Machine-to-machine data traffic multiplexing in LTE-advanced networks

Abstract

Machine-to-Machine (M2M) communication is one of the latest areas of future communication networks which will enables billions of intelligent devices to communicatewith each other without or with small human intervention. The application domains employing these M2M devices include Intelligent Transport System (ITS), Smart Metering and Monitoring, Home Automation, E-healthcare, Transportation and Logistics, Safety and Emergency and industrial applications. Advancements in cellular communication have resulted in the emergence of M2M communication due to the wide range, coverage provision, decreasing costs and high mobility support of cellular networks. Long Term Evolution Advanced (LTE-A) is a recent Third Generation Partnership Project (3GPP) cellular standard and is a promising technology to support future M2M data traffic. Several researchers have suggested LTE-A as a candidate to support future M2M communication. However, the cellular standards are designed to support Human-Type-Communication (HTC). In recent years, HTC traffic has seen exponential growth over cellular networks. This growth demands increased capacity and higher data rates. Latest cellular standards use multi-carrier transmission schemes such as Orthogonal Frequency Division Multiplexing (OFDM) to meet the increasing demands of HTC traffic. These networks are expected to face challenges due to the future M2M data traffic with various Quality-of-Service (QoS) requirements such as provision of radio resources to a large number of M2M devices, prioritization and inter-device communication. The current cellular systems might run out of capacity due to additional M2M traffic, resulting in the performance degradation of regular mobile traffic. M2M devices transmit small and large sized data with distinct QoS requirements. For instance, e-healthcare devices transmit small sized data but are delay sensitive. The Physical Resource Block (PRB) is the smallest radio resource which is allocated to a single device for data transmission in LTE-A. In the M2M applications with devices transmitting small sized data, the capacity of the PRB is not fully utilized. This results in significant degradation of the system performance. This thesis proposes an M2M data aggregation scheme for efficient utilization of the LTE-A radio resources for M2M communication. In the proposed scheme, LTE-A radio resources are efficiently utilized by aggregating the data of several M2M devices. The resources are shared by the M2M devices to enhance the spectral efficiency of the system. A simulation approach is used to evaluate the performance of the proposed scheme. Several scenarios are simulated to evaluate the impact of M2M data traffic on regular LTE-A traffic. The simulated LTE-A traffic classes include File Transfer Protocol (FTP), Voice over IP (VoIP) and video users. The scenarios are categorized into M2M narrowband and broadband applications. The results show significant impact of M2M data traffic on low priority LTE-A traffic. The network end-to-end performance is improved by aggregating data of several M2M devices which is determined by simulating several scenarios. Considerable performance improvement is achieved in terms of average cell throughput, FTP average upload response time, FTP average packet end-to-end delay and radio resource utilization.