Popularity based file categorization and coded caching in 5G networks
In this paper, we will study the capacity of 5G cellular networks with caching. We first investigate the capacity using uncoded caching and then we study the capacity of such networks using a novel technique based on file categorization and coded cache placement. In our cache placement strategy, we propose to create file groups with approximately similar popularity levels (within a factor of two) and then we randomly code the files in each file group together and place them in the User Terminal (UT) caches. We prove that this technique can significantly increase the network capacity by reducing the average traffic. Our proposed coded cache placement strategy is decentralized and performs close to optimal. Simulation results also confirm our theoretical results.