Machine-to-machine (M2M) communication is becoming an increasingly essential part of mobile traffic and thus also\na major focus of the latest 4G and upcoming 5G mobile networks. M2M communication offers various ubiquitous\nservices and is one of the main enablers of the Internet-of-things (IoTs) vision. Nevertheless, the concept of mobile\nM2M communication has emerged due to the wide range, coverage provisioning, high reliability as well as\ndecreasing costs of future mobile networks. Resultantly, M2M traffic poses drastic challenges to mobile networks,\nparticularly due to the expected large number of devices sending small-sized data. Moreover, mobile M2M traffic is\nanticipated to degrade the performance of traditional cellular traffic due to inefficient utilization of the scarce radio\nspectrum. This paper presents a novel data aggregation and multiplexing scheme for mobile M2M traffic and thus\nfocuses on the latest 3GPP (3rd Generation Partnership Project) tong-term-evolution-advanced (LTE-A) networks. 3GPP\nstandardized layer 3 inband Relay Nodes (RNs) are used to aggregate uplink M2M traffic by sharing the Physical\nResource Blocks (PRBs) among several devices. The proposed scheme is validated through extensive system level\nsimulations in an LTE-A based implementation for the Riverbed Modeler simulator. Our simulation results show that\nbesides coverage extensions, RNs serve approximately 40% more M2M devices with the proposed data multiplexing\nscheme compared to the conventional without multiplexing approach. Moreover, in this paper an analytical model is\ndeveloped to compute the multiplexing transition probabilities. In the end, the simulation and analytical results of\nmultiplexing transition probabilities are compared in order to analyze the multiplexing scheme.
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