Energy-Saving Pushing Based on Personal Interest and Context Information

Abstract

Abstract-Pushing files to users based on predicting the personal interest of each user may provide higher throughput gain than broadcasting popular files to users based on their common interests. However, the energy consumed at base station for pushing files individually to each user is also higher than broadcast. In this paper, we propose an energy-saving transmission strategy for pre-downloading the files to each user by exploiting the excess resources in the network during off-peak time. Specifically, a power allocation and scheduling algorithm is designed aimed to minimize the extra energy consumed for pushing, where network and user level context information are exploited. Simulation results show that when the energy of both content placement and content delivery is taken into account, the proposed unicast strategy consumes less energy and achieves higher throughput than broadcasting when the files popularity is not uniform and the personal interest prediction is with less uncertainty.

Caching Policy Optimization for D2D Communications by Learning User Preference

“…Denote caching policy as C := (c k,f ) K×F , and the file set cached at the kth user as C k = {f f |c k,f = 1}. After optimizing C, the BS refreshes the caches of users during the off-peak time of each period, where the energy cost for placing the files can be minimized by using the method in [19].…”