Energy efficiency of soft real time service in hyper-cellular network with users' behavior prediction

Many users require the same content, such as breaking news, newly released movies, and favorites videos. The same content is transmitted multiple times across wireless cellular network because current wireless network is designed to transmit data based on user requests, which exhausts wireless bandwidth and incurs high energy costs. This paper presents a soft real time service frame that is user-centric and content-aware. The frame broadcasts popular content to user equipment before users ask for it to achieve higher network energy efficiency and enhance quality of service. We propose a popularity prediction scheme, a target user group prediction scheme, a dynamic broadcast area calculation scheme, and a content pushing scheme. We build a system model to analyze key parameters in the service framework. As shown in simulations, the wireless network energy efficiency is improved 2 times with news contents in public cellular scenarios, and is improved 50 times with online study contents in campus cellular scenarios.