Mobility-driven user-centric AP clustering in mobile edge computing-based ultra-dense networks

ultra-Dense Network (UDN) has been envisioned as a promising technology to provide high-quality wireless connectivity in dense urban areas, in which the density of Access Points (APs) is increased up to the point where it is comparable with or surpasses the density of active mobile users. In order to mitigate inter-AP interference and improve spectrum efficiency, APs in UDNs are usually clustered into multiple groups to serve different mobile users, respectively. However, as the number of APs increases, the computational capability within an AP group has become the bottleneck of AP clustering. In this paper, we first propose a novel UDN architecture based on Mobile Edge Computing (MEC), in which each MEC server is associated with a user-centric AP cluster to act as a mobile agent. In addition, in the context of MEC-based UDN, we leverage mobility prediction techniques to achieve a dynamic AP clustering scheme, in which the cluster structure can automatically adapt to the dynamic distribution of user traffic in a specific area. Simulation results show that the proposed scheme can highly increase the average user throughput compared with the baseline algorithm using max-SINR user association and equal bandwidth allocation, while it guarantees at the same time low transmission delay.