Fundamentals of Cluster-Centric Content Placement in Device-to-Device Networks

We develop a comprehensive analytical framework with foundations in stochastic geometry to characterize the performance of cluster-centric content placement in a device-to-device (D2D) network. Different from device-centric content placement, cluster-centric placement focuses on placing content in each cluster such that the collective performance of all the devices in each cluster is optimized. Modeling the locations of the devices as a Poisson cluster process, we first show that the coverage optimal performance can be achieved by placing content of interest for each cluster at the device closest to its cluster center. Since this restricts the frequency reuse within a cluster to one, and may not also be feasible due to storage/energy limitations, we also characterize the network performance in terms of coverage probability and area spectral efficiency (ASE) for a general class of strategies in which the content of interest for the typical device is available at the k-th closest device to the cluster center. Our analysis concretely demonstrates significant improvement in network performance when the content of interest for the typical device is biased to lie closer to the cluster center compared to the case when it is placed at a randomly chosen device.