Performance of Channel-Aware M2M communications based on LTE network measurements

The interaction between Machine-to-Machine (M2M) Communications, also known as Machine-Type Communications (MTC), and Human-to-Human (H2H) Communications is a recent topic in the context of cellular networks like Long Term Evolution (LTE). In this paper, we evaluate the performance of Channel-Aware MTC (CAT) based on LTE resource allocation measurements of a real LTE deployment. By means of a novel measurement setup, which uses a real-time spectrum analyzer, the LTE resource utilization in terms of occupied Resource Blocks (RBs) of the uplink is quantified for different channel conditions. Furthermore, the resource distribution in time and frequency domain, which is determined by the scheduler, is analyzed in this paper allowing for the calculation of average data rates and the spectral efficiency. The measurement results are used to quantize the potential gain of CAT. It is shown that by means of the scheme, the influence of MTC on other LTE users can be significantly reduced. In addition, the fraction of available RBs can be increased by 47%.