Caching Improvement Using Adaptive User Clustering

Abstract

In this article we explore one of the most promising technologies for 5G wireless networks using an underlay small cell network, namely distributed 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 by the users.We propose a new method, in which, instead of caching the most popular content, which is the most common approach, we propose a scheme in which users within the network are clustered according to there content popularity. The small base stations will then cache the content according to the average popularity profile of the users within each cluster. We present also a method for estimating the number of users clusters within the network based on the Akaike information criterion. We analytically derive a closed form expression of the hit probability as a function of the system parameters and we propose an optimization problem in which the Small base stations association with users clusters is optimized.