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 information source (so-called extended floating car data). To reduce the impact of MTC traffic on the quality of service (QoS) of human users, this paper presents a client-controlled channel-aware transmission (CAT) strategy. A new Markovian model of the Long Term Evolution (LTE) radio resources assuming heterogeneous MTC and H2H traffic is used to evaluate the performance of this approach. The close-to-reality parameterization of the model is achieved by laboratory LTE data rate measurement campaigns and ray-tracing analyses. The model demonstrates that the CAT scheme decreases the LTE cell utilization and improves the QoS in terms of blocking probability of H2H communication. The results regarding CAT are validated in an independent simulation and by LTE field measurements. Beyond this, the influence of different MTC traffic models, including best- and worst-case investigations, is provided.