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A Lightweight Recommendation Framework for Mobile User's Link Selection in Dense Network
Ji Wang, Xiaomin Zhu, Weidong Bao and Guanlin Wu
National University of Defense Technology, National University of Defense Technology, National University of Defense Technology, National University of Defense Technology

With the proliferation of mobile devices and the development of communication technology, mobile devices have permeated every aspect of our daily lives. However, in dense network where large crowd of mobile devices try to access to the network simultaneously, the severe interference between mobile devices may incur a remarkable deterioration of the wireless communication quality. How to improve individual’s experience in such scenario is a critical yet open problem. Inspired by the mobile device users’ usage pattern as well as the characteristic of most wireless communication systems, we propose a framework offering uplink/downlink selection recommendation to different mobile device users to enhance their utility in this paper. The design of the framework starts with formulating the problem as a link selection game. Analysis shows that the game can be categorized as a generalized ordinal potential game whose Nash Equilibrium is guaranteed. We then devise a distributed link selection algorithm to generate a Nash Equilibrium of the game. To accommodate to the characteristic of dense network and the capacity limitation of mobile device, the design of the algorithm shows a light-weight property and does not require each mobile device user to know others’ current selection. The probability of incomplete information gathering is also considered. Extensive experiments are conducted to demonstrate the effectiveness and superiority of the proposed framework. Experimental results show that the global average utility increase rate reaches above 20%, and about 70% mobile device users can benefit from using our framework.