Spectrum sharing approaches for machine-type communications over LTE heterogeneous networks

Abstract

Machine-type communications (MTC) are expected to be a key enablers in the Internet of Things (IoT) ecosystem by providing ubiquitous connectivity among a new type of small devices (e.g., sensors, wearable devices, smartphone) without (or with minimal) the need of human intervention. In such a scenario, the architecture as well as the radio resource management (RRM) of next-to-come 5G systems needs to be enhanced in order to cope with the exponential growth of lowlatency and low-energy MTC traffic. To this end, we propose a dynamic RRM policy which (i) exploits an heterogeneous networks (HetNets) deployment aiming to handle massive huge load of MTC devices and (ii) adopts a spectrum sharing approach tailored to improve the spectrum utilization in MTC environments. By comparing our proposal with current policies in literature, simulations conducted through the open-source Network Simulator 3 (NS-3) shown that our proposed use of spectrum sharing technique can efficiently improve the performance of MTC traffic in terms of spectral efficiency, power consumption, and fairness.