Service Characteristics-Oriented Joint ACB, Cell Selection, and Resource Allocation Scheme for Heterogeneous M2M Communication Networks

Abstract

Heterogeneous machine-to-machine communication networks (HMCNs) are expected to provide ubiquitous connectivity for machine type communication devices (MTCDs) with reduced human intervention. Although various types of services will be supported for MTCDs, diverse quality of service requirements and network characteristics pose challenges and difficulties to the resource allocation, cell selection, and random access schemes of the HMCNs. In this paper, we propose a joint access class barring (ACB), cell selection, and resource allocation algorithm for HMCNs. To achieve efficient utilization of the resource blocks (RBs) in heterogeneous cells, we first propose a virtual clustering-based joint ACB and RB allocation sub-algorithm. Partitioning the MTCDs into virtual clusters, we formulate the joint ACB and RB allocation problem of the virtual clusters as RB utilization maximization problem. Through solving the optimization problem, we obtain the optimal ACB factor and RB allocation strategy. Given the optimal strategy, we then formulate the joint cell selection and power allocation problem of the MTCDs as a utility function maximization problem. As the formulated problem is a mixed nonlinear optimization problem, which cannot be solved conveniently, we transform the problem using relaxation method and solve it through applying an iterative algorithm and the Lagrange dual method. Simulation results demonstrate the effectiveness of the proposed algorithm.