The long term evolution (LTE) standard plays an important role in the development of internet of things (IoT) and machine-to-machine (M2M) communication because of its high data rates, low latency, high flexibility and low cost. However, improvements are needed in the network to support the uplink-heavy traffic generated by M2M communication and also to ensure the diversity of service requirements of this communication and to control the performance reduction in the classical mobile services of human-to-human (H2H) communication. In this paper, we present a new LTE uplink scheduler that dynamically adjusts to the level of congestion of the network based on the current traffic information of each device to support the M2M traffic. Furthermore, the main goals of our approach are (i) satisfy the quality of service (QoS) requirements, (ii) ensure fair allocation of resources and (iii) control the impact of H2H traffic performance. The simulation results demonstrated that the proposed scheduling has good performance according to the three objectives aforementioned.
['Adyson Magalhães Maia', 'Dario Vieira', 'Miguel Franklin de Castro', 'Yacine Ghamri-Doudane']
A fair QoS-aware dynamic LTE scheduler for machine-to-machine communication