A novel traffic generation framework for LTE network evolution study

The increasing needs of mobile internet application services running on smartphone is driving the evolution of wireless communication networks, due to the diversity of traffic characteristics in addition to the rapid growth of data volumes. Differently from typical internet services like web browsing and FTP, the pervasive usage of always-on applications can lead to frequent User Equipment (UE) transitions between Radio Resource Control (RRC) states, and result in excessive signaling traffic that need to be accounted in network capacity planning. In this paper, we propose a novel traffic generation framework to obtain the traffic flows generated by a smartphone which is running heterogeneous applications including both typical applications which are selected on the basis of a proposed application level traffic growth forecast, and keep-alive messages from always-on applications. Using such a framework, the radio resource consumed by different types of application can be evaluated. We exemplify the use of the proposed traffic modeling with a case study of a year-by-year radio resource consumption of voice traffic and keep-alive messages in a realistic LTE (Long Term Evolution) network scenario.