Facing the high data volume and low latency requirements of mobile Virtual Reality(VR) services, this paper established a partial cache content sharing model for mobile VR and simulated the social attribute-based content sharing cost minimization problem, in order to effectively reduce the data traffic of the core network and reduce the requesting cost of devices. The problem was decomposed into two sub-problems, namely, power optimization with mode selection and device association. A cost-based power optimization and mode selection algorithm and a matching algorithm based on social relationship and requesting cost were respectively proposed. Finally, the performance of proposed algorithms was evaluated through simulations and was compared with other schemes. The simu-lation results show that the content request mode selection and power optimization scheme based on partial cache can effectively reduce the requesting cost of content requesters.