MTC data aggregation for 5G network slicing

Recently network slicing has been identified as a promising network architectural technology for the next generation mobile cellular networks (5G) to address the challenges stemming from a wide range of applications. Especially, for machine type communication (MTC) application, it is widely recognized that traditional cellular network architecture is not adequate to meet the requirements in terms of massive connectivity and low latency. For exploiting network slicing, data aggregation (DA) can be adopted to effectively address the massive connectivity and latency requirement. In this paper, we propose an efficient network slicing data aggregation (NSDA) scheme for MTC applications. Different from conventional DA scheme where data aggregation is performed based on device locations, we perform DA according to latency requirement for MTC devices (MTCDs), with aim to exploit the benefits of network slicing and thus improve network access capacity and decrease access latency. We formulate the DA problem as a 0–1 Linear Programming and propose an efficient two-step algorithm to aggregate the MTC data for accessing a specific network slice. We examine the performance of our proposed NSDA in typical MTC scenarios via simulations. Numerical results reveal that NSDA significantly outperforms traditional MTC access schemes (without network slicing) in terms of network capacity, access congestion degree, latency, etc.