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Pushing files to users based on predicting the personal interest of each usermay provide higher throughput gain than broadcasting popular files to usersbased on their common interests. However, the energy consumed at base stationfor pushing files individually to each user is also higher than broadcast. Inthis paper, we propose an energy-saving transmission strategy forpre-downloading the files to each user by exploiting the excess resources inthe network during off-peak time. Specifically, a power allocation andscheduling algorithm is designed aimed to minimize the extra energy consumedfor pushing, where network and user level context information are exploited.Simulation results show that when the energy of both content placement andcontent delivery is taken into account, the proposed unicast strategy consumesless energy and achieves higher throughput than broadcasting when the filespopularity is not uniform and the personal interest prediction is with lessuncertainty.

Energy-saving Pushing Based on Personal Interest and Context Information