A dynamic backoff approach to control the congestion in M2M communication over LTE networks

Abstract

Machine-to-machine communication (M2M) is a technology to provide information exchange between devices without human intervention. Due to infrastructure characteristics, LTE networks are highly expected to become the deployment network of M2M devices. The integration of the M2M technology in LTE plays an important role in the development of applications for the Internet of Things. However, the M2M communication poses some challenges to these networks, with highlight to the congestion and overload problem in the radio access network (RAN) during the random access procedure caused by the huge number of devices. Thus, mechanisms to control the overload and congestion are required to deal with such scenarios. In this paper, we describe the random access procedure of LTE and we propose a solution to mitigate the impact of the M2M communication. More specifically, we first model how the backoff time should be divided among the H2H and M2M devices as a bankruptcy problem. In a second moment, we apply two solutions for the bankruptcy problem using a game theory framework and an axiomatic approach. The simulation results show that our approaches present improvements in energy efficiency and controls the impact of M2M devices over H2H devices. In addition, we also provide priority among M2M devices with high priority and low priority.