Client-Based Control of the Interdependence Between LTE MTC and Human Data Traffic in Vehicular Environments


The interdependence between machine-type communication (MTC) and human-to-human (H2H) communication has become a major topic for the development of cellular communication systems. One example of MTC application is dynamic traffic forecast, which uses sensors that are mounted on cars as an data source (therefore-referred to as extended floating car data). To cut back the impact of MTC traffic on the standard of service (QoS) of human users, this paper presents a shopper-controlled channel-aware transmission (CAT) strategy. A replacement Markovian model of the Long Term Evolution (LTE) radio resources assuming heterogeneous MTC and H2H traffic is employed to judge the performance of this approach. The shut-to-reality parameterization of the model is achieved by laboratory LTE information rate measurement campaigns and ray-tracing analyses. The model demonstrates that the CAT theme decreases the LTE cell utilization and improves the QoS in terms of blocking probability of H2H communication. The results concerning CAT are validated in an freelance simulation and by LTE field measurements. Beyond this, the influence of different MTC traffic models, including best- and worst-case investigations, is provided.

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