In recent years, machine-to-machine (M2M) communications have attracted great attentions from both academia and industry. In M2M communication systems, machine type communication devices (MTCDs) are capable of communicating with each other intelligently under highly reduced human interventions. Although diverse types of services are expected to be supported for MTCDs, various quality of service (QoS) requirements and network states pose difficulties and challenges to the resource allocation and clustering schemes of M2M communication systems. In this paper, we address the joint resource allocation and clustering problem in M2M communication systems. To achieve the efficient resource management of the MTCDs, we propose a joint resource management architecture, and design a joint resource allocation and clustering algorithm. More specifically, by defining system energy efficiency as the sum of the energy efficiency of the MTCDs, the joint resource allocation and clustering problem is formulated as an energy efficiency maximization problem. As the original optimization problem is a nonlinear fractional programming problem, which cannot be solved conveniently, we transform the optimization problem into power allocation subproblem and clustering subproblem. Applying iterative method-based energy efficiency maximization algorithm, we first obtain the optimal power allocation strategy based on which, we then propose a modified K-means algorithm to obtain the clustering strategy. Numerical results demonstrate the effectiveness of the proposed algorithm.

Introduction

Machine to machine (M2M) communication technology has been considered as one of the promising approaches to realize the Internet of things (IoT) in the 5th generation network [1]. In M2M, machine type communication devices (MTCDs) are capable of communicating with each other intelligently under highly reduced human interventions [2]. To guarantee the quality of service (QoS) requirements of the MTCDs and achieve performance enhancement of the M2M communication systems, efficient radio resource management schemes should be designed [3]. To further enhance the transmission performance of MTCDs, clustering mechanisms can be applied where the MTCDs are divided into groups or clusters with each cluster consisting of one cluster head (CH) and certain number of cluster members (CMs). By applying clustering schemes, the efficiency of data transmission can be enhanced and the energy consumption required for the MTCDs to transmit data packets can be reduced significantly [4]. Although the problem of resource allocation and clustering has been studied for M2M communications in previous research work, it can be shown that the two problems are highly related and the associated strategies may jointly affect user QoS and network performance. In this paper, we address the joint resource allocation and clustering problem in M2M communication systems. To achieve the efficient resource management of the MTCDs, we propose a joint resource management architecture, and design a joint resource allocation and clustering algorithm.