Energy Efficiency and QoS Evaluation of Radio Resource Management Techniques for M2M Communications in LTE-Based Cellular Systems

Abstract

The recent cellular wireless networks must not only ensure the communication between users known as human to human (H2H) but also between a huge number of machines for machine-type communication (MTC) or machine to machine (M2M). M2M can be considered as devices that can establish communications with other devices without any human intervention. M2M is also seen as the base of the vision of connected objects. It tempts a lot of attention because it can be seen as a new opportunity for network operators and Internet of Things (IoT) service. Today, there are several types of MTC-based applications spanning multiple domains, such as health, transport, smart meters and surveillance. The deployment of this kind of application in mobile cellular networks, particularly Long-Term Evolution (LTE) and LTE-Advanced (LTE-A), cannot be effective without controlling the challenges posed by the deployment of a large number of MTC devices in the same cell. Indeed, the deployment of a myriad of MTC devices will cause the challenge of resource allocation for assuring the quality of service (QoS). As MTC devices are equipped with a non-rechargeable battery, power consumption is also among the main challenges facing M2M communications over Long-Term Evolution networks. In this article, we focused on the radio resource management in downlink LTE networks for M2M communication by a study of scheduling techniques that are: proportional fair (PF), exponential proportional fair (EXP)/PF), maximum-largest weighted delay first (MLWDF) and frame-level scheduler (FLS). We considered the video and VoIP services as real-time (RT) streams as well as best effort (BE) as non-real-time (NRT) streams, considering the QoS criteria in terms of throughput, fairness and energy, in order to conclude a distinct vision on the quality of experience provided by these algorithms. The results of analysis indicate that MLWDF scheduler is the best according to the energy and spectral efficiency than PF, EXP-PF and FLS techniques, while FLS is better in terms of quality of service (QoS) metrics for RT services.