In this article we explore one of the most promising technologies for 5G wireless networks using an underlay small cell network, namely proactive caching. Using the increase in storage technologies and through studying the users behavior, peak traffic can be reduced through proactive caching of the content that is most probable to be requested. We propose a new method, in which, instead of caching the most popular content, the users within the network are clustered according to their content popularity and the caching is done accordingly. We present also a method for estimating the number of clusters within the network based on the Akaike information criterion. We analytically derive a closed form expression of the hit probability and we propose an optimization problem in which the small base stations association with clusters is optimized.
@article{arxiv.1605.09602,
title = {Caching Improvement Using Adaptive User Clustering},
author = {Salah Eddine Hajri and Mohamad Assaad},
journal= {arXiv preprint arXiv:1605.09602},
year = {2016}
}