Utility function maximization-based joint cell selection and power allocation for heterogeneous M2M communication networks

Machine-to-Machine (M2M) communications have received considerable attentions in recent years. By allowing machine type communications devices (MTCDs) to communicate with each other or with infrastructures under reduced human intervention, M2M communications are expected to offer a large variety of MTCD-related applications. While the vision of M2M communications is quite promising, the diverse quality of service (QoS) requirements and the complicated network architecture pose challenges and difficulties to resource allocation, cell selection and random access schemes, etc. In this paper, we take into account the impacts of random access on the transmission performance of the MTCDs and examine the energy efficiency of each MTCD. Applying the concept of utility function, we define network utility function and formulate the problem of joint cell selection and power allocation as a network utility function maximization problem. By applying iterative method and Lagrange dual method, the formulated optimization problem is solved and the optimal joint cell selection and power allocation strategy can be obtained. Simulation results demonstrate the effectiveness of the proposed algorithm.