Rado: A Randomized Auction Approach for Data Offloading via D2D Communication

Yifei Zhu, Jingjie Jiang, Bo Li, Baochun Li

Abstract: Despite the growing deployment of 4G networks, the capacity of cellular networks is still insufficient to satisfy the ever-increasing bandwidth demand of mobile applications. Given the common interest of mobile users, Device-to-Device (D2D) communication has emerged as a promising solution to offload cellular traffic and enable proximity-based services. One of the main detriments for D2D communication is the lack of incentive for mobile users to share their content, since such sharing inevitably consumes limited resources and potentially jeopardizes user privacy. In this paper, we study the incentive problem in D2D communications. Specifically, we model the incentive in offloading scenario as an auction game. A trading network is constructed between an eNB and users, in which auctions are conducted to group offloading users and determine proper rewards. We further design a randomized auction mechanism to guarantee system efficiency and truthfulness. Extensive experiments verify the effectiveness of our mechanism in that it achieves a significant performance gain in comparison with baseline methods.