Sociality and Mobility-Based Caching Strategy for Device-to-Device Communications Underlying Heterogeneous Networks

Proactive content caching at the wireless network edge, such as users and small base stations (SBSs), is an effective way to deal with high mobile traffic. In this paper, based on the user mobility and social relationships, we investigate the optimal caching strategy in device-to-device (D2D) communications underlying heterogeneous networks, where several SBSs are within the coverage of a macrobase station (MBS). Except for SBSs, important users (IUs) hired by an operator also cache files. First, assuming that user preference, i.e., the probability distribution of different file requests of users, are unknown, we cluster users and predict each user preference based on their history file requests by fitting to the Zipf distribution. Second, we derive the closed-form expression of the average system cost by jointly considering the mobility of users and the social relationship between them. With the purpose of minimizing the average system cost, we optimize the SBSs and IU caching strategies. The optimization problem is NP-complete. To solve the problem, we demonstrate that this problem belongs to the minimization of a supermodular function over a partition matroid, and thus, we provide a locally greedy caching algorithm with an approximation ratio of 2 to obtain the sub-optimal solution in polynomial time. Finally, since the operator can reduce the system cost by hiring more IUs, requiring higher payments, we reach a tradeoff by determining the number of IUs. The simulation results show that the proposed caching strategy outperforms the traditional caching strategy, and the suboptimal solution obtained by proposing the greedy algorithm is close to the optimal solution.