Resource Efficient Mobile Communications for Crowd-Sensing

Due to continuously growing communication traffic of emerging mobile phone applications, resource-efficient communication is a key to affordable network services with high Quality of Experience. While some communication traffic requires immediate resource allocations (such as voice services), an increasing number of mobile phone applications produce a lot of background communication traffic (e.g. social network apps, crowd sensing services). In this paper we discuss the predictive Channel-Aware Transmission (pCAT) scheme, which leverages the fact, that favorable channel conditions require much less spectrum resource allocation than bad channel conditions. By leveraging the knowledge of user trajectories and recurring spots with favorable channel conditions, the so-called LTE connectivity hot spots, background traffic transmissions can be scheduled by the client according to expected channel quality and application data priority. Thereby, the spectrum consumption of background traffic of applications can be reduced significantly. At the same time, the efficient usage of spectrum resources has also an impact on the battery lifetime of the mobile devices. By introducing the Context-Aware Power Consumption Model (CoPoMo) for LTE communications, we highlight, how decisions about the spectrum resource allocation by the network will impact the battery lifetime. One case study will show, that by simply changing the resource allocation scheme and without the need for spending more spectrum resources, the power consumption can be reduced by more than 70% using the Energy-Efficient Scheduling (EES) introduced in this paper.