Optimal Coded Caching in 5G Information-Centric Device-to-Device Communications
Xingyan Chen, Changqiao Xu, Mu Wang, Tengfei Cao, Lujie Zhong, Gabriel‐Miro Muntean · 2018
As one of the key technologies for future 5G, Device- to-Device communications (D2D) offloads traffic to local by enabling mobile equipment directly communicating with each other, which perfectly supporting distributed applications and IoT scenarios. Integrating Information-centric networking (ICN) with D2D is becoming an attractive trend because of the superior advantages of inherent support of caching and name-based routing. Nevertheless, efficient caching in ICN D2D still remain problematic due to the low utilization of caching space and multicast feature of wireless scenarios. In this paper, we propose a novel optimal coded content caching mechanism for ICN-based 5G D2D. We first building a fluid-based model to describe how the roles of mobile nodes evolve with the user behaviors and caching strategy. We then accordingly formulate the coded caching problem as an optimization problem, which mainly considers the tradeoff between delivery latency and energy consumption. The existence of optimal solutions is proved theoretically. We further propose a Learn Tree- based Code Content (LTCC) mechanism to cluster the contents for content coding selection and an Optimal Coded Content Caching (O3C) algorithm to solve coded content caching problem. Finally, we conduct massive simulation tests to validate the performance of the proposed algorithm against the state-of-art solutions.