Statistical Description and Analysis of the Concurrent Data Transmission from Massive MTC Devices

The concurrent data transmission from massive machine type communications (MTC) devices within a short time period makes the traffic flow of MTC more bursty. The classic Markovian traffic models under the assumption of Poisson arrival, whose inter-arrival time (IAT) is a negative exponentially distributed random variable with infinite support range, are no longer suitable for this situation. Beta distribution, a distribution with finite support range, is then proposed by 3GPP to account for this and used to serve as the IAT of MTC. The researches on the traffic modeling based on Beta distribution is still in its very initial step and is rarely reported in state of the art literatures. This article takes the initiatives to discuss some prime issues for MTC traffic modeling under the assumption of Beta arrival. By the usage of renewal theory and Volterra integral equation of the second kind with difference kernel, we present the methodology to deduce the access intensity of MTC arrival process, which is defined as the mean number of renewals by time t. Numerical results show that in the context of MTC, there is a sharp increase in the number of access requests from MTC devices which directly causes the well-known congestion problem of MTC. And the ratio of  and  of Beta( ,  ) distribution to some extent can be used as a metric to represent the burstiness of Beta distribution or that of MTC. These works together provide researchers and engineers a basis to appropriately choose traffic models for different MTC applications.