On Consideration of Content Preference and Sharing Willingness in D2D Assisted Offloading

Yijin Pan, Cunhua Pan, Huiling Zhu, Qasim Ahmed, Ming Chen, Jiangzhou Wang

Research output: Contribution to journalArticlepeer-review

54 Citations (Scopus)


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.
Original languageEnglish
Article number7875158
Pages (from-to)978-993
Number of pages16
JournalIEEE Journal on Selected Areas in Communications
Issue number4
Early online date9 Mar 2017
Publication statusPublished - 1 Apr 2017
Externally publishedYes

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