QoE preserving resource scheduling for M2M terminals and human users in LTE networks

We study in this paper the impact of supporting a large number of machine to machine (M2M) communication terminals in the 4th generation (4G) long term evolution (LTE) wireless networks. Our main focus in the study is on how to accommodate the large number of M2M devices without negatively impacting the human subscribers' quality of experience (QoE). We propose dividing the available radio resources between human users and M2M devices such that human users' QoE is preserved. Our proposal adds new M2M-specific quality of service (QoS) class indicators (QCIs) for classifying M2M traffic bearers. We use the new classes in a new priority-based scheduler to allocate radio resources to preserve human users' QoE and fairly fulfil M2M terminals' communication requests.