Content Preference-aware User Association and Caching in Cellular Networks

The ever-growing trend of mobile users to consume high quality videos in their devices has pushed the backhaul network to its limits. Caching at Small-cell Base Stations (SBSs) has been established as an effective mechanism for alleviating this burden. Next generation mobile networks promise high Access Network density, hence multiple SBS association options per mobile user may exist. In this paper, we study the joint problem of mobile user association to SBSs and content placement to SBS-collocated caches, aiming to further optimize the utilization of backhaul network. The problem is solved periodically, considering time intervals where the users’ location to the system is assumed to be fixed. First, we decompose the joint problem into two sub-problems that are solve sequentially, namely the content preference similarity-driven user association and the demand aware content placement sub-problems. We then propose a heuristic that consists of multiple phases. In particular, at a preparation phase, it performs clustering of users based on the similarity of their content preferences, accounting also for geographical constraints. The resulting clusters are then utilized for the demand-aware association of users to the SBS, while the placement of content is driven by the resulting local demand in each SBS, and takes place at the end. We demonstrate the effectiveness of our heuristic by evaluating its performance against multiple schemes that either lack a preparation phase or do not account for geographical constraints. As it is evident through the numerical results, the user clustering that takes place during the preparation phase can increase the overall cache hit ratio up to 20%.

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