The smartphone's signaling effect on LTE core network -

Abstract

The world is rapidly moving towards the convergence of communication, computing and IP-based networks. With the smartphones invasion and the massive amount of services and applications available, The Long Term Evolution (LTE) is seen to be the key enabler for delivering the fourth generation of mobile broadband. Furthermore, LTE is huge step toward this convergence since it is the first pure IP-based cellular technology. As such, LTE networks are expected to achieve wide scale adoption worldwide. However, along with the proliferation of powerful smartphones and the diverse IP-based mobile applications, enormous amounts of data and signaling traffic are injected into the mobile network. Thus, mobile operators face additional burden in order to protect their networks, maintain good quality of service, and avoid any possible bottlenecks or node failures. This work sakes to study the effects of smartphone applications on the LTE core network. By profiling some of the most popular smartphone’s applications using Wireshark sniffer, and then inject the profiled data into Opnet simulator. Furthermore, in order to achieve less signaling overheads and more efficient battery consumption at the mobile device, we have proposed an optimization algorithm to decide when it is optimal for a UE to transit between LTE power states. This decision is based on probabilistic estimation using a traffic pattern model generated from an auto-learning algorithm running on the UE side. After experimentally evaluating the proposed algorithm, a decrease of 10 to 30percent was achieved.