  Device-to-device (D2D) assisted offloading heavily depends on the
participation of human users. The content preference and sharing willingness of
human users are two crucial factors in the D2D assisted offloading. In this
paper, with consideration of these two factors, the optimal content pushing
strategy is investigated by formulating an optimization problem to maximize the
offloading gain measured by the offloaded traffic. Users are placed into groups
according to their content preferences, and share content with intergroup and
intragroup users at different sharing probabilities. Although the optimization
problem is nonconvex, the closed-form optimal solution for a special case is
obtained, when the sharing probabilities for intergroup and intragroup users
are the same. Furthermore, an alternative group optimization (AGO) algorithm is
proposed to solve the general case of the optimization problem. Finally,
simulation results are provided to demonstrate the offloading performance
achieved by the optimal pushing strategy for the special case and AGO
algorithm. An interesting conclusion drawn is that the group with the largest
number of interested users is not necessarily given the highest pushing
probability. It is more important to give high pushing probability to users
with high sharing willingness.
