On consideration of content preference and sharing willingness in D2D assisted offloading

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.