Distributed Cache Placement and User Association in Multicast-Aided Heterogeneous Networks

The small cells have been equipped with caching and multicast capabilities to save energy and ease backhaul burden. However, given the increasing diversity of user association in heterogeneous networks, traditional schemes may fail to exploit the energy-saving potential of caching and multicast. In this paper, we propose the model to minimize total power consumption by jointly optimizing the user association and cache deployment. The formulated joint optimization problem is decomposed and reformulated as a NP-complete set partition problem. Motivated by the idea of the tactile networks, the devices can find the candidate user grouping based on its own utility. The utility function is judiciously designed to reduce the searching space without compromising optimality. Then, a heuristic caching algorithm is proposed by rigorously deriving the upper and lower bounds of cache placement. Simulation results show that our proposed scheme outperforms the other existing multicast and caching algorithms in terms of power consumption by up to 28%, while keeping the load among base stations balanced.