Modeling and Analysis of mMTC Traffic in 5G Core Networks

Abstract

Massive Machine-Type Communications (mMTC) are one of the three main use cases powered by 5G and beyond networks. These are distinguished by the need to serve a large number of devices which are characterized by non-intensive traffic and low energy consumption. While the sporadic nature of the mMTC traffic does not pose an exertion on the efficient operation of the network, multiplexing the traffic from a large number of these devices within the cell certainly does. This traffic from the Base Station (BS) is then transported further towards the Core Network (CN), where it is combined with the traffic from other BSs. Therefore, planning carefully the network resources, both on the Radio Access Network (RAN) and the CN, for this type of traffic is of paramount importance. To do this, the statistics of the traffic pattern that arrives at the BS and the CN should be known. To this end, in this paper, we derive first the distribution of the inter-arrival times of the traffic at the BS from a general number of mMTC users within the cell, assuming a generic distribution of the traffic pattern by individual users. Then, using the previous result we derive the distribution of the traffic pattern at the CN. Further, we validate our results on traces for channel conditions and by performing measurements in our testbed. Results show that adding more mMTC users in the cell and more BSs in the network in the long term does not increase the variability of the traffic pattern at the BS and at the CN. Furthermore, this arrival process at all points of our interest in the network is shown to be Poisson both for homogeneous and heterogeneous traffic. However, the empirical observations show that a huge number of packets is needed for this process to converge, and this number of packets increases with the number of users and/or BSs.