Performance Assessment of MachineType Communication Data Traffic in a Small Cell Field Environment MachineType Communication (MTC) has been identified as an important use case for 4G Long Term Evolution (LTE) wireless technology. 3GPP has previously introduced MTC for lowpower, widearea networks supporting the Internet of Things (IoT). This paper presents laboratory experimentation to evaluate MachineType Communication (MTC) performance in a Small Cell Evolved Universal Terrestrial Radio Access Network (EUTRAN) field environment with presence of legacy 4G User Equipment (UEs). The performance of the MTC UEs and legacy UEs in terms of RRC attempts and success, EUTRAN Radio Access Bearer (ERAB) establishment attempts and success, and ERAB drop Key Performance Indicators (KPI) are evaluated. The performance in terms of Downlink and Uplink data throughput for Small Cell EUTRAN system with MTC and legacy UEs are also captured. These performance results have been evaluated through experimental studies and compared with the defined benchmarks of the 3GPP standards to ensure overall call processing stability of the Small Cell EUTRAN system. This experimentation endorses that the KPIs and throughputs of MTC as well as legacy 4G UEs meets the defined 3GPP target values there by leveraging the benefits of MTC UEs in the Small Cell EUTRAN environment. This study assists the mobile operators to deploy MTC UEs confidently in the Small Cell system with the existing legacy 4G UEs.

Characterizing Delay and Control Traffic of the Cellular MME with IoT Support Massive Internetofthings (MIoT) represents one of the main use cases of 5G, as well as one of the most challenging ones. Accordingly, MIoT traffic is given special treatment in the core network, with the Mobility Management Entity (MME) serving both control and data traffic. In this context, it is critical to properly dimension the MME and to adapt its capability to traffic fluctuations. To this end, we present a compact, closed form linking the number of IoT sources with the rate at which bearers are requested from the MME, and such a rate delay incurred by MME operations. Our model represents a valuable tool to make effective, realtime scaling decisions in virtualized cellular core networks.