Social-aware content downloading mode selection for D2D communications

With the emerging demands for local area services of popular content downloading, D2D communication is recognized as a promising technical support for cellular networks. In this work, we propose a social-aware content downloading mode selection scheme, which involves a novel mode, named MD2D, by collaborating multiple available D2D links. In particular, we construct a social-aware evaluation framework, which understands the interplay between physical transmission property and social networking characteristics for defining the performance metric with respect to the downloading mode selection. Accordingly, we formulate the social-aware content downloading mode selection problem based on the combinatorial auctions. By exploring the submodular approximation of this problem, we design a social-aware mode selection algorithm. We demonstrate that the solution achieves incentives for content contribution and resistance to misbehaving potential content providers, and also derive a theoretic upper bound of the corresponding performance loss.