem. Moreover, an EG-based algorithm with low complexity is proposed for decoupled multiple association. Numerical results validate the convergence of the proposed algorithm for strategy adoption. Besides, the impacts of information exchange delay and learning rate are investigated for providing a better association decision.